Faculty Bibliography

PURPOSE/OBJECTIVE:Ovarian-Adnexal Reporting and Data System (O-RADS) MRI uses a 5-point scale to establish malignancy risk in sonographically-indeterminate adnexal masses. The management of O-RADS MRI score 4 lesions is challenging, as the prevalence of malignancy is widely variable (5-90%). We assessed imaging features that may sub-stratify O-RADS MRI 4 lesions into malignant and benign subgroups. METHOD/METHODS:Retrospective single-institution study of women with O-RADS MRI score of 4 adnexal masses between April 2021-August 2022. Imaging findings were assessed independently by 2 radiologists according to the O-RADS lexicon white paper. MRI and clinical findingswere compared between malignant and benign adnexal masses, and inter-reader agreement was calculated. RESULTS:Seventy-four women (median age 52 years, IQR 36-61) were included. On pathology, 41 (55.4%) adnexal masses were malignant. Patients with malignant masses were younger (p = 0.02) with higher CA-125 levels (p = 0.03). Size of solid tissue was greater in malignant masses (p = 0.01-0.04). Papillary projections and larger solid portion were more common in malignant lesions; irregular septations and predominantly solid composition were more frequent in benign lesions (p < 0.01). Solid tissue of malignant lesions was more often hyperintense on T2-weighted and diffusion-weighted imaging (p ≤ 0.03). Other imaging findings were not significantly different (p = 0.09-0.77). Inter-reader agreement was excellent-good for most features (ICC = 0. 662-0.950; k = 0. 650-0.860). CONCLUSION/CONCLUSIONS:Various MRI and clinical features differed between malignant and benign O-RADS MRI score 4 adnexal masses. O-RADS MRI 4 lesions may be sub-stratified (high vs low risk) based on solid tissue characteristics and CA-125 levels.

OBJECTIVES/OBJECTIVE:The aims of this study were to determine whether ComBat harmonization improves multiclass radiomics-based tissue classification in technically heterogeneous MRI data sets and to compare the performances of 2 ComBat variants. MATERIALS AND METHODS/METHODS:One hundred patients who had undergone T1-weighted 3D gradient echo Dixon MRI (2 scanners/vendors; 50 patients each) were retrospectively included. Volumes of interest (2.5 cm3) were placed in 3 disease-free tissues with visually similar appearance on T1 Dixon water images: liver, spleen, and paraspinal muscle. Gray-level histogram (GLH), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and gray-level size-zone matrix (GLSZM) radiomic features were extracted. Tissue classification was performed on pooled data from the 2 centers (1) without harmonization, (2) after ComBat harmonization with empirical Bayes estimation (ComBat-B), and (3) after ComBat harmonization without empirical Bayes estimation (ComBat-NB). Linear discriminant analysis with leave-one-out cross-validation was used to distinguish among the 3 tissue types, using all available radiomic features as input. In addition, a multilayer perceptron neural network with a random 70%:30% split into training and test data sets was used for the same task, but separately for each radiomic feature category. RESULTS:Linear discriminant analysis-based mean tissue classification accuracies were 52.3% for unharmonized, 66.3% for ComBat-B harmonized, and 92.7% for ComBat-NB harmonized data. For multilayer perceptron neural network, mean classification accuracies for unharmonized, ComBat-B-harmonized, and ComBat-NB-harmonized test data were as follows: 46.8%, 55.1%, and 57.5% for GLH; 42.0%, 65.3%, and 71.0% for GLCM; 45.3%, 78.3%, and 78.0% for GLRLM; and 48.1%, 81.1%, and 89.4% for GLSZM. Accuracies were significantly higher for both ComBat-B- and ComBat-NB-harmonized data than for unharmonized data for all feature categories (at P = 0.005, respectively). For GLCM (P = 0.001) and GLSZM (P = 0.005), ComBat-NB harmonization provided slightly higher accuracies than ComBat-B harmonization. CONCLUSIONS:ComBat harmonization may be useful for multicenter MRI radiomics studies with nonbinary classification tasks. The degree of improvement by ComBat may vary among radiomic feature categories, among classifiers, and among ComBat variants.

PURPOSE/OBJECTIVE:To compare the interreader agreement of a novel quality score, called the Radiological Image Quality Score (RI-QUAL), to a slighly modified version of the existing Prostate Imaging Quality (mPI-QUAL) score for magnetic resonance imaging (MRI) of the prostate. METHODS:A total of 43 consecutive scans were evaluated by two subspecialized radiologists who assigned scores using both the RI-QUAL and mPI-QUAL methods. The interreader agreement was analyzed using three statistical methods: concordance correlation coefficient (CCC), intraclass correlation coefficient (ICC), and Cohen's kappa. Time needed to arrive at a quality judgment was measured and compared using the Wilcoxon signed rank test. RESULTS:The interreader agreement for RI-QUAL and mPI-QUAL scores was comparable, as evidenced by the high CCC (0.76 vs. 0.77, p = 0.93), ICC (0.86 vs. 0.87, p = 0.93), and moderate Cohen's kappa (0.61 vs. 0.64, p = 0.85) values. Moreover, RI-QUAL assessment was faster than mPI-QUAL (19 vs. 40 s, p = 0.001). CONCLUSION/CONCLUSIONS:RI-QUAL is a new quality score that has comparable interreader agreement to the mPI-QUAL score, but with the potential to be applied to different MRI protocols and even different modalities. Like PI-QUAL, RI-QUAL may also facilitate communication about quality to referring physicians, as it provides a standardized and easily interpretable score. Further studies are warranted to validate the usefulness of RI-QUAL in larger patient cohorts and for other imaging modalities.

PURPOSE:Neoadjuvant chemotherapy (NAC) has proven survival benefits for patients with invasive urothelial carcinoma of the bladder, yet its role for upper tract urothelial carcinoma (UTUC) remains undefined. We conducted a multicenter, single-arm, phase II trial of NAC with gemcitabine and split-dose cisplatin (GC) for patients with high-risk UTUC before extirpative surgery to evaluate response, survival, and tolerability. METHODS:Eligible patients with defined criteria for high-risk localized UTUC received four cycles of split-dose GC before surgical resection and lymph node dissection. The primary study end point was rate of pathologic response (defined as < ypT2N0). Secondary end points included progression-free survival (PFS), overall survival (OS), and safety and tolerability. RESULTS:< .001). CONCLUSION:NAC with split-dose GC for high-risk UTUC is a well-tolerated, effective therapy demonstrating evidence of pathologic response that is associated with favorable survival outcomes. Given that these survival outcomes are superior to historical series, these data support the use of NAC as a standard of care for high-risk UTUC, and split-dose GC is a viable option for NAC.

OBJECTIVE:To evaluate MRI features of sarcomatoid renal cell carcinoma (RCC) and their association with survival. METHODS:This retrospective single-center study included 59 patients with sarcomatoid RCC who underwent MRI before nephrectomy during July 2003-December 2019. Three radiologists reviewed MRI findings of tumor size, non-enhancing areas, lymphadenopathy, and volume (and percentage) of T2 low signal intensity areas (T2LIA). Clinicopathological factors of age, gender, ethnicity, baseline metastatic status, pathological details (subtype and extent of sarcomatoid differentiation), treatment type, and follow-up were extracted. Survival was estimated using Kaplan-Meier method and Cox proportional-hazards regression model was used to identify factors associated with survival. RESULTS:Forty-one males and eighteen females (median age 62 years; interquartile range 51-68) were included. T2LIAs were present in 43 (72.9%) patients. At univariate analysis, clinicopathological factors associated with shorter survival were: greater tumor size (> 10 cm; HR [hazard ratio] = 2.44, 95% CI 1.15-5.21; p = 0.02), metastatic lymph nodes (present; HR = 2.10, 95% CI 1.01-4.37; p = 0.04), extent of sarcomatoid differentiation (non-focal; HR = 3.30, 95% CI 1.55-7.01; p < 0.01), subtypes other than clear cell, papillary, or chromophobe (HR = 3.25, 95% CI 1.28-8.20; p = 0.01), and metastasis at baseline (HR = 5.04, 95% CI 2.40-10.59; p < 0.01). MRI features associated with shorter survival were: lymphadenopathy (HR = 2.24, 95% CI 1.16-4.71; p = 0.01) and volume of T2LIA (> 3.2 mL, HR = 4.22, 95% CI 1.92-9.29); p < 0.01). At multivariate analysis, metastatic disease (HR = 6.89, 95% CI 2.79-16.97; p < 0.01), other subtypes (HR = 9.50, 95% CI 2.81-32.13; p < 0.01), and greater volume of T2LIA (HR = 2.51, 95% CI 1.04-6.05; p = 0.04) remained independently associated with worse survival. CONCLUSION/CONCLUSIONS:T2LIAs were present in approximately two thirds of sarcomatoid RCCs. Volume of T2LIA along with clinicopathological factors were associated with survival.

PURPOSE:To explore ways to improve O-RADS MRI scoring for fat-containing adnexal masses, by investigating methods for quantifying solid tissue volume and fat distribution and evaluating their associations with malignancy. METHODS:), and fat distribution. Wilcoxon test, Fisher-exact test, and ROC curve analysis were performed. Reference standard was pathology or follow-up > 24 months. RESULTS:(R1, ≥ 1.2 cm; R2, ≥ 1.0 cm) yielded sensitivity and specificity of 0.72 and 0.93 (R1) and 0.76 and 0.95 (R2). Among immature teratomas, 85.7% displayed scattered fat. CONCLUSION:Overall size, size of (any or non-Rokitansky-nodule) solid tissue, and fat distribution differed between benign and malignant fat-containing adnexal masses. Incorporating these would constitute simple and practical approaches to refining O-RADS MRI scoring.

PURPOSE/OBJECTIVE:To evaluate computed tomography (CT) findings in patients with ovarian cancer presenting to a comprehensive cancer center's urgent care unit with acute abdominal symptoms. METHODS:This retrospective study included consecutive patients with ovarian cancer who underwent abdominal CT at a comprehensive cancer center's urgent care unit between January 1, 2018, and January 14, 2020, due to acute abdominal symptoms. Two abdominal radiologists reviewed the abdominal CT reports, categorizing imaging findings as follows: (a) no new or acute finding, (b) new or increased bowel or gastric obstruction, (c) new or increased ascites, (d) new or increased peritoneal carcinomatosis, (e) new or increased nonperitoneal metastases, (f) new inflammatory or infectious changes, (g) new or increased hydronephrosis, (h) new or increased biliary dilatation, (i) new vascular complications, or (j) new bowel perforation. RESULTS:A total of 200 patients (mean age, 59 years; range, 22-87) underwent a total of 259 abdominal CT scans, of which 217/259 (83.8%) scans were found to have new or increased findings. A total of 115/259 (44.4%) scans had only one finding while 102/259 (39.4%) scans had 2 or more findings. Altogether, 382 new or increased findings were detected: findings were most commonly related to bowel or gastric obstruction (92/382, 24.1%) with small bowel obstruction being the most common finding (80/382, 20.9%); ascites (78/382, 20.4%); peritoneal carcinomatosis (62/382, 16.2%); and nonperitoneal metastases (62/382, 16.2%). Inflammatory or infectious findings accounted for 30/382 (7.9%) findings. CONCLUSION/CONCLUSIONS:Most patients with ovarian cancer presenting with acute abdominal had relevant positive findings on abdominal CT, with small bowel obstruction being the most common finding.

Our purpose was to determine whether ComBat harmonization improves ¹⁸F-FDG PET radiomics-based tissue classification in pooled PET/MRI and PET/CT datasets. Methods: Two hundred patients who had undergone ¹⁸F-FDG PET/MRI (2 scanners and vendors; 50 patients each) or PET/CT (2 scanners and vendors; 50 patients each) were retrospectively included. Gray-level histogram, gray-level cooccurrence matrix, gray-level run-length matrix, gray-level size-zone matrix, and neighborhood gray-tone difference matrix radiomic features were calculated for volumes of interest in the disease-free liver, spleen, and bone marrow. For individual feature classes and a multiclass radiomic signature, tissue was classified on ComBat-harmonized and unharmonized pooled data, using a multilayer perceptron neural network. Results: Median accuracies in training and validation datasets were 69.5% and 68.3% (harmonized), respectively, versus 59.5% and 58.9% (unharmonized), respectively, for gray-level histogram; 92.1% and 86.1% (harmonized), respectively, versus 53.6% and 50.0% (unharmonized), respectively, for gray-level cooccurrence matrix; 84.8% and 82.8% (harmonized), respectively, versus 62.4% and 58.3% (unharmonized), respectively, for gray-level run-length matrix; 87.6% and 85.6% (harmonized), respectively, versus 56.2% and 52.8% (unharmonized), respectively, for gray-level size-zone matrix; 79.5% and 77.2% (harmonized), respectively, versus 54.8% and 53.9% (unharmonized), respectively, for neighborhood gray-tone difference matrix; and 86.9% and 84.4% (harmonized), respectively, versus 62.9% and 58.3% (unharmonized), respectively, for radiomic signature. Conclusion: ComBat harmonization may be useful for multicenter ¹⁸F-FDG PET radiomics studies using pooled PET/MRI and PET/CT data.

PURPOSE:To evaluate whether a custom programmatic workflow manager reduces reporting turnaround times (TATs) from a body oncologic imaging workflow at a tertiary cancer center. METHODS:A custom software program was developed and implemented in the programming language R. Other aspects of the workflow were left unchanged. TATs were measured over a 12-month period (June-May). The same prior 12-month period served as a historical control. Median TATs of magnetic resonance imaging (MRI) and computed tomography (CT) examinations were compared with a Wilcoxon test. A chi-square test was used to compare the numbers of examinations reported within 24 hours and after 72 hours as well as the proportions of examinations assigned according to individual radiologist preferences. RESULTS:< .001). CONCLUSION:The custom workflow management software program significantly decreased MRI and CT report TATs.

There has been an increasing role of magnetic resonance imaging (MRI) in the management of prostate cancer. MRI already plays an essential role in the detection and staging, with the introduction of functional MRI sequences. Recent advancements in radiomics and artificial intelligence are being tested to potentially improve detection, assessment of aggressiveness, and provide usefulness as a prognostic marker. MRI can improve pretreatment risk stratification and therefore selection of and follow-up of patients for active surveillance. MRI can also assist in guiding targeted biopsy, treatment planning and follow-up after treatment to assess local recurrence. MRI has gained importance in the evaluation of metastatic disease with emerging technology including whole-body MRI and integrated positron emission tomography/MRI, allowing for not only better detection but also quantification. The main goal of this article is to review the most recent advances on MRI in prostate cancer and provide insights into its potential clinical roles from the radiologist's perspective. In each of the sections, specific roles of MRI tailored to each clinical setting are discussed along with its strengths and weakness including already established material related to MRI and the introduction of recent advancements on MRI.