Faculty Bibliography

Standardized terminology is critical to providing consistent reports to referring clinicians. This lexicon aims to provide a reference for terminology frequently used in rectal cancer and reflects the consensus of the Society of Abdominal Radiology Disease Focused Panel in Rectal cancer. This lexicon divided the terms into the following categories: primary tumor staging, nodal staging, treatment response, anal canal anatomy, general anatomy, and treatments.

PURPOSE:To predict microsatellite instability (MSI) status of colon cancer on preoperative CT imaging using radiomic analysis. METHODS:This retrospective study involved radiomic analysis of preoperative CT imaging of patients who underwent resection of stage II-III colon cancer from 2004 to 2012. A radiologist blinded to MSI status manually segmented the tumor region on CT images. 254 Intensity-based radiomic features were extracted from the tumor region. Three prediction models were developed with (1) only clinical features, (2) only radiomic features, and (3) "combined" clinical and radiomic features. Patients were randomly separated into training (n = 139) and test (n = 59) sets. The model was constructed from training data only; the test set was reserved for validation only. Model performance was evaluated using AUC, sensitivity, specificity, PPV, and NPV. RESULTS:Of the total 198 patients, 134 (68%) patients had microsatellite stable tumors and 64 (32%) patients had MSI tumors. The combined model performed slightly better than the other models, predicting MSI with an AUC of 0.80 for the training set and 0.79 for the test set (specificity = 96.8% and 92.5%, respectively), whereas the model with only clinical features achieved an AUC of 0.74 and the model with only radiomic features achieved an AUC of 0.76. The model with clinical features alone had the lowest specificity (70%) compared with the model with radiomic features alone (95%) and the combined model (92.5%). CONCLUSIONS:Preoperative prediction of MSI status via radiomic analysis of preoperative CT adds specificity to clinical assessment and could contribute to personalized treatment selection.

PURPOSE:To evaluate the role of diffusion kurtosis and diffusivity as potential imaging biomarkers to predict response to neoadjuvant chemoradiation therapy (CRT) from baseline staging magnetic resonance imaging (MRI) in locally advanced rectal cancer (LARC). MATERIALS AND METHODS:) for LARC followed by neoadjuvant chemoradiation and surgical resection. The mean age was 57.4 years (range 34.2-72.9). An abdominal radiologist using open source software manually segmented T2-weighted images. Segmentations were used to derive diffusion kurtosis and diffusivity from diffusion-weighted images as well as volumetric data. These data were analyzed with regard to tumor regression grade (TRG) using the four-tier American Joint Committee on Cancer (AJCC) classification, TRG 0-3. Proportional odds regression was used to analyze the four-level ordinal outcome. A sensitivity analysis was performed using univariable logistic regression for binary TRG groups, TRG 0/1 (> 90% response), or TRG 2/3 (< 90% response). p < 0.05 was considered significant throughout. RESULTS:values [all but region of interest (ROI)-max D median (p = 0.08)] were observed to be significantly associated with higher odds of being TRG 0 or 1. Tumor volume of interest (VOI) and ROI volume, ROI kurtosis mean and median, and VOI kurtosis mean and median were not significantly associated with TRG. CONCLUSION:Diffusivity derived from the baseline staging MRI, but not diffusion kurtosis or volumetric data, is associated with TRG and therefore shows promise as a potential imaging biomarker to predict the response to neoadjuvant chemotherapy in LARC. CLINICAL RELEVANCE STATEMENT:Diffusivity shows promise as a potential imaging biomarker to predict AJCC TRG following neoadjuvant CRT, which has implications for risk stratification. Patients with TRG 0/1 have 5-year disease-free survival (DFS) of 90-98%, as opposed to those who are TRG 2/3 with 5-year DFS of 68-73%.

OBJECTIVE:To provide a review of rare rectal tumors beyond adenocarcinoma. RESULTS:Rectal cancer is a common malignancy, both in the United States and abroad. In addition to adenocarcinoma, abdominal radiologists will encounter a variety of other less common rectal masses, both benign and malignant neoplasms as well as non-neoplastic mimickers. Familiarity with these conditions and their characteristic features on MRI is useful in clinical practice. In this article, a number of such conditions are discussed, with an emphasis on distinguishing features on MRI of the rectum. CONCLUSION:Familiarity with the MRI features of rare rectal tumors beyond adenocarcinoma, as well as a small number of non-neoplastic mimics, is important for abdominal imagers to make diagnostic differentials and to assist in treatment planning.

INTRODUCTION:As computational capabilities have advanced, radiologists and their collaborators have looked for novel ways to analyze diagnostic images. This has resulted in the development of radiomics and radiogenomics as new fields in medical imaging. Radiomics and radiogenomics may change the practice of medicine, particularly for patients with colorectal cancer. Radiomics corresponds to the extraction and analysis of numerous quantitative imaging features from conventional imaging modalities in correlation with several endpoints, including the prediction of pathology, genomics, therapeutic response, and clinical outcome. In radiogenomics, qualitative and/or quantitative imaging features are extracted and correlated with genetic profiles of the imaged tissue. Thus far, several studies have evaluated the use of radiomics and radiogenomics in patients with colorectal cancer; however, there are challenges to be overcome before its routine implementation including challenges related to sample size, model design and interpretability, and the lack of robust multicenter validation set. MATERIAL AND METHODS:In this article, we will review the concepts of radiomics and radiogenomics and their potential applications in rectal cancer. CONCLUSION:Radiologists should be aware of the basic concepts, benefits, pitfalls, and limitations of new radiomic and radiogenomics techniques to achieve a balanced interpretation of the results.

OBJECTIVE:To provide an overview of complete mesocolic excision, along with a review of the relevant vascular anatomy and locoregional staging concepts, for abdominal radiologists. RESULTS:Complete mesocolic excision (CME) with central vascular ligation (CVL) for colon cancer has emerged as a technique that has growing interest in surgical oncology. Specific anatomic considerations and patterns of nodal spread have thus gained clinical significance, and should be familiar to abdominal radiologists. This review article provides an overview of CME with CVL, and discusses some of the important anatomic considerations in patients with colon cancer that are relevant to radiologists. CONCLUSION:Knowledge of CME with CVL and the relevant anatomic and staging considerations is important for abdominal radiologists, as this surgical technique becomes increasingly utilized.

PURPOSE/OBJECTIVE:-mutant, IO-naive CRC. PATIENTS AND METHODS/METHODS:wild-type CRCs. RESULTS:-mutant CRC who received programmed death-1 or PD-L1 IOs, 11 (85%) achieved clinical benefit, defined as stable disease or partial response using Response Evaluation Criteria in Solid Tumors criteria. CONCLUSION/CONCLUSIONS:

IMPORTANCE:There has been significant recent interest in understanding the utility of quantitative imaging to delineate breast cancer intrinsic biological factors and therapeutic response. No clinically accepted biomarkers are as yet available for estimation of response to human epidermal growth factor receptor 2 (currently known as ERBB2, but referred to as HER2 in this study)-targeted therapy in breast cancer. OBJECTIVE:To determine whether imaging signatures on clinical breast magnetic resonance imaging (MRI) could noninvasively characterize HER2-positive tumor biological factors and estimate response to HER2-targeted neoadjuvant therapy. DESIGN, SETTING, AND PARTICIPANTS:In a retrospective diagnostic study encompassing 209 patients with breast cancer, textural imaging features extracted within the tumor and annular peritumoral tissue regions on MRI were examined as a means to identify increasingly granular breast cancer subgroups relevant to therapeutic approach and response. First, among a cohort of 117 patients who received an MRI prior to neoadjuvant chemotherapy (NAC) at a single institution from April 27, 2012, through September 4, 2015, imaging features that distinguished HER2+ tumors from other receptor subtypes were identified. Next, among a cohort of 42 patients with HER2+ breast cancers with available MRI and RNaseq data accumulated from a multicenter, preoperative clinical trial (BrUOG 211B), a signature of the response-associated HER2-enriched (HER2-E) molecular subtype within HER2+ tumors (n = 42) was identified. The association of this signature with pathologic complete response was explored in 2 patient cohorts from different institutions, where all patients received HER2-targeted NAC (n = 28, n = 50). Finally, the association between significant peritumoral features and lymphocyte distribution was explored in patients within the BrUOG 211B trial who had corresponding biopsy hematoxylin-eosin-stained slide images. Data analysis was conducted from January 15, 2017, to February 14, 2019. MAIN OUTCOMES AND MEASURES:Evaluation of imaging signatures by the area under the receiver operating characteristic curve (AUC) in identifying HER2+ molecular subtypes and distinguishing pathologic complete response (ypT0/is) to NAC with HER2-targeting. RESULTS:In the 209 patients included (mean [SD] age, 51.1 [11.7] years), features from the peritumoral regions better discriminated HER2-E tumors (maximum AUC, 0.85; 95% CI, 0.79-0.90; 9-12 mm from the tumor) compared with intratumoral features (AUC, 0.76; 95% CI, 0.69-0.84). A classifier combining peritumoral and intratumoral features identified the HER2-E subtype (AUC, 0.89; 95% CI, 0.84-0.93) and was significantly associated with response to HER2-targeted therapy in both validation cohorts (AUC, 0.80; 95% CI, 0.61-0.98 and AUC, 0.69; 95% CI, 0.53-0.84). Features from the 0- to 3-mm peritumoral region were significantly associated with the density of tumor-infiltrating lymphocytes (R2 = 0.57; 95% CI, 0.39-0.75; P = .002). CONCLUSIONS AND RELEVANCE:A combination of peritumoral and intratumoral characteristics appears to identify intrinsic molecular subtypes of HER2+ breast cancers from imaging, offering insights into immune response within the peritumoral environment and suggesting potential benefit for treatment guidance.

BACKGROUND:Previous authors have reported an increased incidence of acute pulmonary embolism (PE) in patients with sickle cell disease (SCD) based on retrospective analysis of ICD codes. It is unknown whether patients with SCD have higher rates of positive CT pulmonary angiogram (CTPA) in the emergency department (ED). METHODS:The institutional review board (IRB) approved this retrospective study; informed consent was waived. Between January 1, 2005 and May 31, 2015, 28 patients with SCD underwent a total of 78 CTPA studies in the ED. A control group of 75 non-SCD patients matched for age, gender and race underwent 78 consecutive CTPA studies in the emergency department. Modified Wells' (mWells') scores were calculated for each CTPA study performed. The studies for both groups were blind read by two fellowship trained body radiologists. Descriptive statistics were performed, with significance considered if p < 0.05. RESULTS:The rate of positive CT pulmonary angiogram in patients with SCD was 6.4% (5/78), compared with 12.8% (10/78) in non-SCD matched controls. There was no significant difference in the rate of positive CTPA (p = 0.277). There was also no difference in the mean mWells' score between the two groups (2.44 for SCD vs. 1.95 for controls, p = 0.120). CONCLUSION/CONCLUSIONS:SCD patients did not have a significantly different rate of acute PE when compared with matched controls undergoing CTPA in the ED.

OBJECTIVES/OBJECTIVE:To determine the appearance of rectal cancer on MRI after oxaliplatin-based chemotherapy (ICT) and make a preliminary assessment of MRI's value in predicting response to total neoadjuvant treatment (TNT). METHODS:In this IRB-approved, HIPAA-compliant, retrospective study between 1 January 2010-20 October 2014, pre- and post-ICT tumour T2 volume, relative T2 signal intensity (rT2SI), node size, signal intensity and border characteristics were assessed in 63 patients (65 tumours) by three readers. The strength of association between the reference standard of histopathological percent tumour response and tumour volume change, rT2SI and lymph node characteristics was assessed with Spearman's correlation coefficient and Wilcoxon's rank sum test. Cox regression was used to assess association between DFS and radiological measures. RESULTS:Change in T2 volume was not associated with TNT response. Change in rT2SI showed correlation with TNT response for one reader only using selective regions of interest (ROIs) and borderline correlation with response using total volume ROI. There was a significant negative correlation between baseline and post-ICT node size and TNT response (r = -0.25, p = 0.05; r = -0.35, p = 0.005, readers 1 and 2, respectively). Both baseline and post-induction median node sizes were significantly smaller in complete responders (p = 0.03, 0.001; readers 1 and 2, respectively). Change in largest baseline node size and decrease in post-ICT node signal heterogeneity were associated with 100% tumour response (p = 0.04). Nodal sizes at baseline and post-ICT MRI correlated with DFS. CONCLUSION/CONCLUSIONS:In patients undergoing post-ICT MRI, tumour volume did not correlate with TNT response, but decreased lymph node sizes were significantly associated with complete response to TNT as well as DFS. Relative T2SI showed borderline correlation with TNT response. KEY POINTS/CONCLUSIONS:• MRI-based tumour volume after induction chemotherapy and before chemoradiotherapy did not correlate with overall tumour response at the end of all treatment. • Lymph node size after induction chemotherapy and before chemoradiotherapy was strongly associated with complete pathological response after all treatment. • Lymph node sizes at baseline and post-induction chemotherapy MRI correlated with disease-free survival.