The Role of Imaging for Gastrointestinal Bleeding: Consensus Recommendations From the American College of Gastroenterology and Society of Abdominal Radiology.

Gastrointestinal (GI) bleeding is the most common GI diagnosis leading to hospitalization within the United States. Prompt diagnosis and treatment of GI bleeding is critical to improving patient outcomes and reducing high healthcare utilization and costs. Radiologic techniques including computed tomography angiography, catheter angiography, computed tomography enterography, magnetic resonance enterography, nuclear medicine red blood cell scan, and technetium-99m pertechnetate scintigraphy (Meckel scan) are frequently used to evaluate patients with GI bleeding and are complementary to GI endoscopy. However, multiple management guidelines exist which differ in the recommended utilization of these radiologic examinations. This variability can lead to confusion as to how these tests should be used in the evaluation of GI bleeding. In this document, a panel of experts from the American College of Gastroenterology and Society of Abdominal Radiology provide a review of the radiologic examinations used to evaluate for GI bleeding including nomenclature, technique, performance, advantages, and limitations. A comparison of advantages and limitations relative to endoscopic examinations is also included. Finally, consensus statements and recommendations on technical parameters and utilization of radiologic techniques for GI bleeding are provided.

CT Colonography Reporting and Data System (C-RADS): Version 2023 Update.

The CT Colonography Reporting and Data System (C-RADS) has withstood the test of time and proven to be a robust classification scheme for CT colonography (CTC) findings. C-RADS version 2023 represents an update on the scheme used for colorectal and extracolonic findings at CTC. The update provides useful insights gained since the implementation of the original system in 2005. Increased experience has demonstrated confusion on how to classify the mass-like appearance of the colon consisting of soft tissue attenuation that occurs in segments with acute or chronic diverticulitis. Therefore, the update introduces a new subcategory, C2b, specifically for mass-like diverticular strictures, which are likely benign. Additionally, the update simplifies extracolonic classification by combining E1 and E2 categories into an updated extracolonic category of E1/E2 since, irrespective of whether a finding is considered a normal variant (category E1) or an otherwise clinically unimportant finding (category E2), no additional follow-up is required. This simplifies and streamlines the classification into one category, which results in the same management recommendation.

The Role of Imaging for GI Bleeding: ACG and SAR Consensus Recommendations.

Gastrointestinal (GI) bleeding is the most common GI diagnosis leading to hospitalization within the United States. Prompt diagnosis and treatment of GI bleeding is critical to improving patient outcomes and reducing high health care utilization and costs. Radiologic techniques including CT angiography, catheter angiography, CT enterography, MR enterography, nuclear medicine red blood cell scan, and technetium-99m pertechnetate scintigraphy (Meckel scan) are frequently used to evaluate patients with GI bleeding and are complementary to GI endoscopy. However, multiple management guidelines exist, which differ in the recommended utilization of these radiologic examinations. This variability can lead to confusion as to how these tests should be used in the evaluation of GI bleeding. In this document, a panel of experts from the American College of Gastroenterology and Society of Abdominal Radiology provide a review of the radiologic examinations used to evaluate for GI bleeding including nomenclature, technique, performance, advantages, and limitations. A comparison of advantages and limitations relative to endoscopic examinations is also included. Finally, consensus statements and recommendations on technical parameters and utilization of radiologic techniques for GI bleeding are provided. © Radiological Society of North America and the American College of Gastroenterology, 2024. Supplemental material is available for this article. This article is being published concurrently in American Journal of Gastroenterology and Radiology. The articles are identical except for minor stylistic and spelling differences in keeping with each journal's style. Citations from either journal can be used when citing this article. See also the editorial by Lockhart in this issue.

Radiofrequency ablation of subcapsular versus nonsubcapsular hepatocellular carcinomas ≤ 3 cm: analysis of long-term outcomes from two large-volume liver centers.

OBJECTIVES: To compare the safety and efficacy of RFA for single HCCs ≤ 3 cm in subcapsular versus nonsubcapsular locations using a propensity score matched analysis. MATERIALS AND METHODS: This retrospective study included patients with solitary HCCs ≤ 3 cm in size who underwent percutaneous RFA from 2005 to 2015 as initial treatment at two large-volume liver centers. Patients were divided into two groups, consisting of those with subcapsular and nonsubcapsular tumor locations. Complications, local tumor progression (LTP), and overall survival (OS) were compared in these two groups before and after propensity score matching (PSM). RESULTS: The study population consisted of 964 patients (712 men [74%]) of mean age 58.3 years. Of these 964 patients, 561 (58%) had nonsubcapsular and 403 (42%) had subcapsular HCCs. PSM generated 402 pairs of patients. Major complication rate was low, but significantly higher in the subcapscular group (p = 0.047). Rates of technical effectiveness in these two groups were 99% and 98%, respectively (p = 0.315). However, during follow-up, cumulative 1-, 3-, 5-, and 10-year LTP and OS rates did significantly differ in both entire and PSM cohorts, resulting in the latter 8%, 15%, 20%, and 26% in the nonsubcapsular group vs. 13%, 24%, 30%, and 31% in the subcapsular group (p = 0.015), and 99%, 91%, 80%, and 59% vs. 98%, 85%, 73%, and 50% in the two groups (p = 0.004), respectively. CONCLUSION: Rates of major complications, LTP, and OS differed significantly following first-line RFA treatment of single HCCs ≤ 3 cm in favor of the nonsubcapsular locations. CLINICAL RELEVANCE STATEMENT: This large-scale study provides evidence that radiofrequency ablation for small (≤ 3 cm) hepatocellular carcinomas is safer and more effective in nonsubcapsular location than in subcapsular location. KEY POINTS: • There exist conflicting outcomes on the effectiveness of RFA for early HCC depending on tumor location. • Rate of local tumor progression was significantly higher in the subcapsular hepatocellular carcinomas. • Overall survival rate was significantly poorer in the subcapsular hepatocellular carcinomas.

Radiologist's Guide to Evaluating Publications of Clinical Research on AI: How We Do It.

Literacy in research studies of artificial intelligence (AI) has become an important skill for radiologists. It is required to make a proper assessment of the validity, reproducibility, and clinical applicability of AI studies. However, AI studies are generally perceived to be more difficult for clinician readers to evaluate than traditional clinical research studies. This special report-as an effective, concise guide for readers-aims to assist clinical radiologists in critically evaluating different types of clinical research articles involving AI. It does not intend to be a comprehensive checklist or methodological summary for complete clinical evaluation of AI or a reporting guideline. Ten key items for readers to check are described, regarding study purpose, function and clinical context of AI, training data, data preprocessing, AI modeling techniques, test data, AI performance, helpfulness and value of AI, interpretability of AI, and code sharing. The important aspects of each item are explained for readers to consider when reading publications on AI clinical research. Evaluating each item can help radiologists assess the validity, reproducibility, and clinical applicability of clinical research articles involving AI.

Methods for Clinical Evaluation of Artificial Intelligence Algorithms for Medical Diagnosis.

Adequate clinical evaluation of artificial intelligence (AI) algorithms before adoption in practice is critical. Clinical evaluation aims to confirm acceptable AI performance through adequate external testing and confirm the benefits of AI-assisted care compared with conventional care through appropriately designed and conducted studies, for which prospective studies are desirable. This article explains some of the fundamental methodological points that should be considered when designing and appraising the clinical evaluation of AI algorithms for medical diagnosis. The specific topics addressed include the following: (a) the importance of external testing of AI algorithms and strategies for conducting the external testing effectively, (b) the various metrics and graphical methods for evaluating the AI performance as well as essential methodological points to note in using and interpreting them, (c) paired study designs primarily for comparative performance evaluation of conventional and AI-assisted diagnoses, (d) parallel study designs primarily for evaluating the effect of AI intervention with an emphasis on randomized clinical trials, and (e) up-to-date guidelines for reporting clinical studies on AI, with an emphasis on guidelines registered in the EQUATOR Network library. Sound methodological knowledge of these topics will aid the design, execution, reporting, and appraisal of clinical evaluation of AI.

Deep Learning-based Detection of Solid and Cystic Pancreatic Neoplasms at Contrast-enhanced CT.

Background Deep learning (DL) may facilitate the diagnosis of various pancreatic lesions at imaging. Purpose To develop and validate a DL-based approach for automatic identification of patients with various solid and cystic pancreatic neoplasms at abdominal CT and compare its diagnostic performance with that of radiologists. Materials and Methods In this retrospective study, a three-dimensional nnU-Net-based DL model was trained using the CT data of patients who underwent resection for pancreatic lesions between January 2014 and March 2015 and a subset of patients without pancreatic abnormality who underwent CT in 2014. Performance of the DL-based approach to identify patients with pancreatic lesions was evaluated in a temporally independent cohort (test set 1) and a temporally and spatially independent cohort (test set 2) and was compared with that of two board-certified radiologists. Performance was assessed using receiver operating characteristic analysis. Results The study included 852 patients in the training set (median age, 60 years [range, 19-85 years]; 462 men), 603 patients in test set 1 (median age, 58 years [range, 18-82 years]; 376 men), and 589 patients in test set 2 (median age, 63 years [range, 18-99 years]; 343 men). In test set 1, the DL-based approach had an area under the receiver operating characteristic curve (AUC) of 0.91 (95% CI: 0.89, 0.94) and showed slightly worse performance in test set 2 (AUC, 0.87 [95% CI: 0.84, 0.89]). The DL-based approach showed high sensitivity in identifying patients with solid lesions of any size (98%-100%) or cystic lesions measuring 1.0 cm or larger (92%-93%), which was comparable with the radiologists (95%-100% for solid lesions [P = .51 to P > .99]; 93%-98% for cystic lesions ≥1.0 cm [P = .38 to P > .99]). Conclusion The deep learning-based approach demonstrated high performance in identifying patients with various solid and cystic pancreatic lesions at CT. © RSNA, 2022 Online supplemental material is available for this article.

Multicentre external validation of a commercial artificial intelligence software to analyse chest radiographs in health screening environments with low disease prevalence.

OBJECTIVES: To externally validate the performance of a commercial AI software program for interpreting CXRs in a large, consecutive, real-world cohort from primary healthcare centres. METHODS: A total of 3047 CXRs were collected from two primary healthcare centres, characterised by low disease prevalence, between January and December 2018. All CXRs were labelled as normal or abnormal according to CT findings. Four radiology residents read all CXRs twice with and without AI assistance. The performances of the AI and readers with and without AI assistance were measured in terms of area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. RESULTS: The prevalence of clinically significant lesions was 2.2% (68 of 3047). The AUROC, sensitivity, and specificity of the AI were 0.648 (95% confidence interval [CI] 0.630-0.665), 35.3% (CI, 24.7-47.8), and 94.2% (CI, 93.3-95.0), respectively. AI detected 12 of 41 pneumonia, 3 of 5 tuberculosis, and 9 of 22 tumours. AI-undetected lesions tended to be smaller than true-positive lesions. The readers' AUROCs ranged from 0.534-0.676 without AI and 0.571-0.688 with AI (all p values < 0.05). For all readers, the mean reading time was 2.96-10.27 s longer with AI assistance (all p values < 0.05). CONCLUSIONS: The performance of commercial AI in these high-volume, low-prevalence settings was poorer than expected, although it modestly boosted the performance of less-experienced readers. The technical prowess of AI demonstrated in experimental settings and approved by regulatory bodies may not directly translate to real-world practice, especially where the demand for AI assistance is highest. KEY POINTS: • This study shows the limited applicability of commercial AI software for detecting abnormalities in CXRs in a health screening population. • When using AI software in a specific clinical setting that differs from the training setting, it is necessary to adjust the threshold or perform additional training with such data that reflects this environment well. • Prospective test accuracy studies, randomised controlled trials, or cohort studies are needed to examine AI software to be implemented in real clinical practice.

Involvement of tissue changes induced by neoadjuvant treatment in total mesorectal excision (TME): novel suggestions for determining TME quality.

BACKGROUND: Few studies to date have investigated morphological changes after neoadjuvant treatment (NAT) and their implications in total mesorectal excision (TME). This study was primarily designed to evaluate whether tissue changes associated with NAT affected the quality of TME and additionally to suggest a more objective method evaluating TME quality. METHODS: This study enrolled 1322 consecutive patients who underwent curative robot-assisted surgery for rectal cancer. Patients who did and did not receive NAT were subjected to propensity-score matching, yielding 402 patients in each group. RESULTS: NAT independently reduced complete achievement of TME [odds ratio (OR) = 2.056, p = 0.017]. Intraoperative evaluation identified seven tissue changes significantly associated with NAT, including tumor perforation, mucin pool, necrosis, fibrosis, fat degeneration, and rectal or perirectal edema NAT (p < 0.001-0.05). Tumor perforation (OR = 5.299, p = 0.001) and mucin pool (OR = 14.053, p = 0.002) were independently associated with inappropriate (near-complete + incomplete) TME. Complete TME resulted in significantly reduced local recurrence (4.3% vs 15.3%, p = 0.003) and increased 5-year DFS rate (80.6% vs 67.6%, p = 0.047) compared with inappropriate one. By contrast, two tiers of complete and near-complete TMEs vs incomplete TME did not. Notably, among patients with complete TME, those who received NAT had a lower 5-year DFS than those who did not (77.8% vs 83.3%, p = 0.048). CONCLUSIONS: NAT-associated tissue changes, somewhat interrupting complete TME, may provide unsolved clue to the relative inability of NAT to improve overall survival. The conventional three-tier grading of TME seems to be simplified into two tiers as complete and inappropriate.

A Single-Center Retrospective Analysis of Periprocedural Variables Affecting Local Tumor Progression after Radiofrequency Ablation of Colorectal Cancer Liver Metastases.

Background Local tumor progression (LTP) is associated with poorer survival in patients undergoing radiofrequency ablation (RFA) for colorectal liver metastasis (CLM). An algorithmic strategy to predict LTP may help in selection of patients who would benefit most from RFA for CLM. Purpose To estimate local tumor progression-free survival (LTPFS) following RFA of CLM and develop an algorithmic strategy based on clinical variables. Materials and Methods In this retrospective study, between March 2000 and December 2014, patients who underwent percutaneous RFA for CLM were randomly split into development (60%) and internal validation (40%) data sets. Kaplan-Meier method was used to estimate LTPFS and overall survival (OS) rates. Independent factors affecting LTPFS in the development data set were investigated by using multivariable Cox proportional hazard regression analysis. Risk scores were assigned to the risk factors and applied to the validation data set. Results A total of 365 patients (mean age, 60 years ± 11 [standard deviation]; 259 men) with 512 CLMs were evaluated. LTPFS and OS rates were 85% and 92% at 1 year, 73% and 41% at 5 years, 72% and 30% at 10 years, and 72% and 28% at 15 years, respectively. Independent risk factors for LTP included tumor size of 2 cm or greater (hazard ratio [HR], 3.8; 95% CI: 2.3, 6.2; P < .001), subcapsular tumor location (HR, 1.9; 95% CI: 1.1, 3.1; P = .02), and minimal ablative margin of 5 mm or less (HR, 11.7; 95% CI: 4.7, 29.2; P < .001). A prediction model that used the risk factors had areas under the curve of 0.89, 0.92, and 0.90 at 1, 5, and 10 years, respectively, and it showed significantly better areas under the curve when compared with the model using the minimal ablative margin of 5 mm or less alone. Conclusion Radiofrequency ablation provided long-term control of colorectal liver metastases. Although minimal ablative margin of 5 mm or less was the most dominant factor, the multifactorial approach including tumor size and subcapsular location better predicted local tumor progression-free survival. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Soulen and Sofocleous in this issue.

Sleep structure and electroencephalographic spectral power of middle-aged or older adults: Normative values by age and sex in the Korean population.

The fine structure of sleep electrocortical activity reflects health and disease. The current study provides normative data for sleep structure and electroencephalography (EEG) spectral power measures derived from overnight polysomnography (PSG) and examines the effect of age and sex among Korean middle-aged and older adults with or without obstructive sleep apnea (OSA). We analysed home PSG data from 1,153 adult participants of an ongoing population-based cohort study, the Korean Genome and Epidemiology Study. Sleep stages were visually scored and spectral power was measured on a single-channel EEG (C4-A1). We computed spectral power for five frequency ranges. The EEG power was reported in relative (%) and log-transformed absolute values (µV2 ). With ageing, the proportion of N1 sleep increased, whereas N3 decreased, which is more noticeable in men than in women. The amount of N3 was relatively low in this cohort. With ageing, relative delta power decreased and alpha and sigma power increased for the whole sleep period, which was more pronounced during REM sleep in non-OSA. For men compared with women, relative theta power was lower during REM and sigma and beta were higher during N1 sleep. The differences of relative powers by age and sex in OSA were comparable to those in non-OSA. In a community-based Korean population, we present normative data of sleep structure and spectral power for middle-aged or older adults of a non-Caucasian ethnicity. The values varied with age and sex and were not influenced by sleep apnea.

Deep learning-based algorithm to detect primary hepatic malignancy in multiphase CT of patients at high risk for HCC.

OBJECTIVES: To develop and evaluate a deep learning-based model capable of detecting primary hepatic malignancies in multiphase CT images of patients at high risk for hepatocellular carcinoma (HCC). METHODS: A total of 1350 multiphase CT scans of 1280 hepatic malignancies (1202 HCCs and 78 non-HCCs) in 1320 patients at high risk for HCC were retrospectively analyzed. Following the delineation of the focal hepatic lesions according to reference standards, the CT scans were categorized randomly into the training (568 scans), tuning (193 scans), and test (589 scans) sets. Multiphase CT information was subjected to multichannel integration, and livers were automatically segmented before model development. A deep learning-based model capable of detecting malignancies was developed using a mask region-based convolutional neural network. The thresholds of the prediction score and the intersection over union were determined on the tuning set corresponding to the highest sensitivity with < 5 false-positive cases per CT scan. The sensitivity and the number of false-positives of the proposed model on the test set were calculated. Potential causes of false-negatives and false-positives on the test set were analyzed. RESULTS: This model exhibited a sensitivity of 84.8% with 4.80 false-positives per CT scan on the test set. The most frequent potential causes of false-negatives and false-positives were determined to be atypical enhancement patterns for HCC (71.7%) and registration/segmentation errors (42.7%), respectively. CONCLUSIONS: The proposed deep learning-based model developed to automatically detect primary hepatic malignancies exhibited an 84.8% of sensitivity with 4.80 false-positives per CT scan in the test set. KEY POINTS: • Image processing, including multichannel integration of multiphase CT and automatic liver segmentation, enabled the application of a deep learning-based model to detect primary hepatic malignancy. • Our model exhibited a sensitivity of 84.8% with a false-positive rate of 4.80 per CT scan.

The Liver Imaging Reporting and Data System tumor-in-vein category: a systematic review and meta-analysis.

OBJECTIVES: We aimed to systematically determine the etiology of the Liver Imaging Reporting and Data System (LI-RADS) tumor-in-vein category (LR-TIV) on contrast-enhanced CT or MRI and to determine the sources of heterogeneity between reported results. METHODS: Original studies reporting the etiology of LR-TIV were identified in MEDLINE and EMBASE up until July 7, 2020. The meta-analytic pooled percentages of HCC and non-HCC in LR-TIV were calculated. Subgroup analyses were performed according to the type of reference standard and the most common underlying liver disease. Meta-regression analysis was performed to explore study heterogeneity. RESULTS: Sixteen studies reported the etiology of a total of 150 LR-TIV, of which 98 (65%) were HCC and 52 (35%) were non-HCC. The meta-analytic pooled percentages of HCC and non-HCC in LR-TIV were 70.9% (95% confidence interval [CI], 55.7-82.5%; I2 = 59%) and 29.2% (95% CI, 17.5-44.4%; I2 = 59%), respectively. The meta-analytic pooled percentage of HCC was lower in studies using only pathology as a reference standard (67.1%; 95% CI, 49.3-81.1%), but higher in studies in which hepatitis C was the most common underlying liver disease (81.9%; 95% CI, 11.3-99.4%) than that in the total 16 studies. Study type (cohort study versus case-control study) was significantly associated with study heterogeneity (p = 0.04). CONCLUSION: The most common etiology of LR-TIV was HCC. It might be important to understand the percentage of HCC and non-HCC in LR-TIV in consideration of the type of reference standard, geographic differences, and study design. KEY POINTS: • The most common etiology of Liver Imaging Reporting and Data System (LI-RADS) tumor-in-vein category (LR-TIV) was hepatocellular carcinoma (HCC). • The percentage of HCC in LR-TIV was relatively low in studies using only pathology as a reference standard, but high in studies in which hepatitis C was the most common underlying liver disease. • Study type was a factor significantly influencing study heterogeneity.

CT in the prediction of margin-negative resection in pancreatic cancer following neoadjuvant treatment: a systematic review and meta-analysis.

OBJECTIVES: We aimed to systematically evaluate the diagnostic accuracy of CT-determined resectability following neoadjuvant treatment for predicting margin-negative resection (R0 resection) in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: Original studies with sufficient details to obtain the sensitivity and specificity of CT-determined resectability following neoadjuvant treatment, with a reference on the pathological margin status, were identified in PubMed, EMBASE, and Cochrane databases until February 24, 2020. The identified studies were divided into two groups based on the criteria of R0 resectable tumor (ordinary criterion: resectable PDAC alone; extended criterion: resectable and borderline resectable PDAC). The meta-analytic summary of the sensitivity and specificity for each criterion was estimated separately using a bivariate random-effect model. Summary results of the two criteria were compared using a joint-model bivariate meta-regression. RESULTS: Of 739 studies initially searched, 6 studies (6 with ordinary criterion and 5 with extended criterion) were included for analysis. The meta-analytic summary of sensitivity and specificity was 45% (95% confidence interval [CI], 19-73%; I2 = 88.3%) and 85% (95% CI, 65-94%; I2 = 60.5%) for the ordinary criterion, and 81% (95% CI, 71-87%; I2 = 0.0%) and 42% (95% CI, 28-57%; I2 = 6.2%) for the extended criterion, respectively. The diagnostic accuracy significantly differed between the two criteria (p = 0.02). CONCLUSIONS: For determining resectability on CT, the ordinary criterion might be highly specific but insensitive for predicting R0 resection, whereas the extended criterion increased sensitivity but would decrease specificity. Further investigations using quantitative parameters may improve the identification of R0 resection. KEY POINTS: • CT-determined resectability of PDAC after neoadjuvant treatment using the ordinary criterion shows low sensitivity and high specificity in predicting R0 resection. • With the extended criterion, CT-determined resectability shows higher sensitivity but lower specificity than with the ordinary criterion. • CT-determined resectability with both criteria achieved suboptimal diagnostic performances, suggesting that care should be taken while selecting surgical candidates and when determining the surgical extent after neoadjuvant treatment in patients with PDAC.

Gastrointestinal Bleeding at CT Angiography and CT Enterography: Imaging Atlas and Glossary of Terms.

Gastrointestinal (GI) bleeding is a common potentially life-threatening medical condition frequently requiring multidisciplinary collaboration to reach the proper diagnosis and guide management. GI bleeding can be overt (eg, visible hemorrhage such as hematemesis, hematochezia, or melena) or occult (eg, positive fecal occult blood test or iron deficiency anemia). Upper GI bleeding, which originates proximal to the ligament of Treitz, is more common than lower GI bleeding, which arises distal to the ligament of Treitz. Small bowel bleeding accounts for 5-10% of GI bleeding cases commonly manifesting as obscure GI bleeding, where the source remains unknown after complete GI tract endoscopic and imaging evaluation. CT can aid in identifying the location and cause of bleeding and is an important complementary tool to endoscopy, nuclear medicine, and angiography in evaluating patients with GI bleeding. For radiologists, interpreting CT scans in patients with GI bleeding can be challenging owing to the large number of images and the diverse potential causes of bleeding. The purpose of this pictorial review by the Society of Abdominal Radiology GI Bleeding Disease-Focused Panel is to provide a practical resource for radiologists interpreting GI bleeding CT studies that reviews the proper GI bleeding terminology, the most common causes of GI bleeding, key patient history and risk factors, the optimal CT imaging technique, and guidelines for case interpretation and illustrates many common causes of GI bleeding. A CT reporting template is included to help generate radiology reports that can add value to patient care. An invited commentary by Al Hawary is available online. Online supplemental material is available for this article. ©RSNA, 2021.

Supplementary Anal Imaging by Magnetic Resonance Enterography in Patients with Crohn's Disease Not Suspected of Having Perianal Fistulas.

BACKGROUND & AIMS: Few data are available to guide the use of anal imaging for patients with Crohn's disease (CD) who are not suspected of having perianal fistulas. We aimed to evaluate the role of anal imaging supplementary to magnetic resonance enterography (MRE) in these patients. METHODS: In a prospective study, we added a round of anal MR imaging (MRI), collecting axial images alone, to MRE evaluation of 451 consecutive adults who were diagnosed with or suspected of having CD but not believed to have perianal fistulas. Images were examined for perianal tracts; if present, colorectal surgeons reexamined patients to identify external openings or perianal inflammation or abscess. Patients were followed and data were collected on dedicated treatment for perianal fistulas or abscess. We calculated the diagnostic yield for anal MRI, associated factors, and outcomes of MRI-detected asymptomatic perianal tracts. RESULTS: A total of 440 patients (mean age, 29.6±8.9 years) met the inclusion criteria. Anal MRI revealed perianal tracts in 53 patients (12%; 95% CI, 9.3%-15.4%). Surgeons however did not identify any lesions that required treatment. The asymptomatic tracts were mostly single unbranched (83%), inter-sphincteric (72%), or had a linear dark signal at the tract margin (79%). Younger age at MRE, female sex, and CD activity index scores of 220-450 were independently associated with detection of perianal tracts. MRI detection of asymptomatic tracts was independently associated with later development of perianal fistulas or abscess that required treatment: 17.8% cumulative incidence at 37 months and an adjusted hazard ratio of 3.06 (95% CI, 1.01-9.27; P = .048). CONCLUSIONS: In a prospective study of patients with CD, we found that adding anal MRI evaluation to MRE resulted in early identification of patients at risk for perianal complications.

Interreader Agreement of Liver Imaging Reporting and Data System on MRI: A Systematic Review and Meta-Analysis.

BACKGROUND: Use of the Liver Imaging Reporting and Data System (LI-RADS) is increasing, but the reported results for interreader agreement seem quite variable. PURPOSE: To systematically determine the interreader agreement of LI-RADS on magnetic resonance imaging (MRI) and to determine the sources of heterogeneity between the reported results. STUDY TYPE: Systematic review and meta-analysis. SUBJECTS: Fifteen original articles with 2968 lesions. FIELD STRENGTH: 1.5T and 3.0T. ASSESSMENT: Two reviewers independently performed the data extraction. The reviewers identified and reviewed the original articles reporting the interreader agreement of LI-RADS using MRI. STATISTICAL TESTS: The meta-analytic pooled intraclass correlation coefficient (ICC) for lesion size and kappa value (κ) for major features (arterial-phase hyperenhancement [APHE], nonperipheral washout [WO], enhancing capsule [EC]) and LI-RADS categorization (LR) were calculated using the random-effects model. Sensitivity analysis and meta-regression analysis were performed to explore the cause of study heterogeneity. RESULTS: The meta-analytic pooled ICC of lesion size was 0.97 (95% confidence interval [CI], 0.94-1.00). Meta-analytic pooled κ of APHE, WO, EC, and LR were 0.72 (95% CI, 0.62-0.82), 0.69 (95% CI, 0.60-0.78), 0.66 (95% CI, 0.58-0.74), and 0.70 (95% CI, 0.56-0.85), respectively. Substantial study heterogeneity was noted in all five variables (I2 ≥ 89.1%, P < 0.001). Study design, type, and clarity of blinding review were factors that significantly influenced study heterogeneity (P ≤ 0.05). DATA CONCLUSION: LI-RADS demonstrated overall substantial interreader agreement for major features and the category on MRI, but showed heterogeneous results between studies. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:795-804.

Liver imaging reporting and data system category M: A systematic review and meta-analysis.

BACKGROUND AND AIMS: The Liver Imaging Reporting and Data System (LI-RADS) category M (LR-M) was introduced to preserve the high specificity of LI-RADS algorithm for diagnosing hepatocellular carcinoma (HCC). We aimed to systematically determine the probability of the LR-M for HCC and non-HCC malignancy, and to determine the sources of heterogeneity between reported results. METHODS: Original studies reporting the probability of LR-M for HCC and non-HCC malignancy on magnetic resonance imaging (MRI) were identified in MEDLINE and EMBASE. The meta-analytic pooled percentages of HCC and non-HCC in LR-M were calculated. Meta-regression analysis was performed to explore study heterogeneity. The meta-analytic frequency of each LR-M imaging feature was determined. RESULTS: We found 10 studies reporting the diagnostic performance of LR-M (1819 lesions in 1631 patients), and six reporting the frequency of LR-M imaging features. The pooled percentages of HCC and non-HCC malignancy for LR-M were 28.2% (95% confidence interval [CI], 23.8%-33.1%; I2  = 83%) and 69.6% (95% CI, 64.6%-74.1%; I2  = 83%) respectively. The study type and MRI scanner field strength were significantly associated with study heterogeneity (P ≤ .04). Of the seven imaging features, rim arterial phase hyperenhancement showed the highest frequency in both non-HCC (48.9%; 95% CI, 43.0%-54.8%) and HCC groups (9.8%; 95% CI, 6.9%-13.6%). CONCLUSIONS: The LR-M category most commonly included non-HCC malignancy but also included 28.2% of HCC. Substantial study heterogeneity was noted, and it was significantly associated with study type and MRI scanner field strength. In addition, the frequency of LR-M imaging features was variable.

MR tumor regression grade for pathological complete response in rectal cancer post neoadjuvant chemoradiotherapy: a systematic review and meta-analysis for accuracy.

OBJECTIVES: To determine the diagnostic accuracy of magnetic resonance tumor regression grade (mrTRG) for pathological complete response (pCR) and its correlation with pathological findings. METHODS: Original studies that investigated the correlation of mrTRG with pathological tumor regression grade and pathological T stage were identified in MEDLINE and EMBASE up until August 31, 2018, according to PRISMA guidelines. The search terms included colorectal cancer, chemoradiation therapy, magnetic resonance imaging, and response or regression. Meta-analytic summary sensitivity and specificity for pathologic complete response (pCR) and pathologic T1 or lower than T1 stage (≤ypT1) were calculated using a bivariate random-effects model. The sensitivity and specificity were calculated in both mrTRG 1 and mrTRG 1 or 2, respectively. RESULTS: Six studies with 916 patients were included. The meta-analytic summary sensitivity and specificity of mrTRG 1 for pCR were 32.3% (95% CI, 18.2-50.6%) and 93.5% (95% CI, 91.5-95.1%), while for ≤ypT1 they were 31.8% (95% CI, 16.2-53.0%) and 94.7% (95% CI, 91.9-96.5%). On the contrary, sensitivity and specificity of mrTRG 1 or 2 for pCR were 69.9% (95% CI, 60.2-78.1%) and 62.2% (95% CI, 56.2-67.8%), while those for ≤ypT1 were 71.4% (95% CI, 61.6-79.6%) and 67.7% (95% CI, 59.8-74.7%). CONCLUSIONS: mrTRG 1 showed high specificity for pCR and ≤ypT1, but suboptimal sensitivity. mrTRG 1 or 2 showed higher sensitivity for pCR and ≤ypT1, but lower specificity. Because of the suboptimal sensitivity of mrTRG 1, it might be limited as a criterion for less aggressive treatment after neoadjuvant chemoradiotherapy. KEY POINTS: • Magnetic resonance tumor regression grade 1 shows high specificity for pCR and ≤ypT1, but suboptimal sensitivity. • Magnetic resonance tumor regression grade 1 or 2 shows higher sensitivity for pCR and ≤ypT1, but lower specificity than magnetic resonance tumor regression grade 1 alone.

Traditional Serrated Adenomas on CT Colonography: International Multicenter Experience With This Rare Colorectal Neoplasm.

OBJECTIVE. Serrated polyps include hyperplastic polyps, sessile serrated polyps, and traditional serrated adenomas (TSAs). Hyperplastic polyps and sessile serrated polyps account for approximately 99% of all serrated lesions; TSAs are rare. However, both sessile serrated polyps and TSAs are now recognized as precursor lesions to carcinogenesis, representing approximately one-fourth of all sporadic colorectal cancers. We report what is, to our knowledge, the first series describing the characteristics of CTAs on CT colonography (CTC). MATERIALS AND METHODS. An international, multicenter, retrospective review of CT colonography-detected TSAs diagnosed between 2008 and 2018 was conducted. Data collected included patient demographics and data from CTC, optical colonoscopy, and pathologic analysis. RESULTS. A total of 67 proven TSAs in 58 patients (mean age, 67 years) were identified. The majority (66%) were located in the distal colon (descending colon, sigmoid colon, and rectum), and their mean size was 19 mm (range, 3-80 mm). Small (< 10 mm) TSAs typically had a simple sessile or pedunculated morphologic appearance, whereas large (≥ 10 mm) TSAs tended to be more lobulated and irregular, pedunculated, or carpetlike. The majority (88%) showed at least some contrast medium surface coating. CONCLUSION. We report what we believe to be the first multicenter experience describing the characteristics of TSAs on CTC. Unlike sessile serrated lesions, TSAs are more often left-sided and tend to be more lobulated and irregular. However, like sessile serrated polyps, most TSAs show contrast medium surface coating. Detection of these rare lesions on CTC is important, given their malignant potential.