Imaging Pearls ❯ September 2025
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3D and Workflow
- First, we must understand that burnout is correlated to how and where we spend our time and effort, and it is imperative to note that both are valuable but limited resources. Understanding that fact, it is easy to see that the ubiquitous phrase “work-life balance” is a misnomer. Attempting to achieve balance by overloading one side of the scale to equal the other is not only a waste of valuable energy but also counterproductive, adding stress and accelerating burnout. A much better way of tackling this issue is by focusing on work-life harmony.
The Elevation Approach for Work-Life Harmony.
Wells T, Fishman EK, Chu LC, Rowe SP, Crawford CK.
J Am Coll Radiol. 2025 Aug;2 2(8):972-974. - Adopting a new strategy for achieving work-life harmony can be challenging, regardless of your stage in life or career. Furthermore, incorporating 12 new principles while testing your Elevation Approach may seem daunting. The final piece of advice is to select the three principles you believe will most effectively enhance your work-life harmony. It’s easy to become fixated on setting goals and using every available tool to achieve them, but more tools do not necessarily lead to a better approach for you. Remember, the Elevation Approach is not about achieving every set goal; rather, it is designed to create a framework that helps elevate your everyday life.
The Elevation Approach for Work-Life Harmony.
Wells T, Fishman EK, Chu LC, Rowe SP, Crawford CK.
J Am Coll Radiol. 2025 Aug;2 2(8):972-974. - In that context, then importance of emphasizing “work-life harmony” over “work-life balance” is particularly crucial. If there are periods of time during which there will be imbalance and a necessary single-minded focus on work, ensuring that friends and family understand and support the radiologist during that period is paramount. Ultimately, with supportive friends and family and the right work environment, we can achieve “work-life harmony,” whereby a successful professional life improves our mental well-being and feeds into healthy personal relationships, while at the same time the healthy personal relationships free us mentally to focus on work and excel professionally.
The Elevation Approach for Work-Life Harmony.
Wells T, Fishman EK, Chu LC, Rowe SP, Crawford CK.
J Am Coll Radiol. 2025 Aug;2 2(8):972-974.
Adrenal
- Background: Adrenal lesions, often incidentally detected, present diagnostic challenges in distinguishing benign from malignant or hormonally active lesions. Conventional imaging(computed tomography/magnetic resonance imaging (CT/MRI)) has limitations, driving interest in artificial intelligence (AI) and radiomics for enhanced accuracy.
Objectives: To systematically evaluate AI and radiomics applications in adrenal lesion characterization, focusing on diagnostic performance, methodologies, and clinical utility.
Conclusion: CT-based radiomics outperformed MRI, aligning with guidelines favoring CT for adrenal assessment. AI-enhanced models show promise in refining diagnostics and reducing invasive procedures. However, retrospective designs, small cohorts, and protocol variability limit generalizability. Future work requires multicenter collaboration, standardized protocols, and prospective validation to translate AI/radiomics into clinical practice. - Conclusion: CT-based radiomics outperformed MRI, aligning with guidelines favoring CT for adrenal assessment. AI-enhanced models show promise in refining diagnostics and reducing invasive procedures. However, retrospective designs, small cohorts, and protocol variability limit generalizability. Future work requires multicenter collaboration, standardized protocols, and prospective validation to translate AI/radiomics into clinical practice .
Artificial intelligence and radiomics applications in adrenal lesions: a systematic review
Matteo Ferro , Octavian Sabin Tataru , Giuseppe Carrieri et al.
Ther Adv Urol 2025, Vol. 17: 1–17 
Artificial intelligence and radiomics applications in adrenal lesions: a systematic review
Matteo Ferro , Octavian Sabin Tataru , Giuseppe Carrieri et al.
Ther Adv Urol 2025, Vol. 17: 1–17- Given the limitations of current imaging modalities in accurately characterizing adrenal lesions, the integration of artificial intelligence and radiomics presents a significant opportunity to improve diagnostic precision. In this review, CT-based radiomics achieved a mean AUC of 0.88, outperforming MRI-based radiomics (mean AUC: 0.82), thus confirming CT as the preferred modality for adrenal lesion characterization.
Artificial intelligence and radiomics applications in adrenal lesions: a systematic review
Matteo Ferro , Octavian Sabin Tataru , Giuseppe Carrieri et al.
Ther Adv Urol 2025, Vol. 17: 1–17 - This systematic assessment evaluated the diagnostic performance of imaging-based radiomics in distinguishing benign from malignant tumors and functional from non-functional adrenal masses. Despite current limitations—including small cohort sizes, lack of prospective validation, and insufficient standardization—the potential of AI to augment diagnostic workflows is evident. Future studies, driven by advances in AI, radiomics, and collaborative research, are essential to validate these tools, ensure clinical applicability, and ultimately improve patient outcomes in the management of adrenal tumors.
Artificial intelligence and radiomics applications in adrenal lesions: a systematic review
Matteo Ferro , Octavian Sabin Tataru , Giuseppe Carrieri et al.
Ther Adv Urol 2025, Vol. 17: 1–17
Deep Learning
- Artificial intelligence (AI) holds significant potential to enhance various aspects of oncology, spanning the cancer care continuum. This review provides an overview of current and emerging AI applications, from risk assessment and early detection to treatment and supportive care. AI-driven tools are being developed to integrate diverse data sources, including multi-omics and electronic health records, to improve cancer risk stratification and personalize prevention strategies. In screening and diagnosis, AI algorithms show promise in augmenting the accuracy and efficiency of medical image analysis and histopathology interpretation. AI also offers opportunities to refine treatment planning, optimize radiation therapy, and personalize systemic therapy selection. Furthermore, AI is explored for its potential to improve survivorship care by tailoring interventions and to enhance end-of-life care through improved symptom management and prognostic modeling.
Artificial intelligence across the cancer care continuum.
Riaz IB, Khan MA, Osterman TJ.
Cancer. 2025 Aug 15;131(16):e70050. - Beyond care delivery, AI augments clinical workflows, streamlines the dissemination of up-to-date evidence, and captures critical patient-reported outcomes for clinical decision support and outcomes assessment. However, the successful integration of AI into clinical practice requires addressing key challenges, including rigorous validation of algorithms, ensuring data privacy and security, and mitigating potential biases. Effective implementation necessitates interdisciplinary collaboration and comprehensive education for health care professionals. The synergistic interaction between AI and clinical expertise is crucial for realizing the potential of AI to contribute to personalized and effective cancer care.
Artificial intelligence across the cancer care continuum.
Riaz IB, Khan MA, Osterman TJ.
Cancer. 2025 Aug 15;131(16):e70050. - Beyond imaging-based and tissue-based diagnostics, AI is playing an increasingly important role in molecular diagnostics by complementing these traditional methods with genomic and molecular insights, enabling a more comprehensive approach to cancer detection and treatment planning. AI from histopathology slides can assess tumor microenvironment and identify genetic mutations driving cancer growth and predict responses to targeted therapies or immunotherapy. Deep-learning approaches have been used to analyze tumor heterogeneity, predicting tumor evolution and resistance mechanisms and identifying prognostic biomarkers
Artificial intelligence across the cancer care continuum.
Riaz IB, Khan MA, Osterman TJ.
Cancer. 2025 Aug 15;131(16):e70050. - Although AI is improving cancer screening and early diagnosis, its success depends on collaboration between AI systems and medical professionals. AI enhances efficiency by reducing workload and expediting image analysis, yet expert oversight remains essential to ensure accuracy, interpret complex cases, and provide clinical context. Radiologists and pathologists play a crucial role in integrating AI findings into practice, ensuring that these technologies enhance—not replace—expert clinical judgment. AI tools enable radiologists to work more efficiently, focusing on complex cases and improving overall patient care while reducing turnaround time for diagnostic interpretations.
Artificial intelligence across the cancer care continuum.
Riaz IB, Khan MA, Osterman TJ.
Cancer. 2025 Aug 15;131(16):e70050. - State-of-the-art LLMs can now accept multimodal input, including live speech, and generate structured documentation in real time. This advance underpins digital scribes that capture the entire encounter and draft notes autonomously. Controlled and observational studies indicate that ambient documentation both shortens charting time and lowers cognitive burden. Microsoft's Nuance DAX Copilot, an Epic-embedded tool, has reduced time-in-notes by 1 minute per visit, halved scores on the National Aeronautics and Space Administration Task Load Index, and signaled a reduction in clinician burnout. Vendor surveys suggest that 70% of clinicians report better work–life balance and clinics regain 13–26 extra appointment slots per provider per month when documentation writes itself.
Artificial intelligence across the cancer care continuum.
Riaz IB, Khan MA, Osterman TJ.
Cancer. 2025 Aug 15;131(16):e70050. - By using ABRIDGE, another ambient clinical documentation tool, 81% of clinicians reported easier documentation compared with the current workflows according to vendor surveys. A multispecialty trial at the University of Kansas Medical Center indicated higher professional satisfaction and lower cognitive load for nearly 100 clinicians already using legacy speech-recognition tools. Leading cancer institutes are now deploying ABRIDGE across hematology and medical oncology services after pilots confirmed accurate handling of complex terminology and multilingual conversations. Beyond easing clinician workload, ambient systems automatically produce lay-language after-visit summaries, reinforcing education and shared decision making for patients navigating intricate oncology care plans.
Artificial intelligence across the cancer care continuum.
Riaz IB, Khan MA, Osterman TJ.
Cancer. 2025 Aug 15;131(16):e70050. - AI is rapidly transforming oncology, offering unprecedented opportunities to improve cancer care across the entire disease spectrum—from prevention and early detection to treatment, survivorship, and end-of-life care AI-powered tools enhance cancer risk assessment, optimize screening programs, refine diagnostic precision, and personalize treatment strategies, ultimately improving patient outcomes. Moreover, AI facilitates care delivery, streamlines evidence generation and syntheses, and optimizes the recording of PROs. In addition, AI-driven advancements in fundamental biology, such as protein structure prediction and cancer genomics, are enhancing our understanding of the disease. At the same time, applications in robotic surgery, radiation therapy planning, drug discovery, and patient support are well poised to improve patient care and treatment outcomes.
Artificial intelligence across the cancer care continuum.
Riaz IB, Khan MA, Osterman TJ.
Cancer. 2025 Aug 15;131(16):e70050. - Multidisciplinary collaboration among clinicians, researchers, data scientists, and technology developers is vital to refining AI models, ensuring interpretability, and expanding AI applications in oncology. As AI continues to evolve and access to high-quality data improves, its role in cancer care will become even more effective. The future of oncology is increasingly intertwined with AI. By embracing this technology responsibly, educating health care professionals, and fostering human–AI collaboration, we can usher in a new era of personalized, precise, and effective cancer care—ultimately improving outcomes and quality of life for all patients.
Artificial intelligence across the cancer care continuum.
Riaz IB, Khan MA, Osterman TJ.
Cancer. 2025 Aug 15;131(16):e70050.
- From typists to truckers, people have long worried whether automation will complement or disrupt their work. This debate divides radiology into two camps. The augmentation camp believes AI will handle routine tasks and free up doctors to focus on complex interpretations, interventions, and ‘soft skills’. The replacement camp believes that AI will soon interpret diagnostic imaging to an above-human standard and make many radiologists redundant. The camps can coexist: AI may boost some radiologists and displace others. Yet, most commentators overlook an uncomfortable question: as AI becomes more capable, what happens to the value of radiologists’ work? In other words, cui bono – who benefits from the productivity gains?
Perspective: AI Productivity Will Not Benefit Employed Radiologists
Ruthven, Heathcote Agten, Christoph
Europ J of Radiology AI 3(2025) 1000033 - Yet for AI firms and investors, radiology remains too good an opportunity to ignore. It offers what they value most: a large market with high-quality datasets. As such, radiology is by far the top target for medical AI. By December 2024, 76 % of all AI-enabled medical applications cleared by the FDA target radiology. Meanwhile, ageing populations, rising chronic disease, and cheaper imaging have driven up imaging volumes. Too few radiologists exist to meet demand: the UK expects a 40 % shortage of consultants by 2028, and the US a gap of 122,000 by 2032. In 2025, Hinton appeared to repent, telling The New York Times he spoke “too broadly” and was referring only to image analysis. He now says AI will make radiologists more efficient and accurate – a measured position leaving him room to be right either way. Again, this sidesteps the question: what will these changes mean for radiologists’ careers?
- Many radiologists assume workforce shortages will protect them from automation. But history suggests the opposite: automation is most profitable when labour is scarce and expensive. High radiologist salaries increase the pressure to automate. Once adopted, automation tends to reduce labour’s share of the value it creates. As economists Acemoglu and Restrepo argue, automation “increases the size of the pie, but labour gets a smaller slice.” This displacement effect, where capital substitutes for human tasks, is why productivity gains come at labour’s expense. For instance, in Bessen’s study of the US textile industry he charted how a weaver in 1900 could produce 50 times more cloth than a one in 1800. Rising productivity made cloth cheaper and demand for it soared, as consumers discovered the joy of owning more than one outfit. This created four times more weaving jobs. However, people have a finite desire for cloth. Demand at some point can no longer keep up with productivity, and a tipping point arrives. After 1920, output per worker kept rising by about 3 % a year, but demand for cloth stagnated and employers cut jobs). Bessen’s inverted U-curve charts this boom-and-bust cycle for labour: on the way up, lower costs open markets and create jobs. On the way down, machines replace labour, and the job market shrinks.
- “Could radiology be approaching its own downward slope? Past innovations like CT, PACS, and voice recognition boosted productivity, yet never enough to exceed demand. Today, AI systems increasingly perform at or above radiologist level. Consider three examples from the past year: in breast cancer screening, a South Korean trial shows that AI-assisted readers detect 13.8 % more cancers than radiologists working alone. In MSK radiographs, a Finnish emergency-department study finds that two AI algorithms match expert MSK radiologists at 89 % accuracy. In chest X-ray reporting, a DeepMind study shows that 75 % of radiologists judge AI-generated reports preferable or equivalent to expert-written ones.”
Perspective: AI Productivity Will Not Benefit Employed Radiologists
Ruthven, Heathcote Agten, Christoph
Europ J of Radiology AI 3(2025) 1000033 - Labour is scarce today, but if AI tools can increase productivity by orders of magnitude, practices will employ fewer radiologists. As AI capabilities grow, radiologists will shift from reading to reviewing, from interpreting to confirming. Tasks such as biopsies and patient consultations will likely remain in human hands. Radiology will continue to exist, but the nature and value of the work will change. For some, this brings opportunities. For others, a loss of autonomy, status, or income.
- Radiologists cannot control the pace of AI, but they can prepare a clear ‘Plan B′. Some may seek equity in a practice, move into education or industry, or shift toward procedures and subspecialties that automation is less likely to affect. Younger radiologists should think not only about how to adapt, but how to build additional income streams. Those later in their careers may focus on securing roles that are harder to replace or on reducing clinical time on their own terms. Langlotz’s idea – that radiologists who use AI will replace those who do not – is partly true. But for employed radiologists, the more likely outcome is that their profession will be less in demand and less well paid. Those who remain in the field will do different work, with no guarantee that employers will value, reward, or respect it as they once did.
Perspective: AI Productivity Will Not Benefit Employed Radiologists
Ruthven, Heathcote Agten, Christoph
Europ J of Radiology AI 3(2025) 1000033 - “Employers, private equity firms, and AI vendors will capture most of the profit from AI-driven productivity. Employed radiologists are unlikely to receive these gains. Without structural change in how value is shared, increased productivity will come at the expense of those who still work.”
Perspective: AI Productivity Will Not Benefit Employed Radiologists
Ruthven, Heathcote Agten, Christoph
Europ J of Radiology AI 3(2025) 1000033
- “In radiology, the prevailing view has long favored assistive artificial intelligence (AI) approaches, where human radiologists work 'with' AI systems, under the belief that merging machine precision with human judgment naturally leads to improved diagnostic outcomes. However, recent evidence challenges this assumption by demonstrating that integrating AI into radiologists’ workflows does not always yield the anticipated enhancements. This emerging perspective suggests that a clearly defined division of labor—where AI and radiologists assume separate responsibilities in the diagnostic process—might provide more reliable results.”
Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows
Pranav Rajpurkar, PhD • Eric J. Topol, MD
Radiology 2025; 316(1):e250477 - In the assistive AI model, AI systems provide their analysis First, followed by radiologist review and independent interpretation. The AI outputs—typically highlighting potential findings or providing quantitative measurements—are made available to radiologists as they conduct their own evaluation. This approach assumes that having access to AI insights will help radiologists catch potential oversights and make more informed decisions. while still maintaining their autonomy in the final interpretation. However, practical implementations of the assistive model have revealed notable challenges. Agarwal et al demonstrated that when discrepancies arose between AI assessment and radiologist interpretation of chest radiographs, radiologists tended to discount the AI output—even when the algorithm was correct. This automation neglect is only part of the story, as radiologists may have valid reasons for disregarding AI suggestions, particularly when AI systems occasionally produce clinically implausible results.
Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows
Pranav Rajpurkar, PhD • Eric J. Topol, MD
Radiology 2025; 316(1):e250477 - Conversely, radiologists can also exhibit automation bias— the tendency to rely too much on AI suggestions even when they are incorrect. In mammography interpretation, Dratsch et al found that even experienced radiologists saw their diagnostic accuracy drop substantially (from 82.3% to 45.5%) when given incorrect AI predictions. This highlights that the challenges of human-AI collaboration extend beyond automation, neglecting to include potentially dangerous overreliance on AI systems.
Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows
Pranav Rajpurkar, PhD • Eric J. Topol, MD
Radiology 2025; 316(1):e250477 - “We propose three distinct models of role separation. In the AI-first sequential model, AI undertakes an initial portion of the workflow, handling parts of the process that can be effectively automated. Once the AI completes its portion, the radiologist takes over for expert interpretation. In the doctor-first sequential model, the radiologist initiates the diagnostic process using their clinical expertise, while the AI performs a distinct, complementary task that enhances the overall workflow. In the case allocation model, the responsibility for handling a case is determined by its characteristics. Depending on the complexity and clarity of a given case, it may be managed entirely by AI, entirely by the radiologist, or by a combination of both.”
Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows
Pranav Rajpurkar, PhD • Eric J. Topol, MD
Radiology 2025; 316(1):e250477 - One compelling application of the AI-first sequential model involves using AI to analyze electronic health records to prepare relevant clinical context before radiologist interpretation. In this workflow, AI systems review prior reports, laboratory results, and clinical notes to compile a focused summary of the patient’s medical history and current clinical questions relevant to the imaging study. Bhayana et al (4) evaluated the ability of GPT-4 (OpenAI) to automatically generate clinical histories for CT requisitions from clinical notes at a cancer center. The results were encouraging: Histories generated by the large language model included more critical parameters than physician-provided requisition histories, such as primary oncologic diagnosis (99.5% vs 89%), acute symptoms (15% vs 4%), and relevant surgical history (61% vs 12%). Radiologists generally preferred the AI-generated histories for image interpretation (89% vs 5%).
Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows
Pranav Rajpurkar, PhD • Eric J. Topol, MD
Radiology 2025; 316(1):e250477 - The doctor-first sequential model maintains radiologists’ traditional role in primary image interpretation and diagnosis, while AI systems are deployed to enhance and extend the impact of their expertise. This model acknowledges that certain aspects of radiologic work—particularly those requiring complex pattern recognition, clinical judgment, and integration of contextual factors—remain best suited to human expertise. Several promising applications of this model have emerged. For structured reporting, AI tools can transform a radiologist’s free-text findings into standardized reports that conform to reporting guidelines. For clinical decision support, AI systems can analyze a radiologist’s findings in conjunction with clinical guidelines to suggest appropriate follow-up recommendations.
Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows
Pranav Rajpurkar, PhD • Eric J. Topol, MD
Radiology 2025; 316(1):e250477 - The case allocation model offers perhaps the most pragmatic approach to role separation in radiology, routing cases based on specific characteristics to optimize the use of both AI and human expertise. Three distinct pathways have emerged: using AI to rule out normal cases, risk-based reader allocation, and dynamic complexity-based allocation.
Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows
Pranav Rajpurkar, PhD • Eric J. Topol, MD
Radiology 2025; 316(1):e250477 - “This approach involves dynamically allocating cases based on case complexity and AI uncertainty levels. Agarwal et al (1) found that while access to AI predictions improved radiologist performance for cases where the AI predictions were very close to 0 or 1 (indicating high confidence in either direction), the performance of the AI system itself was even better than the AI-assisted radiologists in these ranges. The PRAIM study (10) found that radiologists naturally gravitated toward efficient role separation when given flexibility in workflow design. They tended to use AI-supported viewing for cases the AI system tagged as “normal,” while preferring traditional viewing for more complex cases. This natural separation emerged without explicit guidance, suggesting that radiologists intuitively recognize when to leverage AI’s strengths versus maintain direct control.”
Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows
Pranav Rajpurkar, PhD • Eric J. Topol, MD
Radiology 2025; 316(1):e250477 - “The radiology community faces difficult decisions about how to proceed. Current evidence suggests that neither fully integrated assistive approaches nor complete automation represent optimal solutions. Instead, a careful, measured approach to role separation—guided by rigorous clinical validation and real-world evidence—offers the most pragmatic path forward. Successful implementation will likely require flexibility to accommodate different practice patterns, radiologist preferences, and institutional contexts, recognizing that the most effective workflows may blend elements from multiple models rather than adhering rigidly to any single approach.”
Beyond Assistance: The Case for Role Separation in AI-Human Radiology Workflows
Pranav Rajpurkar, PhD • Eric J. Topol, MD
Radiology 2025; 316(1):e250477
- Background: Adrenal lesions, often incidentally detected, present diagnostic challenges in distinguishing benign from malignant or hormonally active lesions. Conventional imaging(computed tomography/magnetic resonance imaging (CT/MRI)) has limitations, driving interest in artificial intelligence (AI) and radiomics for enhanced accuracy.
Objectives: To systematically evaluate AI and radiomics applications in adrenal lesion characterization, focusing on diagnostic performance, methodologies, and clinical utility.
Conclusion: CT-based radiomics outperformed MRI, aligning with guidelines favoring CT for adrenal assessment. AI-enhanced models show promise in refining diagnostics and reducing invasive procedures. However, retrospective designs, small cohorts, and protocol variability limit generalizability. Future work requires multicenter collaboration, standardized protocols, and prospective validation to translate AI/radiomics into clinical practice. - Conclusion: CT-based radiomics outperformed MRI, aligning with guidelines favoring CT for adrenal assessment. AI-enhanced models show promise in refining diagnostics and reducing invasive procedures. However, retrospective designs, small cohorts, and protocol variability limit generalizability. Future work requires multicenter collaboration, standardized protocols, and prospective validation to translate AI/radiomics into clinical practice .
Artificial intelligence and radiomics applications in adrenal lesions: a systematic review
Matteo Ferro , Octavian Sabin Tataru , Giuseppe Carrieri et al.
Ther Adv Urol 2025, Vol. 17: 1–17
Artificial intelligence and radiomics applications in adrenal lesions: a systematic review
Matteo Ferro , Octavian Sabin Tataru , Giuseppe Carrieri et al.
Ther Adv Urol 2025, Vol. 17: 1–17- Given the limitations of current imaging modalities in accurately characterizing adrenal lesions, the integration of artificial intelligence and radiomics presents a significant opportunity to improve diagnostic precision. In this review, CT-based radiomics achieved a mean AUC of 0.88, outperforming MRI-based radiomics (mean AUC: 0.82), thus confirming CT as the preferred modality for adrenal lesion characterization.
Artificial intelligence and radiomics applications in adrenal lesions: a systematic review
Matteo Ferro , Octavian Sabin Tataru , Giuseppe Carrieri et al.
Ther Adv Urol 2025, Vol. 17: 1–17 - This systematic assessment evaluated the diagnostic performance of imaging-based radiomics in distinguishing benign from malignant tumors and functional from non-functional adrenal masses. Despite current limitations—including small cohort sizes, lack of prospective validation, and insufficient standardization—the potential of AI to augment diagnostic workflows is evident. Future studies, driven by advances in AI, radiomics, and collaborative research, are essential to validate these tools, ensure clinical applicability, and ultimately improve patient outcomes in the management of adrenal tumors.
Artificial intelligence and radiomics applications in adrenal lesions: a systematic review
Matteo Ferro , Octavian Sabin Tataru , Giuseppe Carrieri et al.
Ther Adv Urol 2025, Vol. 17: 1–17
- “The promise of radiomics is compelling: a data-driven approach capable of identifying microstructural changes on imaging that is often imperceptible to the human eye. Multiple proof-of-concept studies show that radiomics-based machine learning (ML) models can distinguish PDAC from normal pancreatic tissue with high accuracy. Even more Provocative findings suggesting that radiomic changes can be detected on pre-diagnostic CT scans months—even years before clinical diagnosis. These results suggest the possibility of a true lead-time advantage, potentially enabling earlier intervention and better prognosis.”
Radiomics for Early Pancreatic Cancer Detection: From Promise to Practice?
Dias AB.
Can Assoc Radiol J. 2025 Aug 6:8465371251359867. - “First, the reproducibility of radiomic models remains a key hurdle. Radiomics features are highly sensitive to image acquisition parameters, scanner types, reconstruction algorithms, and preprocessing techniques. While harmonization efforts and standardization initiatives (such as the Image Biomarker Standardization Initiative) are underway, variability across institutions continues to impede the development of generalizable models. This is particularly problematic for PDAC, where tumor margins are often indistinct and the pancreas is an anatomically challenging organ to segment— automated methods for tumor segmentation are still in their infancy and often underperform.”
Radiomics for Early Pancreatic Cancer Detection: From Promise to Practice?
Dias AB.
Can Assoc Radiol J. 2025 Aug 6:8465371251359867. - ”Second, the translation of these promising models into robust clinical tools demand large, diverse, and well-curated datasets. Yet, most existing studies are retrospective, single-center, and use relatively small sample sizes. The review highlights that overfitting and limited external validation are common. Indeed, in a radiomics quality score analysis across 54 pancreatic imaging studies, the mean score was only 32.1%, reflecting poor methodological robustness and limited clinical readiness.”
Radiomics for Early Pancreatic Cancer Detection: From Promise to Practice?
Dias AB.
Can Assoc Radiol J. 2025 Aug 6:8465371251359867. - ” Third, even assuming technical hurdles can be overcome, questions remain about how radiomics would fit into existing clinical workflows. Can radiomics reliably guide downstream decisions such as endoscopic ultrasound or biopsy? What is the appropriate threshold for action when radiomics detects abnormalities that radiologists cannot? With a low disease prevalence in the general population and the potential for false positives, widespread screening using radiomics could introduce harm through unnecessary investigations and anxiety. In this sense, radiomics may be most impactful when deployed in high-risk cohorts—such as individuals with familial predisposition or germline mutations—where the pretest probability of PDAC is higher.
Radiomics for Early Pancreatic Cancer Detection: From Promise to Practice?
Dias AB.
Can Assoc Radiol J. 2025 Aug 6:8465371251359867. - In summary, this review maps both the achievements and the road ahead for radiomics in pancreatic cancer. The technology is mature enough to show real promise, but not yet validated or standardized enough for clinical deployment. Future efforts must focus on improving reproducibility, developing robust and interpretable models, and defining their role in clinical decision-making—ideally within prospective trials targeting high-risk groups. Only then can we begin integrating radiomics into the workflows that have the potential to change the trajectory of this challenging disease.
Radiomics for Early Pancreatic Cancer Detection: From Promise to Practice?
Dias AB.
Can Assoc Radiol J. 2025 Aug 6:8465371251359867.
Kidney
- In 2017, the global incidence of sepsis was estimated to be 48.9 million cases with 11 million sepsis-related deaths (accounting for nearly 20% of all global deaths) . Within the United States, according to the Centers for Disease Control and Prevention, the incidence of sepsis is >1.7 million adults per year. Greater than 15% of Americans diagnosed with sepsis die as a result of sepsis each year, and the in-hospital mortality is >30%, exemplifying that prompt recognition and treatment is crucial. Furthermore, sepsis was shown to account for 5.2% of total United States hospital costs (>20 billion dollars) in 2011, and the incidence is only rising because of an aging population . Risk factors for the development of sepsis overlap with risk factors for infection and include immune compromise, chronic diseases such as malignancy, certain patient demographics(infants and elderly persons, males, Black race), as well as numerous unidentified causes .
ACR Appropriateness Criteria® Sepsis
Brixey, Anupama G. et al.
Journal of the American College of Radiology, Volume 21, Issue 6, S292 - S309 - Pohlan et al performed a retrospective study of 357 ED patients with suspected sepsis, of whom 132 underwent CT scan within 72 hours of admission. The second and third most commonly identified septic foci were in the abdomen, 22.0% (28/127 patients), and pelvis/genitourinary tract 20.5% (26/127 patients). A PPV of 81.82% (CI, 76.31%-86.28%) was calculated for septic foci identified by CT. However, the NPV was only 21.74% (CI, 10.73%- 39.11%). Patients with suspected sepsis who received a CT within 72 hours of admission were given a final diagnosis of sepsis in 93.3% of cases (124/132). The detection of septic foci in 76.5% of CTs results in a high diagnostic yield for CT in septic ED patients, particularly in patients who are extremely ill and/or require ICU admission.
ACR Appropriateness Criteria® Sepsis
Brixey, Anupama G. et al.
Journal of the American College of Radiology, Volume 21, Issue 6, S292 - S309 - Just et al performed a single-center 1 year retrospective study of all CT scans of the chest and/or abdomen ordered in pursuit of suspected infection in surgical ICU patients. A source of infection was found in 76/144 of cases (52.8%) and resulted in a change of management in 65/144 (45%) of patients, including a change in antimicrobial regimen, surgery, and nonsurgical interventions such as placement of drainage catheters. A pathologic infectious source was found in up to 44% of patients who underwent abdominal CT (exact breakdown not provided). Use of IV contrast was not specified in this study. Furthermore, preceding diagnostic procedures such as abdominal radiography were not recorded.
ACR Appropriateness Criteria® Sepsis
Brixey, Anupama G. et al.
Journal of the American College of Radiology, Volume 21, Issue 6, S292 - S309
- Angiomyolipoma (AML) is a benign tumor comprised of a mixture of vessels (“angio”), smooth muscle (“myo”), and adipose tissue (“lipo”). It belongs to a group of unusual mesenchymal tumors with myogenic and melanocytic differentiation known as perivascular epithelioid cell tumors. AMLs are commonly sporadic tumors but may be associated with tuberous sclerosis complex (TSC) and/or lymphangioleiomyomatosis (LAM). The imaging appearance of AMLs strongly correlates with the pathologic findings. Fat is detectable in the vast majority of AMLs, and these tumors are referred to as classic AMLs. Fat-poor AMLs are smooth muscle–predominant tumors.
Spectrum of Renal Angiomyolipoma with Radiologic-Pathologic Correlation.
Lubner MG, Marko J, Taffel MT, et al.
Radiographics. 2025 Jul;45(7):e240159. - Most AMLs exhibit benign clinical behavior. The most important clinical complication of AML is tumor hemorrhage, which may lead to retroperitoneal hemorrhage and shock. Hemorrhage most commonly occurs in large tumors or tumors with aneurysms equal to or larger than 5 mm. Benign AMLs may also invade the renal vein and inferior vena cava. EAMLs may behave aggressively with local recurrence and metastatic spread. Treatment options for AML vary and may include observation for small classic AMLs; embolization, ablation, and/or surgical resection of large or potentially aggressive lesions; or systemic therapy in cases associated with TSC or LAM.
Spectrum of Renal Angiomyolipoma with Radiologic-Pathologic Correlation.
Lubner MG, Marko J, Taffel MT, et al.
Radiographics. 2025 Jul;45(7):e240159. - AML is a benign tumor comprised of a mixture of vessels (“angio”), smooth muscle (“myo”), and adipose tissue (“lipo”). It belongs to a group of unusual mesenchymal tumors with myogenic and melanocytic differentiation known as PEC tumors. The most important clinical complication is tumoral hemorrhage, which may lead to tumor rupture and retroperitoneal hemorrhage, also known as Wunderlich syndrome. The detection of macroscopic fat within a renal mass is essential for making the radiologic diagnosis of classic AML. While AML can also contain microscopic fat, a renal mass with only microscopic fat and not macroscopic fat is concerning for a possible RCC, most frequently the clear cell subtype.
- AMLs are very common in patients with TSC and LAM, which is a rare systemic lung disease that may be sporadic or associated with TSC. In contrast to sporadic tumors, AMLs that arise in association with TSC, with or without LAM, are frequently multifocal and bilateral, arise in younger patients, and are larger. In addition, they are more likely to have an epithelioid component, epithelial cysts, and/or microscopic AML lesions (“tumorlets”) that manifest in the grossly uninvolved renal parenchyma . Patients with TSC are also at an increased risk of developing RCC, including a subset with prominent epithelioid morphologic features and features that overlap with those of EAML.
Spectrum of Renal Angiomyolipoma with Radiologic-Pathologic Correlation.
Lubner MG, Marko J, Taffel MT, et al.
Radiographics. 2025 Jul;45(7):e240159.
- “Renal involvement in pathologic specimens is quite common. However, renal function compromise is rare, usually manifesting as nephrotic syndrome. Focal lesions are rare and may calcify, mimicking a caliceal calculus. At US, amyloidosis is one of the rare causes of increased echogenicity and enlarged kidneys. Progression to end-stage renal disease is also rare.”
Amyloidosis: review and CT manifestations.
Georgiades CS, Neyman EG, Barish MA, Fishman EK.
Radiographics. 2004 Mar-Apr;24(2):405-16. - Primary (AL) and secondary (AA) amyloidosis account for the overwhelming majority of cases. The former has been associated with a monoclonal plasma cell dyscrasia, as at least 30% of primary amyloidosis patients will eventually progress to multiple myeloma. The median survival is 1.5 years . Secondary amyloidosis is a result of chronic inflammatory disease (Crohn disease, adult or juvenile rheumatoid arthritis, Reiter syndrome, ankylosing spondylitis, familial Mediterranean fever, Sjögren syndrome, dermatomyositis, vasculitis, chronic osteomyelitis, tuberculosis, bronchiectasis, cystic fibrosis, systemic lupus erythematosus, etc) and has a median survival of 4.5 years. The incidence of amyloidosis (particularly secondary amyloidosis) has been gradually increasing, presumably due to the longer life expectancy of patients with chronic diseases.
Amyloidosis: review and CT manifestations.
Georgiades CS, Neyman EG, Barish MA, Fishman EK.
Radiographics. 2004 Mar-Apr;24(2):405-16. - More than 35 amyloid precursor proteins have been identified and many have tropism for the kidney. Renal amyloidosis is most commonly seen in AL and AA amyloidosis and the main clinical manifestations are proteinuria and progressive renal dysfunction. On renal pathology, hallmark findings of amyloidosis include Congo red positivity with apple-green birefringence and randomly arranged fibrils measuring 7-12 nm in diameter on ultrastructural examination. Management of renal amyloidosis typically combines therapy targeting the underlying amyloid process and supportive management. Patients with renal amyloidosis who progress to end-stage renal disease can be treated with dialysis, and in selected patients, with renal transplantation.
Renal Amyloidosis: Presentation, Diagnosis, and Management
Gurung, Reena et al.
The American Journal of Medicine, Volume 135, S38 - S43 - “The kidney is the organ most frequently involved in systemic amyloidosis. Renal amyloidosis is characterized by acellular pathologic Congo red-positive deposition of amyloid fibrils in glomeruli, vessels, and/or interstitium. This disease manifests with heavy proteinuria, nephrotic syndrome, and progression to end-stage kidney failure. In some situations, it is not possible to identify the amyloid subtype using immunodetection methods, so the diagnosis remains indeterminate. In cases where hereditary amyloidosis is suspected or cannot be excluded, genetic testing should be considered. ”
Renal amyloidosis: a new time for a complete diagnosis.
Feitosa VA, Neves PDMM, Jorge LB, et al.
Braz J Med Biol Res. 2022 Oct 3;55:e12284.
Liver
- Lymphomatous involvement of the liver may manifest at imaging as a discrete focal liver mass or masses, diffuse infiltrating disease, or an ill-defined mass in the porta hepatis. The most common imaging manifestation of PHL is a solitary discrete lesion, which is seen in about 60% of cases. Multiple lesions are seen in 35%–40% of patients, although one lesion is likely to be dominant . Diffuse infiltration is uncommon in PHL and indicates a poor prognosis. In contrast, multifocal lesions or diffuse infiltration is the most common pattern of secondary hepatic lymphoma (90%).
Hematologic malignancies of the liver: spectrum of disease.
Tomasian A, Sandrasegaran K, Elsayes KM, et al.
Radiographics. 2015 Jan-Feb;35(1):71-86. - Numerous small discrete nodules (in a miliary pattern) are distributed throughout the liver in about 10% of cases of Hodgkin disease and secondary non-Hodgkin lymphoma of the liver. Another point of distinction is that dominant liver masses are not typically seen in secondary lymphoma but are characteristic of PHL. In addition, untreated nodules in secondary hepatic lymphoma are usually homogeneous, even when large , while the dominant masses in PHL are typically heterogeneously enhancing. By definition, splenic lesions are not seen in patients with PHL but are seen in 30%–40% of patients with secondary non-Hodgkin lymphoma.”
Hematologic malignancies of the liver: spectrum of disease.
Tomasian A, Sandrasegaran K, Elsayes KM, et al.
Radiographics. 2015 Jan-Feb;35(1):71-86. - “At CT, lymphomatous nodules commonly have soft-tissue attenuation but enhance to a lesser degree than the liver parenchyma on arterial, portal venous, and delayed phase images. The lesions may demonstrate hemorrhage, necrosis, or a rim-enhancement pattern. Calcification is rare in the absence of treatment. A multiphase CT study is not indicated for diagnosis of hepatic lymphoma because the lesions typically are hypovascular in all phases.”
Hematologic malignancies of the liver: spectrum of disease.
Tomasian A, Sandrasegaran K, Elsayes KM, et al.
Radiographics. 2015 Jan-Feb;35(1):71-86.
- “Hepatic sclerosing hemangioma, a very rare benign tumor, is characterized by fibrosis and hyalinization occurring in association with degeneration of a hepatic cavernous hemangioma. Such atypical hemangiomas can be diagnosed incorrectly as primary or metastatic malignancies based on imaging characteristics.”
Multiple hepatic sclerosing hemangiomas: a case report and review of the literature.
Yugawa, K., Yoshizumi, T., Harada, N. et al.
Surg Case Rep 4, 60 (2018). https://doi.org/10.1186/s40792-018-0468-6 - Hemangiomas are the commonest benign hepatic tumors, being found in up to 7% of autopsies in one series. Hemangiomas have a predilection for women in a ratio of 5:1. They are characteristically discovered incidentally during abdominal imaging in individuals aged 40 to 50 years. Hepatic sclerosing hemangioma, first reported by Shepherd et al. in 1983 , is a rare type of hepatic hemangioma composed of abundant acellular hyalinized tissue in which small vessels are occasionally seen. Another study reported finding them in only two of 1000 autopsies. Hepatic sclerosing hemangiomas are caused by degenerative changes such as thrombus formation, necrosis, and scar formation in hepatic cavernous hemangiomas; however, the mechanism(s) for these degenerative changes has not yet been determined .
Multiple hepatic sclerosing hemangiomas: a case report and review of the literature.
Yugawa, K., Yoshizumi, T., Harada, N. et al.
Surg Case Rep 4, 60 (2018). https://doi.org/10.1186/s40792-018-0468-6
- Biliary Cystadenoma: Facts
Mucinous cystic neoplasms of the liver and biliary system, also known as biliary cystadenomas, are uncommon benign cystic neoplasms.
Biliary cystadenomas are cystic neoplasms that may be either unilocular or multilocular. They are only rarely found in the extrahepatic biliary tree and gallbladder. - Biliary Cystadenoma: Facts
Biliary cystadenomas range in size from 3 to 40 cm and can be either unilocular or multilocular. Unfortunately, there are no specific imaging features that permit reliable differentiation of biliary cystadenoma from biliary cystadenocarcinoma.
Calcifications of septa or cyst wall may be seen. Additionally, the septa may enhance following administration of contrast. - “Biliary cystic neoplasms predominantly affect middle-aged women (30–50 years)and are well known to appear as well-encapsulated multilocular cystic masses with visible internal septation, a solid mural nodule, and possibly enhancing cystic walls on CT. Simple hepatic cysts, on the other hand, are usually known to be homogeneously hypoattenuating round or ovoid cystic lesions with an imperceptible wall .”
Differentiation Between Biliary Cystic Neoplasms and Simple Cysts of the Liver: Accuracy of CT
Kim JY, Kim SH, Eun HW et al.
Ajr 2020;195;1142-1148 - Biliary Cystadenoma: Facts
Biliary cystadenoma (BCA) represents a rare benign cystic hepatic neoplasm that has premalignant potential. The tumor originates in the bile ducts and is lined by mucin-secreting columnar or cuboidal epithelium. Biliary cystadenoma can appear as a unilocular or multilocular cystic intrahepatic mass. The malignant counterpart is biliary cystadenocarcinoma (BCAC), which is believed to arise from the premalignant form. - “Upstream bile duct dilatation, lesion location at the left hepatic lobe, fewer than three coexistent cysts, and THAD were found to be highly suggestive CT findings for the differentiation of biliary cystic neoplasms from simple hepatic cysts. Radiologists’ performance was significantly improved with the knowledge of these highly suggestive CT criteria.”
Differentiation Between Biliary Cystic Neoplasms and Simple Cysts of the Liver: Accuracy of CT
Kim JY, Kim SH, Eun HW et al.
Ajr 2020;195;1142-1148 - “Our study results show that four CT findings—that is, the combined findings of upstream bile duct dilatation, coexistence of fewer than three other cysts, the presence of perilesional THAD, and lesion located at theleft hepatic lobe—were statistically significant predictors of biliary cystic neoplasm in the differentiation of biliary cystic neoplasms from simple hepatic cysts. In addition, radiologists’ performance, which was analyzed using the ROC method, was significantly improved with knowledge of these significant CT criteria.”
Differentiation Between Biliary Cystic Neoplasms and Simple Cysts of the Liver: Accuracy of CT
Kim JY, Kim SH, Eun HW et al.
Ajr 2020;195;1142-1148 - “The location of the lesion was also a significant CT feature for differentiation contrary to our expectation. In our study, the left hepatic lobe was a predominant site for biliary cystic neoplasms (9/12), whereas 76.9% (10/13) of simple hepatic cysts were located at the right lobe of the liver. This difference is statistically significant. Unfortunately, we cannot confidently answer why biliary cystic neoplasms occurred more frequently in the left hepatic lobe and simple cysts occurred more frequently in the right lobe in our study.”
Differentiation Between Biliary Cystic Neoplasms and Simple Cysts of the Liver: Accuracy of CT
Kim JY, Kim SH, Eun HW et al.
Ajr 2020;195;1142-1148
Pancreas
- “The promise of radiomics is compelling: a data-driven approach capable of identifying microstructural changes on imaging that is often imperceptible to the human eye. Multiple proof-of-concept studies show that radiomics-based machine learning (ML) models can distinguish PDAC from normal pancreatic tissue with high accuracy. Even more Provocative findings suggesting that radiomic changes can be detected on pre-diagnostic CT scans months—even years before clinical diagnosis. These results suggest the possibility of a true lead-time advantage, potentially enabling earlier intervention and better prognosis.”
Radiomics for Early Pancreatic Cancer Detection: From Promise to Practice?
Dias AB.
Can Assoc Radiol J. 2025 Aug 6:8465371251359867. - “First, the reproducibility of radiomic models remains a key hurdle. Radiomics features are highly sensitive to image acquisition parameters, scanner types, reconstruction algorithms, and preprocessing techniques. While harmonization efforts and standardization initiatives (such as the Image Biomarker Standardization Initiative) are underway, variability across institutions continues to impede the development of generalizable models. This is particularly problematic for PDAC, where tumor margins are often indistinct and the pancreas is an anatomically challenging organ to segment— automated methods for tumor segmentation are still in their infancy and often underperform.”
Radiomics for Early Pancreatic Cancer Detection: From Promise to Practice?
Dias AB.
Can Assoc Radiol J. 2025 Aug 6:8465371251359867. - ”Second, the translation of these promising models into robust clinical tools demand large, diverse, and well-curated datasets. Yet, most existing studies are retrospective, single-center, and use relatively small sample sizes. The review highlights that overfitting and limited external validation are common. Indeed, in a radiomics quality score analysis across 54 pancreatic imaging studies, the mean score was only 32.1%, reflecting poor methodological robustness and limited clinical readiness.”
Radiomics for Early Pancreatic Cancer Detection: From Promise to Practice?
Dias AB.
Can Assoc Radiol J. 2025 Aug 6:8465371251359867.
Small Bowel
- “The term “hide-bound bowel” first appears in the radiologic literature in 1973 referring to luminal dilation and decreased distance between adjacent valvulae conniventes in scleroderma as seen on a fluoroscopic upper GI series , drawing analogy to the scleroderma hidebound changes present in the skin of the face and hands. The closely spaced valvulae conniventes, sometimes referred to as increased number of folds per inch, can also be readily identified on CT and MRI.”
Hidebound bowel sign.
Leshchinskiy, S., D’Agostino, R
Abdom Radiol 43, 2513–2516 (2018) - “Small bowel is the second most common site of gastrointestinal scleroderma involvement after the esophagus. Pathologically, scleroderma results in damage to the smooth muscles and myenteric plexus of small bowel leading to prolonged transit time and luminal dilation. Concurrently, there is collagen deposition and fibrosis predominantly involving the longitudinal layer of the muscularis propria and atrophy of the inner circular layer of the muscularis propria resulting in bowel contracture with stacking of the valvulae conniventes.”
- Hidebound bowel sign.
Leshchinskiy, S., D’Agostino, R
Abdom Radiol 43, 2513–2516 (2018) 
On computed tomographic enterography there was dilatation of the entire small bowel with narrow separation between valvulae conniventes. This radiographic finding is termed the hidebound bowel sign and is the radiographic representation of the smooth muscle atrophy and fibrosis that occurs as a result of foreshortening of small bowel in scleroderma.
- Mesenteric ischemia is an uncommon disease affecting the small and large bowel resulting from a reduction of intestinal blood flow. Although the disease is responsible for fewer than 1 in 1,000 hospital admissions, the mortality rate remains high, ranging between 30% to 90% in acute settings despite advances in treatment options. The etiology of ischemia may vary from arterial occlusion, venous thrombosis, or vasoconstriction. Higher prevalence in the elderly population and nonspecific clinical presentation leading to delayed diagnosis contribute to the high mortality rate. Most cases of mesenteric ischemia are due to an acute event leading to decreased blood supply to the splanchnic vasculature. Chronic mesenteric ischemia is uncommon, accounting for <5% of cases of mesenteric ischemia, and is almost always associated with diffuse atherosclerotic disease.
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340. - Acute mesenteric ischemia is most commonly secondary to acute embolism to the superior mesenteric artery (SMA), which accounts for approximately 40% to 50% of all episodes. Acute mesenteric artery thrombosis is the second most common cause of acute mesenteric ischemia (20%–30%) followed by nonocclusive mesenteric ischemia (25%) and, less commonly, mesenteric and portal venous thrombosis (5%–15%). In the chronic setting, mesenteric ischemia is almost always caused by severe atherosclerotic disease, with rare causes including fibromuscular dysplasia, median arcuate ligament syndrome, dissection, and vasculitis.
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340. - Acute embolization of the SMA involves the distal aspect of the vessel, usually beyond the origin of the middle colic artery, and commonly does not have associated collateral vessels. Acute mesenteric artery thrombosis is typically associated with chronic atherosclerotic disease and, given its more insidious course, a well-developed collateral circulation is commonly present. Nonocclusive mesenteric ischemia is seen in the setting of hypoperfusion because of secondary vasoconstriction of the mesenteric arteries. In these cases, there is no evidence of vascular occlusion, and the ischemia is distributed over a wider area of the bowel in a nonconsecutive manner. Mesenteric and portal venous thrombosis is the least common cause of acute mesenteric ischemia and may be idiopathic. Most common risk factors are hypercoagulable states, portal hypertension, and recent surgery. Bowel ischemia results from impaired intestinal mucosa venous outflow, leading to visceral edema and subsequent arterial hypoperfusion.
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340. - CTA of the abdomen and pelvis is a fast, accurate, and noninvasive diagnostic tool for evaluating the bowel and assessing intestinal vasculature and should be the first-step imaging approach in patients with acute bowel ischemia. CTA can be helpful in stratifying patients to identify those who would benefit from angiography as opposed to the ones who should undergo emergent surgery. Grading the degree of arterial stenosis with CTA has also been shown to be highly accurate compared to digital subtraction imaging (DSA) as well as other imaging modalities, including US and MRA . A negative or neutral oral contrast, such as low-density barium sulfate or water, has been advocated to distend the small bowel and better evaluate the bowel wall for thickening and enhancement; however this may not be possible in the acute setting . Both arterial and portal venous phases should be included as part of the protocol to assess both arterial and venous patency . Three-dimensional (3-D) rendering may also assist in evaluating the vasculature and should be performed .
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340. - Vascular CT findings include arterial stenosis, embolism, thrombosis, arterial dissection, and mesenteric vein thrombosis. Nonvascular CT findings include bowel-wall thickening, hypoperfusion and hypoattenuation, bowel dilatation, bowel-wall hemorrhage, mesenteric fat stranding, pneumatosis intestinalis, and portal venous gas. Quantitative methods of assessing bowel enhancement may also add value in identifying ischemic bowel . CTA is also preferred in patients with renal insufficiency with GFR under 30 who have suspected acute ischemia as benefits of a fast and accurate diagnosis will generally outweigh risks associated with potential risk of contrast-induced nephropathy. Overall, CTA is an accurate technique for acute mesenteric ischemia diagnosis, with reported sensitivity and specificity as high as 93% to 100% and potential to improve patient survival.
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340. - Summary of Recommendations
• Variant 1: CTA abdomen and pelvis with IV contrast is the recommended initial imaging examination for patients with suspected acute mesenteric ischemia.
• Variant 2: CTA abdomen and pelvis with IV contrast or MRA abdomen and pelvis without and with IV contrast is recommended as the initial imaging examination in patients with suspected chronic mesenteric ischemia.
• CTA abdomen and pelvis with IV contrast has been shown to provide best accuracy and inter-reader agreement for grading mesenteric vessel stenosis compared to MRA and US.
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340.
Stomach
- “CT findings suggestive of gastric cancer are asymmetric enhancement, diffuse or localized thickening of the gastric wall, a protruding ulcerous or polypoid mass, and lack of distensibility of the viscera (eg, linitis plastica).”
Staging of Gastric Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 - “Gastric cancer is one of the most common cancers worldwide—fifth in incidence in 2020—with a high mortality rate. The numbers are escalating because of increases in both risk factors and the population’s average age. In general, the incidence of gastric cancer is rising, even in young patients 40 years of age or older (6.2% in the United States), because of elements of the modern lifestyle and hereditary diffuse gastric cancer syndrome. The incidence is twice as high in men than in women, and the highest number of cases are in Eastern Asia, Eastern Europe, and Andean Latin America.”
Staging of Gastric Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 - Differentiating the cancers into noncardia and cardia is essential to understand the risk factors and epidemiology. In the former, Helicobacter pylori infection is the most important risk factor, followed by smoking, consuming grilled meat and alcohol, and a low-fruit diet. In the latter, gastroesophageal reflux disease is the most relevant causative agent, along with obesity. Familial aggregation has been demonstrated in 10% of cases. Particularly in young patients, only 3% have a predisposing genetic mutation (ie, CDH1 and CTNNA1).
Staging of Gastric Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 
- “The clinical staging mainly is assisted by contrast-enhanced CT. The performance of CT in EGC usually is limited. Therefore, endoscopic US is suggested to have better performance. Endoscopic US also performs better in surgical planning to define the proximal and distal extent of the tumor. Nevertheless, the accuracy of endoscopic US, which ranges from 57% to 88% in T staging and 30% to 90% in N staging, could be affected by operator experience. In locally advanced gastric cancer (LAGC) (cT3–T4), CT has good performance for both T and M staging.”
Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 - The potential of CT in clinical staging is strictly linked to an appropriate CT protocol, which consists of the three fundamentals: fasting for at least 6 hours, gastric lumen distention, and a multiphasic contrast-enhanced approach . Gastric lumen distention can be achieved through the oral administration of 800–1000 mL of water immediately before the scan or 4–7 g of effervescent tablets within 80–100 mL of water 3 minutes prior to the scan. Imaging is performed in a supine position before and after administration of intravenous contrast media. The thorax and abdomen-pelvis should be covered. There are no consensus guidelines regarding the amount of contrast media or rate of injection.
Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 - “The currently recommended multiphasic approach includes the unenhanced CT phase, the late arterial phase (40 seconds after the injection of intravenous contrast media), the portal venous phase (70 seconds after), and the delayed phase (180 seconds after). An unenhanced CT phase of the upper abdomen is usually recommended to assess the degree of stomach distention before contrast media administration. During the late arterial phase, the entire gastric volume should be covered, and in the portal venous phase, the thorax and abdomen-pelvis should be covered to detect nodal and distant metastases. The late arterial phase currently is considered the most important phase to evaluate the clinical T stage in EGC, in both diffuse and intestinal histotypes The delayed phase could be acquired because of the peak enhancement of undifferentiated tumors occurring at this phase and to have extra details in the deep mural invasion.”
Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 - The gastric wall distention before examination is essential to smooth out the normal folds and to detect any abnormal wall thickening. Usually, the rugal fold is more prominent in the greater curvature and the fundus. The submucosa appears as a hypoattenuation line, with varying thickness, covered by the outer layer, which has a slighter lower attenuation than the mucosa. The thickness usually is about 5 mm but it is site-specific. The antrum generally exceeds 5 mm and, depending on the grade of distention, up to 10 mm.
Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 
Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186- Distinguishing T3 from T4a at CT may be difficult, considering the serosa is not visible on CT images and the amount of subserosal adipose tissue is different from one person to another. The nodular or irregular appearance of the outer surface, haziness of the perigastric fat, and the hyperattenuating serosa sign, typical of serosal invasion, are findings that differentiate T3 from T4a gastric cancer. Furthermore, hyperattenuating serosa sign may be considered an independent predicting factor in identifying T4a gastric cancer with a good positive predictive value. The invasion of adjacent organs from gastric cancer (T4b) may be evident as a direct extension into an adjacent organ or as an obliteration of the interspersed adipose tissue, between the gastric mass and adjacent organs. Direct invasion by contiguity most frequently involves the liver, gallbladder, biliary tract, spleen, pancreas, and colon.
Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 - Lymph node involvement in gastric cancer has a high prognostic importance for overall survival. Each radiologic report should describe the number of enlarged nodes with malignant features . According to international guidelines, the following CT criteria are suggestive of pathologic nodes: rounded shape, hypoattenuation caused by necrosis or patchy enhancement, and a lymph node dimension of greater than 6–8 mm for the short axis, which is considered to be malignant . However, the sensitivity of CT is highly variable and sometimes not sufficient.
Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 - Currently, CT is the first option in the evaluation of peritoneal implants because of its availability and robustness; however, sensitivity and specificity are not excellent (66% and 77%, respectively) and are mainly related to the region of the abdomen and the diameter of the lesions. CT findings suggesting peritoneal metastasis include ascites, soft-tissue nodules or plaques on the peritoneal surface, small bowel wall thickening and nodularity, intra-abdominal fat stranding, and peritoneal thickening and/or hyperenhancement . The presence of ascites on CT images could be indicative of peritoneal involvement, but minimal ascites (<50 mL) without other findings are rarely associated with peritoneal metastasis.
Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 - The two most relevant CT constraints are over- or understaging, which is easily understood by looking at the mismatch between the histologic gastric wall composition, with five different layers, and CT multilayer visualization, with only three layers, the outer layer of which includes muscularis propriae, subserosa, and serosa. Starting from this assumption, the relatively poor performance of CT in differentiating EGC from LAGC could be justified . A new proposal has emerged to reduce the risk of overstaging in EGC, based on the introduction of a small CT window with a width of 150– 200 HU and a level of 80–100 HU. The gastric window was able to enhance gastric cancer in both cT1 and cT2, with an accuracy of 88.9%–91.5% and 82.4%–85.6%, respectively. However, the low attenuation of peritumoral fatty tissue in the gastric window should be considered, and in LAGC, it may lead to understaging.
Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186 - Thus far, diagnosis, staging, and therapeutic workflow of gastric cancer mostly is dependent on a multimodality approach. CT has a key role in clinical staging, which is essential to deciding the appropriate therapeutic strategy, usually in combination with endoscopic US and laparoscopy. The correct CT protocol is fundamental to obtaining an accurate T staging and reducing the bias linked to a lack of gastric lumen distention. Overall, CT has several consistent limitations concerning the identification of ECG, the differentiation of cT3 from CT4a, nodal staging, and restaging. Then, becoming aware of the mismatch existing between radiologic and pathologic multilayer visualization and having a head-to-head competition of these methods might be seen as a useful approach to reduce the common CT pitfalls that lead to overstaging and understaging.
Cancer: CT Patterns and Correlation with Pathologic Findings
Francesca Di Gregorio et al.
RadioGraphics 2025; 45(8):e240186
Vascular
- Mesenteric ischemia is an uncommon disease affecting the small and large bowel resulting from a reduction of intestinal blood flow. Although the disease is responsible for fewer than 1 in 1,000 hospital admissions, the mortality rate remains high, ranging between 30% to 90% in acute settings despite advances in treatment options. The etiology of ischemia may vary from arterial occlusion, venous thrombosis, or vasoconstriction. Higher prevalence in the elderly population and nonspecific clinical presentation leading to delayed diagnosis contribute to the high mortality rate. Most cases of mesenteric ischemia are due to an acute event leading to decreased blood supply to the splanchnic vasculature. Chronic mesenteric ischemia is uncommon, accounting for <5% of cases of mesenteric ischemia, and is almost always associated with diffuse atherosclerotic disease.
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340. - Acute mesenteric ischemia is most commonly secondary to acute embolism to the superior mesenteric artery (SMA), which accounts for approximately 40% to 50% of all episodes. Acute mesenteric artery thrombosis is the second most common cause of acute mesenteric ischemia (20%–30%) followed by nonocclusive mesenteric ischemia (25%) and, less commonly, mesenteric and portal venous thrombosis (5%–15%). In the chronic setting, mesenteric ischemia is almost always caused by severe atherosclerotic disease, with rare causes including fibromuscular dysplasia, median arcuate ligament syndrome, dissection, and vasculitis.
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340. - Acute embolization of the SMA involves the distal aspect of the vessel, usually beyond the origin of the middle colic artery, and commonly does not have associated collateral vessels. Acute mesenteric artery thrombosis is typically associated with chronic atherosclerotic disease and, given its more insidious course, a well-developed collateral circulation is commonly present. Nonocclusive mesenteric ischemia is seen in the setting of hypoperfusion because of secondary vasoconstriction of the mesenteric arteries. In these cases, there is no evidence of vascular occlusion, and the ischemia is distributed over a wider area of the bowel in a nonconsecutive manner. Mesenteric and portal venous thrombosis is the least common cause of acute mesenteric ischemia and may be idiopathic. Most common risk factors are hypercoagulable states, portal hypertension, and recent surgery. Bowel ischemia results from impaired intestinal mucosa venous outflow, leading to visceral edema and subsequent arterial hypoperfusion.
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340. - CTA of the abdomen and pelvis is a fast, accurate, and noninvasive diagnostic tool for evaluating the bowel and assessing intestinal vasculature and should be the first-step imaging approach in patients with acute bowel ischemia. CTA can be helpful in stratifying patients to identify those who would benefit from angiography as opposed to the ones who should undergo emergent surgery. Grading the degree of arterial stenosis with CTA has also been shown to be highly accurate compared to digital subtraction imaging (DSA) as well as other imaging modalities, including US and MRA . A negative or neutral oral contrast, such as low-density barium sulfate or water, has been advocated to distend the small bowel and better evaluate the bowel wall for thickening and enhancement; however this may not be possible in the acute setting . Both arterial and portal venous phases should be included as part of the protocol to assess both arterial and venous patency . Three-dimensional (3-D) rendering may also assist in evaluating the vasculature and should be performed .
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340. - Vascular CT findings include arterial stenosis, embolism, thrombosis, arterial dissection, and mesenteric vein thrombosis. Nonvascular CT findings include bowel-wall thickening, hypoperfusion and hypoattenuation, bowel dilatation, bowel-wall hemorrhage, mesenteric fat stranding, pneumatosis intestinalis, and portal venous gas. Quantitative methods of assessing bowel enhancement may also add value in identifying ischemic bowel . CTA is also preferred in patients with renal insufficiency with GFR under 30 who have suspected acute ischemia as benefits of a fast and accurate diagnosis will generally outweigh risks associated with potential risk of contrast-induced nephropathy. Overall, CTA is an accurate technique for acute mesenteric ischemia diagnosis, with reported sensitivity and specificity as high as 93% to 100% and potential to improve patient survival.
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340. - Summary of Recommendations
• Variant 1: CTA abdomen and pelvis with IV contrast is the recommended initial imaging examination for patients with suspected acute mesenteric ischemia.
• Variant 2: CTA abdomen and pelvis with IV contrast or MRA abdomen and pelvis without and with IV contrast is recommended as the initial imaging examination in patients with suspected chronic mesenteric ischemia.
• CTA abdomen and pelvis with IV contrast has been shown to provide best accuracy and inter-reader agreement for grading mesenteric vessel stenosis compared to MRA and US.
ACR Appropriateness Criteria® Imaging of Mesenteric Ischemia.
Ginsburg M, Obara P, Lambert DL, et al.
J Am Coll Radiol. 2018 Nov;15(11S):S332-S340.
