CONTEXT:Testicular adrenal rest tumors (TART) frequently develop and are the most common cause of male infertility in classic congenital adrenal hyperplasia (CAH). Little is known about the natural course. OBJECTIVE:We aimed to investigate age of onset and associated factors and characterize the sonographic natural history of TART in males with classic CAH followed prospectively from childhood to adulthood. METHODS:Longitudinal study of clinical and hormonal data and serial scrotal ultrasounds performed every 6 months during childhood and annually in adulthood. Survival analysis and longitudinal models were used to determine age of TART onset and factors associated with TART progression. RESULTS:Seven hundred eighty-three ultrasounds from 36 males were evaluated. Twenty-seven (75%) developed TART; the mean age of onset was 13.6 ± 4.9 years, with ∼22% risk before age 10. TART presence was associated with elevated ACTH, 17-hydroxyprogesterone, androstenedione, and plasma renin activity, younger age at diagnosis, salt-wasting (SW) phenotype, and null/In2G mutations. Multivariable analysis revealed SW phenotype [odds ratio (OR): 6.83, 95% confidence interval (CI) 2.36-19.77; P < .001], treatment with higher hydrocortisone dose equivalents (OR: 1.10, 95% CI 1.03-1.18; P = .006), and elevated ACTH (OR: 1.0011, 95% CI 1.0005-1.0017; P < .01) increased risk of TART at any given visit. Of 19 patients with TART at last visit, the hydrocortisone dose equivalent was 16.0 ± 7.9 mg/m2/day, lower than 21.3 ± 7.5 mg/m2/day observed in patients whose TARTs resolved. Serial sonograms showed a characteristic pattern of TART progression from a single hypoechoic nodule to multiple hypoechoic nodules to a single conglomerate mass near the mediastinum testis. CONCLUSION:TART formation in CAH is frequently found in prepubertal boys, with a characteristic pattern of development resulting in a proposed radiologic staging. Pediatric screening is recommended, especially in those with a SW phenotype/genotype.

RATIONALE AND OBJECTIVES:To develop a pathology-derived radiomics signature for detecting clinically significant prostate cancer (csPCa) and to evaluate its performance using lesion diameter-based simplified segmentations. MATERIALS AND METHODS:In this retrospective single-center study, 175 participants (120 radical prostatectomy cases; 55 controls) underwent biparametric MRI during 2013-2022. Whole-mount histopathology was registered to MRI using a patient-specific, mold-based 3D pipeline to generate lesion-level ground truth. Six radiologists from different institutions marked lesion diameters per Prostate Imaging Reporting & Data System (PI-RADS) v2.1, blinded to pathology; automated circular segmentations were generated from these measurements and expanded (±1 slice). Features (PyRadiomics) were preprocessed, filtered, and benchmarked via nested cross-validation. Recursive feature elimination produced a 10-feature pathology-derived radiomics signature. Models (Signature, prostate-specific antigen density [PSAD], PI-RADS, and their combinations) were trained/evaluated using a soft-voting ensemble (logistic regression, random forest, and XGBoost) with patient-level grouping; thresholds were optimized using Youden's J. DeLong's and McNemar's tests were used for model comparisons. RESULTS:PSAD+Signature achieved 0.75 area under the curve (AUC) and 68% (211/312) accuracy. PI-RADS+PSAD achieved 0.77 AUC and 74% (230/312) accuracy. Signature-only achieved 0.66 AUC and 62% (194/312) accuracy. A higher AUC for PSAD+Signature versus Signature (|ΔAUC|=0.093, p=0.012) and for the tripartite model versus Signature (|ΔAUC| = 0.11, p=0.007) was found. PSAD+Signature and PI-RADS+PSAD had similar accuracy (p=0.06). CONCLUSION:A histopathology-trained radiomics signature demonstrated moderate standalone performance for lesion-level csPCa detection. When combined with PSAD, diagnostic performance improved and approached that of PI-RADS+PSAD, which achieved the highest absolute accuracy. The PSAD+Signature framework offers a simplified, spatially localized approach that may complement existing PI-RADS-based assessment while maintaining low implementation complexity.

PURPOSE:To develop a multimodal deep learning-based AI algorithm and investigate its ability to predict BCR of PCa after radical prostatectomy (RP) using MRI and clinical data. METHODS:PCa patients (n = 311) underwent prostate MRI prior to RP between January 2008 and December 2018. For each patient, CAPRA-S was calculated. Quantitative imaging features were extracted using methods developed in a previous study. Test set results were assessed independently for each model in the study, using cross-validation of the training set to tune hyperparameters and select features. DeLong's test compared AUROC curve values, and log-rank tests compared BCR-free survival curves. RESULTS:Across all patients, the AUROC of the automated multimodal model was 0.74, compared to 0.66 for CAPRA-S. This model had the highest sensitivity at 75 %, with CAPRA-S at 37 %. BCR-free survival curves for the test set were generated for each model. Log-rank tests indicated each model differentiated between patient outcomes (p < 0.05). The automated multimodal model was the only model with p < 0.01. Focusing on intermediate risk patients (CAPRA-S scores 3-5), this automated model was the only model which maintained the ability to differentiate between outcomes (p < 0.01), while all other models and CAPRA-S failed to differentiate intermediate risk BCR outcomes (p > 0.05). CONCLUSION:Development of a multimodal model using quantitative imaging features and clinical covariates revealed that an automated multimodal AI approach most effectively predicts BCR in PCa patients. Based on AUROC and the ability to differentiate between BCR-free survival outcomes with statistical significance in intermediate risk patients, this model outperforms the gold standard postsurgical CAPRA-S risk scores.

BACKGROUND. Variability in prostate biparametric MRI (bpMRI) interpretation limits diagnostic reliability for prostate cancer (PCa). Artificial intelligence (AI) has the potential to reduce this variability and improve diagnostic accuracy. OBJECTIVE. The objective of this study was to evaluate the impact of a deep learning AI model on lesion- and patient-level rates of detection of PCa and clinically significant PCa (csPCa) and interreader agreement for bpMRI interpretations. METHODS. This retrospective, multireader, multicenter study used a balanced incomplete block design for MRI randomization. Six radiologists of varying experience interpreted bpMRI scans with and without AI assistance in alternating sessions. The reference standard for lesion-level detection for cases was whole-mount pathology after radical prostatectomy; for control patients, it was negative 12-core systematic biopsies. In all, 180 patients (120 in the case group and 60 in the control group) who underwent mpMRI and prostate biopsy or radical prostatectomy between January 2013 and December 2022 were included. Lesion-level sensitivity, PPV, and patient-level AUC for csPCa and PCa detection and interreader agreement for lesion-level PI-RADS scores and size measurements were assessed. RESULTS. AI assistance improved lesion-level PPV (PI-RADS ≥ 3: 77.2% [95% CI, 71.0-83.1%] vs 67.2% [95% CI, 61.1-72.2%] for csPCa; 80.9% [75.2-85.7%] vs 69.4% [95% CI, 63.4-74.1%] for PCa; both p < .001), reduced lesion-level sensitivity (PI-RADS ≥ 3: 44.4% [95% CI, 38.6-50.5%] vs 48.0% [95% CI, 42.0-54.2%] for csPCa; p = .01; 41.7% [95% CI, 37.0-47.4%] vs 44.9% [95% CI, 40.5-50.2%] for PCa; p = .01), and no difference in patient-level AUC (0.822 [95% CI, 0.768-0.866] vs 0.832 [95% CI, 0.787-0.868] for csPCa; p = .61; 0.833 [0.782-0.874] vs 0.835 [95% CI, 0.792-0.871] for PCa; p = .91). AI assistance improved interreader agreement for lesion-level PI-RADS scores (κ = 0.748 [95% CI, 0.701-0.796] vs 0.336 [95% CI, 0.288-0.381]; p < .001), lesion size measurements (coverage probability of 0.397 [95% CI, 0.376-0.419] vs 0.367 [95% CI, 0.349-0.383]; p < .001), and patient-level PI-RADS scores (κ = 0.704 [95% CI, 0.627-0.767] vs 0.507 [95% CI, 0.421-0.584]; p < .001). CONCLUSION. AI improved lesion-level PPV and interreader agreement with slightly lower lesion-level sensitivity. CLINICAL IMPACT. AI may enhance consistency and reduce false-positives in bpMRI interpretations. Further optimization is required to improve sensitivity without compromising specificity.

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. The smooth muscle content drives the imaging findings, which include increased attenuation on non-contrast-enhanced CT images, low T2 signal intensity, and avid enhancement. Rare histologic variants of AMLs include epithelioid AML (EAML) and AML with epithelial cysts. 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. ©RSNA, 2025 Supplemental material is available for this article.

Retrograde urethrography is useful in trauma to identify urethral disruptions and in evaluation of urethral strictures. Penile fracture is defined by disruption of the tunica albuginea, can be evaluated with ultrasound or MR imaging, and requires surgical management. Urethral diverticula should communicate with the urethra, demonstrated with postvoid MR imaging. Penile-scrotal abscess may be related to retrograde genitourinary infection, foreign body, fistula, or a gas forming organism. Squamous cell carcinoma is the most common penile malignancy, and MR imaging can be useful in local urethral and penile tumor staging.

Disclosure: S. Vaid: None. D. Bick: None. J. Marko: None. Z. Kuang: None. X. Li: None. A. Moon: None. A. Poch: None. P. Shin: None. Background: Men with classic CAH due to 21- hydroxylase deficiency (21OHD) commonly have subfertility secondary to poor disease control and/or testicular adrenal rest tumors (TART). Objective: Evaluate novel biomarkers including 11-oxyandrogens and standard biomarkers of disease control in relation to semen analysis and TART findings in males with classic CAH. Methods: A cross-sectional study was conducted at the National Institutes of Health Clinical Center as part of a Natural History Study (NCT00250159). Adult males underwent hormonal testing, semen analysis, and testicular ultrasound. Categorical and continuous data were compared between groups using Fisher’s exact test and Wilcoxon rank-sum test, respectively. Spearman rank correlation coefficients were calculated to assess the relationship between two continuous variables. Results: Thirty-eight men with classic CAH [28 (SW) (73.7%) and 10 (SV) (26.3%)] participated. 22(57.9%) had TART, 8(21.1%) had hypogonadotropic hypogonadism (HH), 7(18.4%) had azoospermia, and 5(13.2%) had oligospermia. Patients were receiving glucocorticoids at hydrocortisone equivalent dose mean ± SD: 30.4±16.1 mg/day. Patients with low vs normal total motile sperm count (TMSC) had higher median(IQR) 11-Ketotestosterone (11KT) [347(94.5-516) vs 67.4(11.0-107) ng/dL; P=0.006], 11-OHtestosterone (11OHT) [134(36.8-203) vs 22(3.6-35) ng/dL; P=0.004], 11-hydroxyandrostenedione (11OHA4) [908(125-2150) vs 207(21.5-365) ng/dL; P=0.03], 11KT:Testosterone (T) [1(0.1-1.3) vs 0.1(0-0.3); P=0.015], 11OHT:T [0.3(0.1-0.7) vs 0.04(0-0.1); P=0.01], higher estrone (E1) [123(68.5-189) vs 44.0(24.5-96.5) pg/mL; P=0.04], higher estradiol (E2) [25(21.6-36.5) vs 18.5(12.0-23.3) pg/mL; P=0.006] and higher E2:T [0.07 (0.06-0.13) vs 0.03(0.02-0.06); P=0.005]. Patients with TART vs without had lower median(IQR) sperm concentration [18(0-42) vs 47(34-72) 106/mL; P=0.010], lower percent motility % [54(0-66) vs 65(55-71); P=0.05], lower TMSC x 106/mL [24(0-70) vs 109(31-173); P=0.01], higher 11KT [180(27-376) vs 76.2(2.6-107) ng/dL; P=0.02], higher 11OHT [32.0(11-153) vs 23(0.5-38.6) ng/dL; P=0.03], higher 11KT:T [0.17(0.04-1) vs 0.14(0-0.3); P=0.03], and higher 11OHT:T [0.08(0.02-0.5) vs 0.04(0-0.08); P=0.03]. No differences were observed in 17 hydroxyprogesterone, androstenedione, FSH, T, A4:T and prevalence of HH. 11KT:T and 11OHT:T correlated inversely with sperm concentration: (rs=-0.48, P=0.003; rs=-0.49, P=0.002). Conclusion: 11-Oxyandrogens, 11KT:T and 11OHT:T, unlike the standard hormonal measurements of disease control, might serve as useful biomarkers in the evaluation of male infertility in CAH. Excess estrogens and the presence of TART also play a role. Presentation: Saturday, July 12, 2025

Rationale and Objectives: Extraprostatic extension (EPE) is well established as a significant predictor of prostate cancer aggression and recurrence. Accurate EPE assessment prior to radical prostatectomy can impact surgical approach. We aimed to utilize a deep learning-based AI workflow for automated EPE grading from prostate T2W MRI, ADC map, and High B DWI. Material and Methods: An expert genitourinary radiologist conducted prospective clinical assessments of MRI scans for 634 patients and assigned risk for EPE using a grading technique. The training set and held-out independent test set consisted of 507 patients and 127 patients, respectively. Existing deep-learning AI models for prostate organ and lesion segmentation were leveraged to extract area and distance features for random forest classification models. Model performance was evaluated using balanced accuracy, ROC AUCs for each EPE grade, as well as sensitivity, specificity, and accuracy compared to EPE on histopathology. Results: A balanced accuracy score of .390 +/- 0.078 was achieved using a lesion detection probability threshold of 0.45 and distance features. Using the test set, ROC AUCs for AI-assigned EPE grades 0-3 were 0.70, 0.65, 0.68, and 0.55 respectively. When using EPE >= 1 as the threshold for positive EPE, the model achieved a sensitivity of 0.67, specificity of 0.73, and accuracy of 0.72 compared to radiologist sensitivity of 0.81, specificity of 0.62, and accuracy of 0.66 using histopathology as the ground truth. Conclusion: Our AI workflow for assigning imaging-based EPE grades achieves an accuracy for predicting histologic EPE approaching that of physicians. This automated workflow has the potential to enhance physician decision-making for assessing the risk of EPE in patients undergoing treatment for prostate cancer due to its consistency and automation.

You have accessJournal of UrologySurgical Technology & Simulation: Artificial Intelligence III (PD36)1 May 2024PD36-02 EVALUATING AI ASSISTANCE IN PROSTATE BPMRI INTERPRETATION: A MULTI-READER STUDY David G. Gelikman, Enis C. Yilmaz, Stephanie A. Harmon, Julie Y. An, Sena Azamat, Yan Mee Law, Daniel J. A. Margolis, Jamie Marko, Valeria Panebianco, Sonia Gaur, Marco Bicchetti, Erich P. Huang, Sandeep Gurram, Joanna H. Shih, Peter L. Choyke, Bradford J. Wood, Peter A. Pinto, and Baris Turkbey David G. GelikmanDavid G. Gelikman , Enis C. YilmazEnis C. Yilmaz , Stephanie A. HarmonStephanie A. Harmon , Julie Y. AnJulie Y. An , Sena AzamatSena Azamat , Yan Mee LawYan Mee Law , Daniel J. A. MargolisDaniel J. A. Margolis , Jamie MarkoJamie Marko , Valeria PanebiancoValeria Panebianco , Sonia GaurSonia Gaur , Marco BicchettiMarco Bicchetti , Erich P. HuangErich P. Huang , Sandeep GurramSandeep Gurram , Joanna H. ShihJoanna H. Shih , Peter L. ChoykePeter L. Choyke , Bradford J. WoodBradford J. Wood , Peter A. PintoPeter A. Pinto , and Baris TurkbeyBaris Turkbey View All Author Informationhttps://doi.org/10.1097/01.JU.0001008916.72488.6a.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Interpretation of biparametric magnetic resonance imaging (bpMRI) for prostate cancer is subject to significant inter-reader variability. Artificial intelligence (AI) has the potential to enhance diagnostic accuracy and consistency among radiologists. This study aims to evaluate the effectiveness of a deep-learning AI model as a first reader in assisting radiologists of varied experience in interpreting prostate bpMRI. METHODS: Six radiologists (3 prostate-focused and 3 generalists) from different institutions each evaluated 120 prostate bpMRIs, of which 80 were from cases with pathologically confirmed prostate cancer and 40 were controls. In 60 of these scans, readers used AI assistance using a first-reader method in which they were only allowed to accept or reject lesions that were detected on AI prediction maps without reporting any additional lesions. The remaining 60 cases were read without AI. We conducted a patient-level analysis to compare sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for lesion detection at bpMRI with and without AI. Inter-reader agreement on lesion measurement and PI-RADS scores was also evaluated. RESULTS: The patient cohort had a median age of 63 years (IQR, 57-68) and prostate-specific antigen of 7.1 ng/mL (IQR, 5.1-10.8). AI assistance varied in effectiveness across all readers, with sensitivity ranging from 83%-93%, specificity from 16%-90%, and accuracy from 68%-87%. Without AI, the ranges were 82%-98% for sensitivity, 19%-81% for specificity, and 70%-87% for accuracy, Table 1. One prostate-focused reader improved accuracy by 10% with AI and one general radiologist showed a 5% improvement. AI-assistance resulted in a slight, non-significant reduction in the median absolute difference in largest lesion dimension measurements (1.56 mm with AI vs. 2.27 mm without; p=.373). The quadratic weighted Cohen's kappa indicated a slight improvement in PI-RADS score agreement from 0.438 to 0.459 with AI. CONCLUSIONS: AI assistance in the interpretation of bpMRI can improve accuracy for some readers. Despite a slight improvement in measurement agreement and PI-RADS scores, the varied impact of AI on different readers calls for further investigation into how AI tools can best complement radiologists in an effective and consistent manner. Source of Funding: Intramural Research Program of the NCI, NIH © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e792 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information David G. Gelikman More articles by this author Enis C. Yilmaz More articles by this author Stephanie A. Harmon More articles by this author Julie Y. An More articles by this author Sena Azamat More articles by this author Yan Mee Law More articles by this author Daniel J. A. Margolis More articles by this author Jamie Marko More articles by this author Valeria Panebianco More articles by this author Sonia Gaur More articles by this author Marco Bicchetti More articles by this author Erich P. Huang More articles by this author Sandeep Gurram More articles by this author Joanna H. Shih More articles by this author Peter L. Choyke More articles by this author Bradford J. Wood More articles by this author Peter A. Pinto More articles by this author Baris Turkbey More articles by this author Expand All Advertisement PDF downloadLoading ...

Abstract Disclosure: R.J. Auchus: Consulting Fee; Self; Corcept Therapeutics, H Lundbeck A/S, Quest Diagnostics, Sparrow Pharmaceuticals, Neurocrine Biosciences, Novo Nordisk, Recordati Rare Diseases, Diurnal, Xeris Pharmaceuticals. Research Investigator; Self; Corcept Therapeutics, Adrenas Therapeutics, Neurocrine Biosciences, Diurnal, Spruce Biosciences. P.J. Trainer: Employee; Self; Crinetics Pharmaceuticals, Inc.. Stock Owner; Self; Crinetics Pharmaceuticals, Inc.. K.J. Lucas: None. D. Bruera: None. J. Marko: Consulting Fee; Self; Crinetics Pharmaceuticals, Inc. A. Ayala: Employee; Self; Crinetics Pharmaceuticals, Inc.. Stock Owner; Self; Crinetics Pharmaceuticals, Inc. Y. Wu: Employee; Self; Crinetics Pharmaceuticals, Inc.. Stock Owner; Self; Crinetics Pharmaceuticals, Inc. C.T. Ferrara-Cook: Employee; Self; Crinetics Pharmaceuticals, Inc.. Stock Owner; Self; Crinetics Pharmaceuticals, Inc. E. De La Torre: Employee; Self; Crinetics Pharmaceuticals, Inc.. Stock Owner; Self; Crinetics Pharmaceuticals, Inc. A. Krasner: Employee; Self; Crinetics Pharmaceuticals, Inc.. Stock Owner; Self; Crinetics Pharmaceuticals, Inc. H. Lagast: Employee; Self; Crinetics Pharmaceuticals, Inc.. Stock Owner; Self; Crinetics Pharmaceuticals, Inc. R. Luo: Employee; Self; Crinetics Pharmaceuticals Inc.. Stock Owner; Self; Crinetics Pharmaceuticals Inc. T.A. Bachega: Research Investigator; Self; Spruce Biosciences. R.S. Struthers: Employee; Self; Crinetics Pharmaceuticals Inc.. Stock Owner; Self; Crinetics Pharmaceuticals Inc. S.F. Betz: Employee; Self; Crinetics Pharmaceuticals, Inc.. Stock Owner; Self; Crinetics Pharmaceuticals, Inc. U. Srirangalingam: Consulting Fee; Self; Diurnal, H Lundbeck A/S. Atumelnant (CRN04894) is a potent, once-daily, orally bioavailable, nonpeptide, first-in-class competitive and selective melanocortin type 2 receptor (MC2R, or ACTH receptor) antagonist being developed for the treatment of CAH and ACTH-Dependent Cushing’s Syndrome. Here we report initial results from an open-label, dose-finding phase 2 study of atumelnant in patients with CAH (NCT05907291). Patients (aged ≥18-75, ≥16 years in USA) with classical CAH on a stable dose of GC replacement for at least 6 months were enrolled and received once daily, oral atumelnant for 12 weeks. Key efficacy endpoints include early morning androstenedione (A4) and 17-hydroxyprogesterone (17-OHP) levels. Ten (10) participants have been enrolled and dosed. Data from the first 4 participants (3 females, median age 34 [range 25-42] years, methylprednisone 8 mg/day [hydrocortisone equivalent {HCeq} 32 mg/day, n=2], prednisone 10 mg/day [HCeq 40 mg/day, n=2]) who received 80 mg once daily, oral atumelnant are available. Baseline morning A4 levels in these participants ranged from 116 to 604 ng/dL (reference range [RR]: females 30-200 ng/dL; males 40-150 ng/dL). In these 4 participants, treatment with atumelnant resulted in rapid and profound A4 reductions within 2 weeks which were maintained for the duration of therapy. A4 reductions ranged from 74% to 99% throughout the study. There have been no instances of A4 being above the upper limit of normal on treatment with atumelnant. Baseline 17-OHP levels in these participants ranged from 4740 to 6905 ng/dL (RR: females <80 ng/dL [follicular], <285 ng/dL [luteal]; males <220 ng/dL). In these 4 participants, treatment with atumelnant resulted in rapid and profound 17-OHP reductions within 2 weeks which were maintained for the duration of therapy. 17-OHP reductions ranged from 68% to >99% throughout the study. Two female participants in this cohort menstruated for the first time in over 2 years. Mean baseline morning ACTH ranged from 155 to 1009 pg/mL (RR: 7.2-63 pg/mL), and while modest variations were seen with atumelnant, no consistent directional trend was observed. In conclusion, these data demonstrate rapid, profound, and sustained suppression of A4 and 17-OHP with 80 mg once daily, oral atumelnant. There were no serious or treatment-related adverse events and atumelnant was generally well-tolerated. This ongoing study will explore further the safety and efficacy of various doses of atumelnant. Support: Crinetics Pharmaceuticals, Inc. Presentation: 6/3/2024

Abstract Background Adenosine deaminase deficiency (ADA) is an autosomal recessive disorder leading to severe combined immunodeficiency (SCID). It is characterized patho-physiologically by intracellular accumulation of toxic products affecting lymphocytes. Other organ systems are known to be affected causing non-immune abnormalities. We aimed to conduct a cross sectional study to describe liver disease in autosomal recessive ADA-SCID. Methods Single center retrospective analysis of genetically confirmed autosomal recessive ADA-SCID was performed. Liver disease was defined as ≥1.5x the gender specific upper limit of normal (ULN; 33 IU/L for males and 25 IU/L for females) alanine aminotransferase (ALT) or moderate and severe increase in liver echogenicity on ultrasound. Results The cohort included 18 patients with 11 males. The median age was 11.5 (3.5–30.0 years) and median BMI percentile was 75.5 [36.75, 89.5]. All patients received enzyme replacement therapy at the time of evaluation. Seven (38%) and five (27%) patients had gene therapy (GT) and hematopoietic stem cell transplant (HSCT) in the past. Five patients had 1.5x ALT level more than 1.5x the U. Liver echogenicity was mild in 6 (33%), moderate in 2 (11%) and severe in 2 (11%) patients. All patients had normal Fibrosis-4 Index and Non-alcoholic fatty liver disease fibrosis biomarker scores indicating absence of advanced fibrosis in our cohort. Of 5 patients who had liver biopsies, steatohepatitis was noted in 3 patients (NAS score of 3,3,4). Discussion Non-immunologic manifestations of ADA-SCID have become more apparent in recent years as survival improved. We concluded that steatosis is the most common finding noted in our ADA-SCID cohort.

Chronic granulomatous disease (CGD) is a rare inborn error of immunity, resulting from a defect in nicotinamide adenine dinucleotide phosphate oxidation and decreased production of phagocyte reactive oxygen species. The main clinical manifestations are recurrent infections and chronic inflammatory disorders. Current approaches to management include antimicrobial prophylaxis and control of inflammatory complications. Hematopoietic stem cell transplantation or gene therapy can provide definitive treatment. Gastrointestinal and hepatic manifestations are common in CGD and include structural changes, dysmotility, CGD-associated inflammatory bowel disease, liver abscesses, and noncirrhotic portal hypertension. The findings can be heterogeneous, and the management is complex in light of the underlying immune dysfunction. This review describes the various clinical findings and the latest studies in management of gastrointestinal and hepatic manifestations in CGD, as well as the management experience at the National Institutes of Health.

RATIONALE AND OBJECTIVES:Prostate MRI quality is essential in guiding prostate biopsies. However, assessment of MRI quality is subjective with variation. Quality degradation sources exert varying impacts based on the sequence under consideration, such as T2W versus DWI. As a result, employing sequence-specific techniques for quality assessment could yield more advantageous outcomes. This study aims to develop an AI tool that offers a more consistent evaluation of T2W prostate MRI quality, efficiently identifying suboptimal scans while minimizing user bias. MATERIALS AND METHODS:This retrospective study included 1046 patients from three cohorts (ProstateX [n = 347], All-comer in-house [n = 602], enriched bad-quality MRI in-house [n = 97]) scanned between January 2011 and May 2022. An expert reader assigned T2W MRIs a quality score. A train-validation-test split of 70:15:15 was applied, ensuring equal distribution of MRI scanners and protocols across all partitions. T2W quality AI classification model was based on 3D DenseNet121 architecture using MONAI framework. In addition to multiclassification, binary classification was utilized (Classes 0/1 vs. 2). A score of 0 was given to scans considered non-diagnostic or unusable, a score of 1 was given to those with acceptable diagnostic quality with some usability but with some quality distortions present, and a score of 2 was given to those considered optimal diagnostic quality and usability. Partial occlusion sensitivity maps were generated for anatomical correlation. Three body radiologists assessed reproducibility within a subgroup of 60 test cases using weighted Cohen Kappa. RESULTS:The best validation multiclass accuracy of 77.1% (121/157) was achieved during training. In the test dataset, multiclassification accuracy was 73.9% (116/157), whereas binary accuracy was 84.7% (133/157). Sub-class sensitivity for binary quality distortion classification for class 0 was 100% (18/18), and sub-class specificity for T2W classification of absence/minimal quality distortions for class 2 was 90.5% (95/105). All three readers showed moderate to substantial agreement with ground truth (R1-R3 κ = 0.588, κ = 0.649, κ = 0.487, respectively), moderate to substantial agreement with each other (R1-R2 κ = 0.599, R1-R3 κ = 0.612, R2-R3 κ = 0.685), fair to moderate agreement with AI (R1-R3 κ = 0.445, κ = 0.410, κ = 0.292, respectively). AI showed substantial agreement with ground truth (κ = 0.704). 3D quality heatmap evaluation revealed that the most critical non-diagnostic quality imaging features from an AI perspective related to obscuration of the rectoprostatic space (94.4%, 17/18). CONCLUSION:The 3D AI model can assess T2W prostate MRI quality with moderate accuracy and translate whole sequence-level classification labels into 3D voxel-level quality heatmaps for interpretation. Image quality has a significant downstream impact on ruling out clinically significant cancers. AI may be able to help with reproducible identification of MRI sequences requiring re-acquisition with explainability.

Penile malignancy is the third most common male-specific genitourinary malignancy, with squamous cell carcinoma representing the most common histologic type. Squamous cell carcinoma is an epithelial malignancy, frequently developing from the mucosal surfaces of the foreskin, glans, and coronal sulcus and manifesting as a distal infiltrative or ulcerated mass. This typically occurs in men from the 6th to 8th decades of life, and risk factors include human papillomavirus, phimosis, presence of foreskin and poor hygiene, chronic inflammatory conditions such as lichen sclerosus, trauma, and smoking. Primary urethral malignancies including urothelial carcinoma and adenocarcinoma can occur but may lack this distal predilection. Sarcoma, melanoma, leukemia or lymphoma, and metastatic disease are less common sources of penile malignancy. Because of the sensitive nature of penile malignancies, there may be delays in seeking care and in subsequent diagnosis. Recently, the staging guidelines for penile cancer have been updated concurrently with a shift toward more penile-preserving therapies, which have led to a larger role of imaging in diagnosis, staging, and treatment planning for penile malignancies. A variety of imaging modalities may play a role in the identification and staging of penile malignancy, including an increased use of MRI for local staging of tumors, CT and PET/CT for identification of nodal and distant disease, and US for image-guided biopsy. The authors discuss an imaging approach to a spectrum of penile malignancies, with an emphasis on radiologic and pathologic correlation and how knowledge of normal tissue types and anatomic structures can aid in the diagnosis and staging of these tumors. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Importance Adrenalectomy is the definitive treatment for multiple adrenal abnormalities. Advances in technology and genomics and an improved understanding of adrenal pathophysiology have altered operative techniques and indications. Objective To develop evidence-based recommendations to enhance the appropriate, safe, and effective approaches to adrenalectomy. Evidence Review A multidisciplinary panel identified and investigated 7 categories of relevant clinical concern to practicing surgeons. Questions were structured in the framework Population, Intervention/Exposure, Comparison, and Outcome, and a guided review of medical literature from PubMed and/or Embase from 1980 to 2021 was performed. Recommendations were developed using Grading of Recommendations, Assessment, Development and Evaluation methodology and were discussed until consensus, and patient advocacy representation was included. Findings Patients with an adrenal incidentaloma 1 cm or larger should undergo biochemical testing and further imaging characterization. Adrenal protocol computed tomography (CT) should be used to stratify malignancy risk and concern for pheochromocytoma. Routine scheduled follow-up of a nonfunctional adrenal nodule with benign imaging characteristics and unenhanced CT with Hounsfield units less than 10 is not suggested. When unilateral disease is present, laparoscopic adrenalectomy is recommended for patients with primary aldosteronism or autonomous cortisol secretion. Patients with clinical and radiographic findings consistent with adrenocortical carcinoma should be treated at high-volume multidisciplinary centers to optimize outcomes, including, when possible, a complete R0 resection without tumor disruption, which may require en bloc radical resection. Selective or nonselective α blockade can be used to safely prepare patients for surgical resection of paraganglioma/pheochromocytoma. Empirical perioperative glucocorticoid replacement therapy is indicated for patients with overt Cushing syndrome, but for patients with mild autonomous cortisol secretion, postoperative day 1 morning cortisol or cosyntropin stimulation testing can be used to determine the need for glucocorticoid replacement therapy. When patient and tumor variables are appropriate, we recommend minimally invasive adrenalectomy over open adrenalectomy because of improved perioperative morbidity. Minimally invasive adrenalectomy can be achieved either via a retroperitoneal or transperitoneal approach depending on surgeon expertise, as well as tumor and patient characteristics. Conclusions and Relevance Twenty-six clinically relevant and evidence-based recommendations are provided to assist surgeons with perioperative adrenal care.

Background: Late-onset complications in X-linked agammaglobulinemia (XLA) are increasingly recognized. Nodular regenerative hyperplasia (NRH) has been reported in primary immunodeficiency but data in XLA are limited. Objectives: This study sought to describe NRH prevalence, associated features, and impact in patients with XLA. Methods: Medical records of all patients with XLA referred to the National Institutes of Health between October 1994 and June 2019 were reviewed. Liver biopsies were performed when clinically indicated. Patients were stratified into NRH+ or NRH- groups, according to their NRH biopsy status. Fisher exact test and Mann-Whitney test were used for statistical comparisons. Results: Records of 21 patients with XLA were reviewed, with a cumulative follow-up of 129 patient-years. Eight patients underwent >= 1 liver biopsy of whom 6 (29% of the National Institutes of Health XLA cohort) were NRH+. The median age at NRH diagnosis was 20 years (range, 17-31). Among patients who had liver biopsies, alkaline phosphatase levels were only increased in patients who were NRH+ (P = .04). Persistently low platelet count (<100,000 per mu L for >6 months), mildly to highly elevated hepatic venous pressure gradient and either hepatomegaly and/or splenomegaly were present in all patients who were NRH+. In opposition, persistently low platelet counts were not seen in patients who were NRH-, and hepatosplenomegaly was observed in only 1 patient who was NRH-. Hepatic venous pressure gradient was normal in the only patient tested who was NRH-. All-cause mortality was higher among patients who were NRH+ (5 of 6, 83%) than in the rest of the cohort (1 of 15, 7% among patients who were NRH- and who were classified as unknown; P = .002). Conclusions: NRH is an underreported, frequent, and severe complication in XLA, which is associated with increased morbidity and mortality.

Background:Giant cell arteritis (GCA) and Takayasu’s arteritis (TAK) are the two main forms of large-vessel vasculitis (LVV). Although angiography is essential to detect vascular disease in patients with LVV, there is limited prospective data characterizing change in arterial lesions over time, and factors that predict angiographic change remain unknown.Objectives:The objectives of this study were to: 1) describe longitudinal change in angiographic studies in patients with GCA and TAK and 2) determine whether FDG-PET activity predicts angiographic progression of disease.Methods:Patients with GCA or TAK were recruited into a prospective, observational cohort. All patients underwent baseline magnetic resonance (MR) or computed tomography (CT) angiography and a follow-up study (same modality) ≥6 months after baseline per a standardized imaging protocol. For patients who had multiple angiograms, the baseline and most recent images were compared. Arterial lesions, defined as stenosis, occlusion, or aneurysm, were evaluated by visual inspection in 4 segments of the aorta and 13 branch arteries by a single reader blinded to clinical status. On follow up angiography, the development of new lesions in these same territories was recorded, and existing lesions were characterized as improved, worsened, or unchanged by visual inspection, with confirmation by an independent reader.All patients underwent FDG-PET on the same date as angiography. Qualitative assessment of FDG uptake was performed in each corresponding arterial territory evaluated by angiography. Active vasculitis was defined as greater FDG uptake in the arterial wall compared to the liver by visual inspection.Results:At the baseline visit, there were 248 arterial lesions (21%) out of 1162 arterial territories evaluated from 70 patients with LVV (TAK=38; GCA=32). Baseline characteristics were as follows: Age [TAK=29.5 years (18.4-39.5), GCA=69.6 years (60.7-75.5)], Female gender [TAK=30 patients (79%), GCA=23 patients (72%)], Disease duration [TAK=2.2 years (0.6-5.5), GCA=0.7 years (0.1-2.6)], Active clinical disease [TAK=17 patients (45%), GCA=20 patients (63%)].Over 1.6 years (1.0-2.7) of median follow-up, no angiographic change was observed in 1,132 (97%) arterial territories. New lesions developed in 8 arterial territories, exclusively in 5 patients with TAK. Arterial lesions improved in 16 territories (GCA = 7, TAK = 9) and worsened in 6 territories (GCA = 1, TAK = 5). Patients with angiographic improvement were initially imaged earlier in the disease course compared to patients with new/worsening lesions (median 1.1 vs 16.4 months, p=0.09). Patients with angiographic improvement had significantly lower acute phase reactants at follow-up compared to patients with new/worsening arterial lesions [median ESR 3.0 (2.0-15.0) vs. 27.0 (7.3-39) mm/h, p<0.01; median CRP 0.7 (0.3-1.4) vs. 6.1 (3.1-19.6) mg/L, p<0.01]. Seventy-nine percent of patients with new/worsening arterial lesions had received increased treatment over the follow-up interval compared to 100% patients with improved arterial lesions, p=0.09.FDG-PET activity was evaluated in 1091/1162 (94%) of corresponding arterial territories. PET activity in an arterial territory at baseline was significantly associated with change in that arterial territory (either new/worsening or improvement) on follow-up angiography (p<0.01) (FIGURE 1). PET activity had a sensitivity of 80% and specificity of 74% for predicting change in arterial lesions. Most arterial territories without PET activity at baseline remained unchanged over time by angiography, yielding a negative predictive value of 99%. (FIGURE 1).Conclusion:Development of new arterial lesions is infrequent in LVV. Change in arterial lesions is dynamic, and improvement can occur. FDG-PET activity predicts change in angiographic lesions, and lack of PET activity is strongly associated with stable angiographic disease. These data may inform guideline recommendations for imaging monitoring in LVV.Figure 1.Disclosure of Interests:None declared