Faculty Bibliography

Vulvar cancer is an uncommon gynecologic tumor and one of several human papillomavirus-associated malignancies. Squamous cell carcinoma is the most prevalent histologic subtype of vulvar cancer, accounting for the majority of cases. Imaging plays an important role in managing vulvar cancer. At initial diagnosis, imaging is useful to assess the size and extent of primary tumor and to evaluate the status of inguinofemoral lymph nodes. If recurrent disease is suspected, imaging is essential to demonstrate local extent of tumor and to identify lymph node and distant metastases. In this publication, we summarize the recent literature and describe the panel's recommendations about the appropriate use of imaging for various phases of patient management including initial staging, surveillance, and restaging of vulvar cancer. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

There have been many publications detailing imaging features of malignant transformation of intraductal papillary mucinous neoplasms (IPMN), management and recommendations for imaging follow-up of diagnosed or presumed IPMN. However, there is no consensus on several practical aspects of imaging IPMN that could serve as a clinical guide for radiologists and enable future data mining for research. These aspects include how to measure IPMN, define reporting terminology, standardize reporting and unify guidelines for surveillance. The Society of Abdominal Radiology (SAR) created multiple Disease-Focused Panels (DFP) comprised multidisciplinary panel members who focus on a particular disease, with the goal to develop ways for radiologists to improve patient care, education, and research. DFP members met to identify the current controversies and limitations of imaging pancreatic IPMN. This paper aims to provide a practical review of the key imaging characteristics of IPMN for trainees and practicing radiologists, to guide uniformity of performance and interpretation of surveillance imaging studies, and to improve communication with clinicians by providing a lexicon and reporting template based on the experience of the SAR-DFP panel members.

Oral cavity cancer has a low 5-y survival rate, but outcomes improve when the disease is detected early. Cytology is a less invasive method to assess oral potentially malignant disorders relative to the gold-standard scalpel biopsy and histopathology. In this report, we aimed to determine the utility of cytological signatures, including nuclear F-actin cell phenotypes, for classifying the entire spectrum of oral epithelial dysplasia and oral squamous cell carcinoma. We enrolled subjects with oral potentially malignant disorders, subjects with previously diagnosed malignant lesions, and healthy volunteers without lesions and obtained brush cytology specimens and matched scalpel biopsies from 486 subjects. Histopathological assessment of the scalpel biopsy specimens classified lesions into 6 categories. Brush cytology specimens were analyzed by machine learning classifiers trained to identify relevant cytological features. Multimodal diagnostic models were developed using cytology results, lesion characteristics, and risk factors. Squamous cells with nuclear F-actin staining were associated with early disease (i.e., lower proportions in benign lesions than in more severe lesions), whereas small round parabasal-like cells and leukocytes were associated with late disease (i.e., higher proportions in severe dysplasia and carcinoma than in less severe lesions). Lesions with the impression of oral lichen planus were unlikely to be either dysplastic or malignant. Cytological features substantially improved upon lesion appearance and risk factors in predicting squamous cell carcinoma. Diagnostic models accurately discriminated early and late disease with AUCs (95% CI) of 0.82 (0.77 to 0.87) and 0.93 (0.88 to 0.97), respectively. The cytological features identified here have the potential to improve screening and surveillance of the entire spectrum of oral potentially malignant disorders in multiple care settings.

To date, there is little consensus on the role of pelvic imaging in assessing local disease extent during initial staging in patients with endometrial carcinoma, with practices differing widely across centers. However, when pretreatment assessment of local tumor extent is indicated, MRI is the preferred imaging modality. Preoperative imaging of endometrial carcinoma can define the extent of disease and indicate the need for subspecialist referral in the presence of deep myometrial invasion, cervical extension, or suspected lymphadenopathy. If distant metastatic disease is clinically suspected, preoperative assessment with cross-sectional imaging or PET/CT may be performed. However, most patients with low-grade disease are at low risk of lymph node and distant metastases. Thus, this group may not require a routine pretreatment evaluation for distant metastases. Recurrence rates in patients with endometrial carcinoma are infrequent. Therefore, radiologic evaluation is typically used only to investigate suspicion of recurrent disease due to symptoms or physical examination and not for routine surveillance after treatment. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

OBJECTIVE:Patients increasingly access radiology results through digital portals. We compared patient satisfaction and understanding of radiology results when received through an electronic patient portal versus direct communication from providers. METHODS:tests and logistic regression. RESULTS:Of 1,005 survey respondents, 87.8% (882 of 1,005) reported having received their imaging test results, with 486 (48.4%) first being notified through the patient portal and 396 (39.4%) via direct provider communication. Patients reported high levels of satisfaction with timing regardless of whether they first received the results through the patient portal or through direct provider communication (88.8%-89.9%). Patients who first received their results through the patient portal reported a lesser degree of perceived understanding than those who first received their results through direct provider communication (26.7% versus 47.8%; P < .001). Patients were less likely to report clear understanding for advanced imaging (CT or MRI) than ultrasound or x-rays (29.3% versus 40.3% versus 38.2%, respectively; P = .02). Patient characteristics showed no association with understanding in multivariable analysis. CONCLUSION/CONCLUSIONS:As online portal release of radiology results to patients becomes commonplace, efforts may be warranted to improve patient experience when first receiving their radiology results online.

BACKGROUND:The COVID-19 pandemic has resulted in significant morbidity and mortality, with large numbers of patients requiring intensive care threatening to overwhelm healthcare systems globally. There is an urgent need for a COVID-19 disease severity assessment that can assist in patient triage and resource allocation for patients at risk for severe disease. OBJECTIVE:The goal of this study was to develop, validate, and scale a clinical decision support system and mobile app to assist in COVID-19 severity assessment, management, and care. METHODS:Model training data from 701 patients with COVID-19 were collected across practices within the Family Health Centers network at New York University Langone Health. A two-tiered model was developed. Tier 1 uses easily available, non-laboratory data to help determine whether biomarker-based testing and/or hospitalization is necessary. Tier 2 predicts probability of mortality using biomarker measurements (CRP, PCT, D-dimer) and age. Both Tier 1 and Tier 2 models were validated using two external datasets from hospitals in Wuhan, China comprising 160 and 375 patients, respectively. RESULTS:All biomarkers were measured at significantly higher levels in patients that died vs. those that were not hospitalized or discharged (P < .001). The Tier 1 and Tier 2 internal validation had AUC (95% confidence interval) of 0.79 (0.74-0.84) and 0.95 (0.92-0.98), respectively. The Tier 1 and Tier 2 external validation had AUCs of 0.79 (0.74-0.84) and 0.97 (0.95-0.99), respectively. CONCLUSIONS:Our results demonstrate validity of the clinical decision support system and mobile app, which are now ready to assist healthcare providers in making evidence-based decisions in managing COVID-19 patient care. The deployment of these new capabilities has potential for immediate impact in community clinics, sites whereby application of such tools could lead to improvements in patient outcomes and cost containment. CLINICALTRIAL/UNASSIGNED/:

Patients with renal cell carcinoma may develop metastases after radical nephrectomy, and therefore monitoring with imaging for recurrent or metastatic disease is critical. Imaging varies with specific suspected site of disease. Computed tomography/MRI of the abdomen and pelvis are mainstay modalities. Osseous and central nervous system imaging is reserved for symptomatic patients. Radiologic reporting is evolving to reflect effects of systemic therapy on lesion morphology. Nuclear medicine studies compliment routine imaging as newer agents are evaluated for more accurate tumor staging. Imaging research aims to fill gaps in treatment selection and monitoring of treatment response in metastatic renal cell carcinoma.

OBJECTIVES/OBJECTIVE:To perform a systematic review on apparent diffusion coefficient (ADC) values of renal tumor subtypes and meta-analysis on the diagnostic performance of ADC for differentiation of localized clear cell renal cell carcinoma (ccRCC) from other renal tumor types. METHODS:Medline, Embase, and the Cochrane Library databases were searched for studies published until May 1, 2019, that reported ADC values of renal tumors. Methodological quality was evaluated. For the meta-analysis on diagnostic test accuracy of ADC for differentiation of ccRCC from other renal lesions, we applied a bivariate random-effects model and compared two subgroups of ADC measurement with vs. without cystic and necrotic areas. RESULTS:We included 48 studies (2588 lesions) in the systematic review and 13 studies (1126 lesions) in the meta-analysis. There was no significant difference in ADC of renal parenchyma using b values of 0-800 vs. 0-1000 (p = 0.08). ADC measured on selected portions (sADC) excluding cystic and necrotic areas differed significantly from whole-lesion ADC (wADC) (p = 0.002). Compared to ccRCC, minimal-fat angiomyolipoma, papillary RCC, and chromophobe RCC showed significantly lower sADC while oncocytoma exhibited higher sADC. Summary estimates of sensitivity and specificity to differentiate ccRCC from other tumors were 80% (95% CI, 0.76-0.88) and 78% (95% CI, 0.64-0.89), respectively, for sADC and 77% (95% CI, 0.59-0.90) and 77% (95% CI, 0.69-0.86) for wADC. sADC offered a higher area under the receiver operating characteristic curve than wADC (0.852 vs. 0.785, p = 0.02). CONCLUSIONS:ADC values of kidney tumors that exclude cystic or necrotic areas more accurately differentiate ccRCC from other renal tumor types than whole-lesion ADC values. KEY POINTS/CONCLUSIONS:• Selective ADC of renal tumors, excluding cystic and necrotic areas, provides better discriminatory ability than whole-lesion ADC to differentiate clear cell RCC from other renal lesions, with area under the receiver operating characteristic curve (AUC) of 0.852 vs. 0.785, respectively (p = 0.02). • Selective ADC of renal masses provides moderate sensitivity and specificity of 80% and 78%, respectively, for differentiation of clear cell renal cell carcinoma (RCC) from papillary RCC, chromophobe RCC, oncocytoma, and minimal-fat angiomyolipoma. • Selective ADC excluding cystic and necrotic areas are preferable to whole-lesion ADC as an additional tool to multiphasic MRI to differentiate clear cell RCC from other renal lesions whether the highest b value is 800 or 1000.

SARS-CoV-2 is the virus that causes coronavirus disease (COVID-19) which has reached pandemic levels resulting in significant morbidity and mortality affecting every inhabited continent. The large number of patients requiring intensive care threatens to overwhelm healthcare systems globally. Likewise, there is a compelling need for a COVID-19 disease severity test to prioritize care and resources for patients at elevated risk of mortality. Here, an integrated point-of-care COVID-19 Severity Score and clinical decision support system is presented using biomarker measurements of C-reactive protein (CRP), N-terminus pro B type natriuretic peptide (NT-proBNP), myoglobin (MYO), D-dimer, procalcitonin (PCT), creatine kinase-myocardial band (CK-MB), and cardiac troponin I (cTnI). The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality. The COVID-19 Severity Score was trained and evaluated using data from 160 hospitalized COVID-19 patients from Wuhan, China. Our analysis finds that COVID-19 Severity Scores were significantly higher for the group that died versus the group that was discharged with median (interquartile range) scores of 59 (40-83) and 9 (6-17), respectively, and area under the curve of 0.94 (95% CI 0.89-0.99). Although this analysis represents patients with cardiac comorbidities (hypertension), the inclusion of biomarkers from other pathophysiologies implicated in COVID-19 (e.g., D-dimer for thrombotic events, CRP for infection or inflammation, and PCT for bacterial co-infection and sepsis) may improve future predictions for a more general population. These promising initial models pave the way for a point-of-care COVID-19 Severity Score system to impact patient care after further validation with externally collected clinical data. Clinical decision support tools for COVID-19 have strong potential to empower healthcare providers to save lives by prioritizing critical care in patients at high risk for adverse outcomes.