Mitochondrial matrix RTN4IP1/OPA10 is an oxidoreductase for coenzyme Q synthesis.

Targeting proximity-labeling enzymes to specific cellular locations is a viable strategy for profiling subcellular proteomes. Here, we generated transgenic mice (MAX-Tg) expressing a mitochondrial matrix-targeted ascorbate peroxidase. Comparative analysis of matrix proteomes from the muscle tissues showed differential enrichment of mitochondrial proteins. We found that reticulon 4-interacting protein 1 (RTN4IP1), also known as optic atrophy-10, is enriched in the mitochondrial matrix of muscle tissues and is an NADPH oxidoreductase. Interactome analysis and in vitro enzymatic assays revealed an essential role for RTN4IP1 in coenzyme Q (CoQ) biosynthesis by regulating the O-methylation activity of COQ3. Rtn4ip1-knockout myoblasts had markedly decreased CoQ9 levels and impaired cellular respiration. Furthermore, muscle-specific knockdown of dRtn4ip1 in flies resulted in impaired muscle function, which was reversed by dietary supplementation with soluble CoQ. Collectively, these results demonstrate that RTN4IP1 is a mitochondrial NAD(P)H oxidoreductase essential for supporting mitochondrial respiration activity in the muscle tissue.

MR imaging findings of ovarian lymphoma: differentiation from other solid ovarian tumors.

PURPOSE: To evaluate magnetic resonance imaging (MRI) findings for distinguishing ovarian lymphomas from other solid ovarian tumors. METHODS: This retrospective multicenter study included 14 women (median age, 46.5 years; range, 26-81 years) with surgically proven ovarian lymphoma and 28 women with solid ovarian tumors other than lymphoma. We conducted a subjective image analysis of factors including laterality, shape, composition, T2 signal intensity (SI), heterogeneity, diffusion restriction, enhancement, and presence of peripheral follicles. A generalized estimating equation was used to identify MRI findings that could be used to distinguish ovarian lymphomas from other solid ovarian tumors. Diagnostic performance of the identified MRI findings was assessed using the area under the receiver-operating characteristic curve (AUC). RESULTS: Ovarian lymphoma more frequently showed homogeneous high SI on T2-weighted imaging (81.8% vs. 19.4%, P < 0.001) and peripheral ovarian follicles (40.9% vs. 8.3%, P = 0.01) than other ovarian solid tumors did. Bilaterality, shape, size, diffusion restriction, and enhancement did not differ between the two groups (P > 0.05 for all). Homogeneous high SI on T2-weighted imaging was the only independent MRI finding (OR = 15.19; 95% CI 3.15-73.33; P = 0.001) in the multivariable analysis. Homogeneous high SI on T2-weighted imaging yielded an AUC of 0.82 with a sensitivity of 81.8% and specificity of 80.6% in distinguishing ovarian lymphomas from other solid ovarian tumors. CONCLUSION: Homogeneous high signal intensity on T2-weighted imaging was helpful in distinguishing ovarian lymphomas from other solid ovarian tumors. Peripheral ovarian follicles might be an additional clue that suggests a diagnosis of ovarian lymphoma.

Prediction of acute rejection in renal allografts using shear-wave dispersion slope.

OBJECTIVES: To evaluate the role of shear-wave dispersion slope for predicting renal allograft dysfunction. METHODS: We retrospectively reviewed 128 kidney transplant recipients (median age, 55 years [interquartile range, 43-62 years]; male, 68) who underwent biopsy for allograft evaluation from November 2022 to February 2023. Cortex and renal sinus fat stiffness and shear-wave dispersion slope were obtained at shear-wave elastography (SWE). Cortex-to-sinus stiffness ratio (SR) and dispersion slope ratio (DSR)-related clinical and pathologic factors were evaluated using multivariable linear regression analysis. We conducted univariate and multivariate analyses for multiparametric ultrasound (US) parameters for identifying acute rejection and calculated the area under the receiver operating curve (AUC) values. RESULTS: Of 128 patients, 31 (24.2%) demonstrated acute rejection. The SR value did not differ between patient groups (1.21 vs. 1.20, p = 0.47). Patients with acute rejection demonstrated a higher DSR than those without rejection (1.4 vs. 1.21, p < 0.01). Interstitial fibrosis and tubular atrophy grade (IFTA; coefficient, 0.11/grade; p = 0.04) and renal transplant and biopsy interval (coefficient, 0.00007/day; p = 0.03) were SR determinant factors, whereas only IFTA grade (coefficient, 0.10/grade; p = 0.01) for DSR. Multivariate analysis revealed mean resistive index (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.02-1.14, p = 0.01) and DSR value (OR 16.0, 95% CI 3.0-85.8, p = 0.001) as independent factors for predicting acute rejection. An AUC of 0.74 for detecting acute rejection was achieved by combining the resistive index and DSR value. CONCLUSION: Shear-wave dispersion slope obtained at SWE may help identify renal allograft dysfunction. CLINICAL RELEVANCE STATEMENT: Acute rejection in renal allografts is a major cause of allograft failure, but noninvasive diagnosis is a challenge. Shear-wave dispersion slope can identify acute rejection non-invasively. KEY POINTS: • The interstitial fibrosis and tubular atrophy grade was a determinant factor for stiffness ratio and shear-wave dispersion slope ratio between cortex and renal sinus fat. • Shear-wave dispersion slope ratio between cortex and renal sinus fat could identify acute rejection in renal allografts. • A shear-wave dispersion slope has a potential to reduce unnecessary renal biopsy for evaluating renal allografts.

[Renal Biopsy]. / ì‹ ìž¥ì˜ 조직 검사.

The extent of renal biopsy indication is being widened because of the increasing incidence of incidental renal masses; the increasing treatment options for renal cell carcinoma, including ablation therapy and novel targeted treatment; and the increasing incidence of kidney transplantation. However, percutaneous renal biopsy is technically difficult, particularly for beginners, because the skin-to-organ distance is relatively longer than those associated with other organs. In the present review, we will discuss the indications, technical considerations, efficacy, and complications of renal biopsy. Furthermore, we share practical tips of renal biopsy through many examples to help radiologists perform renal biopsy safely and effectively in various situations.

Contrast-Enhanced MRI in Women with Endometrial Cancer: Dynamic Versus Single-Phase Acquisitions.

Background: The 2019 European Society of Urogenital Radiology (ESUR) guidelines for endometrial cancer recommend performing either dynamic contrast-enhanced magnetic resonance imaging (CE MRI) or single-phase CE MRI. However, no study has directly compared these options. Therefore, this study compared dynamic versus single-phase CE MRI for the evaluation of myometrial invasion in women with endometrial cancer. Methods: This retrospective, single-institution comparative study was conducted among women with surgically proven endometrial cancer, including 30 consecutive women with single-phase CE MRI and 30 age- and pathologic stage-matched women with dynamic CE MRI. Three readers independently compared dynamic and single-phase CE MRI in terms of the tumor-myometrium signal intensity (SI) difference ratio, depth of myometrial invasion, image quality, and image number. Pathologic findings served as a reference standard for the depth of myometrial invasion. Results: The estimated mean SI difference ratios of dynamic CE MRI and single-phase CE MRI fell within an equivalence margin of 0.05 (90% confidence intervals [CIs] = [-0.0497 to -0.0165], [-0.0226 to -0.0403], and [-0.0429 to -0.0433], respectively, for readers A, B, and C). The area under the receiver operating characteristic curve for the detection of deep myometrial invasion was not significantly different between the acquisitions (P = .3315, P = .3345, and P = .8593, respectively). Single-phase CE MRI showed significantly better image quality than dynamic CE MRI (P = .0143, P = .0042, and P = .0066, respectively), while the median number of images for dynamic CE MRI was 2.4 times higher than that for single-phase CE MRI. Conclusion: Single-phase acquisition may be a better option for CE MRI in women with endometrial cancer than dynamic acquisition.

Diagnostic performance of MRI for prediction of recurrent prostate cancer after high-intensity focused ultrasound: a systematic review and meta-analysis.

Purpose: This article aims to evaluate the pooled diagnostic performance control MRI for prediction of recurrent prostate cancer (PCa) after high-intensity focused ultrasound (HIFU). Materials and methods: MEDLINE, EMBASE, and Cochrane library databases up to December 31, 2021, were searched. We included studies providing 2×2 contingency table for diagnostic performance of MRI in predicting recurrent PCa after HIFU, using control biopsy as reference standard. The quality of the included studies was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Sensitivity and specificity were pooled and displayed in a summary receiver operating characteristics (SROC) plot. Meta-regression analysis using clinically relevant covariates was performed for the causes of heterogeneity. Results: Nineteen studies (703 patients) were included. All included studies satisfied at least four of the seven QUADAS-2 domains. Pooled sensitivity was 0.81 (95% CI 0.72-0.90) with specificity of 0.91 (95% CI 0.86-0.96), with area under the SROC curve of 0.81. Larger studies including more than 50 patients showed relatively poor sensitivity (0.68 vs. 0.84) and specificity (0.75 vs. 0.93). The diagnostic performance of studies reporting higher nadir serum prostate-specific antigen levels (>1 ng/mL) after HIFU was inferior, and differed significantly in sensitivity (0.54 vs. 0.78) rather than specificity (0.85 vs. 0.91). Conclusions: Although MRI showed adequate diagnostic performance in predicting PCa recurrence after HIFU, these results may have been exaggerated.

Tumor contact length with bladder wall provides effective risk stratification for lesions with a VIRADS score of 2-3.

OBJECTIVES: To evaluate the diagnostic performance of the tumor contact length (TCL) in the prediction of MIBC (muscle-invasive bladder cancer) in lesions corresponding to the vesical imaging-reporting and data system (VIRADS) score 2-3. METHODS: This is a single institution, retrospective study targeting 191 consecutive patients assigned of VIRADS score 2-3, who had pre-transurethral resection MRI from July 2019 to September 2021. Logistic regression analyses were performed to determine meaningful predictors of MIBC for this score group, and a nomogram was plotted with those variables. The diagnostic performance of each predictor was compared at predefined thresholds (VIRADS score 3 and TCL 3 cm) using the generalized linear model and ROC analysis. RESULTS: Both VIRADS score and TCL remained independent predictors of MIBC for this score group (odds ratio 7.3 for VIRADS score, and 1.3 for TCL, p < 0.01 for both). The contribution of TCL to the probability of MIBC in the nomogram was greater than that of the VIRADS score. VIRADS score had a sensitivity of 0.54 (14/26), specificity of 0.92 (203/221), and diagnostic accuracy of 0.88 (217/247), and TCL showed a sensitivity of 0.89 (23/26), specificity of 0.95 (209/221), and diagnostic accuracy of 0.94 (232/247). The difference in sensitivity (p = 0.03) and accuracy (p = 0.04) was statistically significant. The AUC was also significantly wider for TCL than for VIRADS (0.97 vs. 0.73, p < 0.01). CONCLUSION: A simple index, TCL, may be helpful in further risk stratification for MIBC in patients with a score of VIRADS 2-3. CLINICAL RELEVANCE STATEMENT: For bladder cancer patients with insufficient qualitative evidence of muscle layer invasion using VIRADS categorization, TCL, a simple quantitative indicator defined as the curvilinear contact length between the bladder wall and the tumor, may be helpful in risk stratification. KEY POINTS: • Even when only lesions with score 2-3 were targeted, VIRADS was still a meaningful indicator of MIBC. • With a predefined threshold of 3 cm applied, TCL outperformed VIRADS in the score 2-3 group, in predicting MIBC. • A longer TCL for a lesion with a VIRADS score 2 may warrant an additional warning for MIBC, whereas a shorter TCL for a lesion with a score 3 may indicate a lower risk of MIBC.

Accuracy of actual stage prediction using Vesical Imaging Reporting and Data System (VI-RADS) before radical cystectomy for urothelial carcinoma in SUPER-UC-Cx.

Background: Previous studies using the Vesical Imaging Reporting and Data System (VI-RADS) to predict muscle-invasive bladder cancer (MIBC) had some limitations. Most studies were performed with transurethral resection of bladder tumor (TUR-BT) specimens with few samples. This study was conducted to address these shortcomings and confirm the accuracy of VI-RADS for bladder cancer. Methods: This study used data from the Seoul National University Prospectively Enrolled Registry for Urothelial Cancer-Radical Cystectomy (SUPER-UC-Cx). Patients who underwent multiparametric magnetic resonance imaging (mp-MRI) before radical cystectomy (RC) were included in this study between March 2020 and March 2022. All images were reported by radiologists and reviewed by two urologists. The patient characteristics and clinical information were blinded during the review. The performance of qualitative and quantitative variables in predicting muscle layer invasion or perivesical fat infiltration was verified by receiver operating characteristic (ROC) curve analysis. Results: Of 208 patients, 182 (87.5%) underwent mp-MRI before RC. Twenty-three patients with non-urothelial carcinoma, inappropriate MRI scans, and bladder filling were excluded. Cut-off for muscle invasion, VI-RADS score of 4 had the highest area under the curve (AUC) (sensitivity 0.84; specificity 0.93; accuracy 0.90; positive predictive value (PPV) 0.84; negative predictive value (NPV) 0.93, and AUC 0.88). Cut-off for perivesical fat invasion and VI-RADS score of 5 had the highest AUC (sensitivity, 0.78; specificity, 0.99; accuracy, 0.95; PPV, 0.96; NPV, 0.95; and AUC, 0.89). Conclusions: VI-RADS is a good predictor of bladder cancer staging before RC and is especially helpful in predicting muscle invasion and perivesical fat infiltration.

Fasudil alleviates the vascular endothelial dysfunction and several phenotypes of Fabry disease.

Fabry disease (FD), a lysosomal storage disorder, is caused by defective α-galactosidase (GLA) activity, which results in the accumulation of globotriaosylceramide (Gb3) in endothelial cells and leads to life-threatening complications such as left ventricular hypertrophy (LVH), renal failure, and stroke. Enzyme replacement therapy (ERT) results in Gb3 clearance; however, because of a short half-life in the body and the high immunogenicity of FD patients, ERT has a limited therapeutic effect, particularly in patients with late-onset disease or progressive complications. Because vascular endothelial cells (VECs) derived from FD-induced pluripotent stem cells display increased thrombospondin-1 (TSP1) expression and enhanced SMAD2 signaling, we screened for chemical compounds that could downregulate TSP1 and SMAD2 signaling. Fasudil reduced the levels of p-SMAD2 and TSP1 in FD-VECs and increased the expression of angiogenic factors. Furthermore, fasudil downregulated the endothelial-to-mesenchymal transition (EndMT) and mitochondrial function of FD-VECs. Oral administration of fasudil to FD mice alleviated several FD phenotypes, including LVH, renal fibrosis, anhidrosis, and heat insensitivity. Our findings demonstrate that fasudil is a novel candidate for FD therapy.

Fully automatic volume measurement of the adrenal gland on CT using deep learning to classify adrenal hyperplasia.

OBJECTIVES: To develop a fully automated deep learning model for adrenal segmentation and to evaluate its performance in classifying adrenal hyperplasia. METHODS: This retrospective study evaluated automated adrenal segmentation in 308 abdominal CT scans from 48 patients with adrenal hyperplasia and 260 patients with normal glands from 2010 to 2021 (mean age, 42 years; 156 women). The dataset was split into training, validation, and test sets at a ratio of 6:2:2. Contrast-enhanced CT images and manually drawn adrenal gland masks were used to develop a U-Net-based segmentation model. Predicted adrenal volumes were obtained by fivefold splitting of the dataset without overlapping the test set. Adrenal volumes and anthropometric parameters (height, weight, and sex) were utilized to develop an algorithm to classify adrenal hyperplasia, using multilayer perceptron, support vector classification, a random forest classifier, and a decision tree classifier. To measure the performance of the developed model, the dice coefficient and intraclass correlation coefficient (ICC) were used for segmentation, and area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were used for classification. RESULTS: The model for segmenting adrenal glands achieved a Dice coefficient of 0.7009 for 308 cases and an ICC of 0.91 (95% CI, 0.90-0.93) for adrenal volume. The models for classifying hyperplasia had the following results: AUC, 0.98-0.99; accuracy, 0.948-0.961; sensitivity, 0.750-0.813; and specificity, 0.973-1.000. CONCLUSION: The proposed segmentation algorithm can accurately segment the adrenal glands on CT scans and may help clinicians identify possible cases of adrenal hyperplasia. KEY POINTS: • A deep learning segmentation method can accurately segment the adrenal gland, which is a small organ, on CT scans. • The machine learning algorithm to classify adrenal hyperplasia using adrenal volume and anthropometric parameters (height, weight, and sex) showed good performance. • The proposed segmentation algorithm may help clinicians identify possible cases of adrenal hyperplasia.

CT-based preoperative risk assessment of prolonged urine leak in patients undergoing partial nephrectomy.

OBJECTIVES: This study aims to evaluate risk factors of prolonged urine leak following partial nephrectomy (PN) to identify objective imaging characteristics on preoperative CT. METHODS: A total of 865 patients who underwent PN and had preoperative CT and postoperative imaging were included. We set a twofold size-matched control group without urine leak, with all tumors located ≤ 4 mm to the collecting system to identify imaging parameters that increase the risk of urine leak other than tumor size and location. Four CT parameters that show the relationship of the tumor and collecting system, namely, curvilinear border length, protruding distance, margin at the interface, and pelvicalyceal contact, were analyzed. Multivariate logistic regression analyses were performed to identify significant predictors of urine leak. The diagnostic performance of the significant parameters was evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: Fifty-three of 865 patients (6.1%) demonstrated urine leak. Compared with the control group, urine leak group showed longer curvilinear border length, longer protruding distance, frequent non-smooth contact interface, and frequent direct pelvicalyceal contact (p < 0.05 for all). In the multivariate analysis, pelvicalyceal contact was the independent predictor of urine leak (OR = 2.62; 95% C.I 1.02-6.63). Combining four CT parameters, an AUC of 0.70 with a sensitivity of 58.5% and a specificity of 79.2% for identifying urine leak after PN could be obtained. CONCLUSIONS: The four CT features that describe the relationship between the tumor and collecting system might be useful for evaluating the risk of urine leak before PN. KEY POINTS: • Four CT parameters (curvilinear border length, protruding distance, margin at the interface, and pelvicalyceal contact) were significantly associated with postoperative urine leak after partial nephrectomy. • A comprehensive preoperative imaging evaluation of the relationship between the tumor and renal sinus may help in selecting the optimal surgical options and afford better patient counseling of complication risk.

Diagnostic value of multiparametric MRI in detecting residual or recurrent prostate cancer after high-intensity focused ultrasound.

PURPOSE: To evaluate the diagnostic performance of follow-up multiparametric MRI for prediction of recurrent prostate cancer after high-intensity focused ultrasound (HIFU), and to find other, if any, clinical or radiological predictors. MATERIALS AND METHODS: Post-HIFU MRIs of 110 consecutive patients who underwent follow-up biopsies between August 2019 and April 2021 were retrospectively analyzed and the likelihood of recurrence was assessed on a five-point Likert scale by two board-certified uroradiologists. Diagnostic performance of the Likert scale assigned to the post-HIFU MRI was assessed using the follow-up biopsy results as a reference standard. Among the clinical and radiological variables, predictors of the recurrence were examined through logistic regression. RESULTS: In per-patient and per-sector analyses, Likert scale on post-HIFU MRI showed a sensitivity and specificity of 0.37 and 0.97, and 0.42 and 0.87, respectively, in predicting recurrence. Two patients with high suspicion on MRI required additional treatment to regain biochemical control despite negative biopsies. High suspicion on post-HIFU MRI (odds ratio = 1.74; p < 0.01), and more cancer-positive cores on initial biopsy (odds ratio = 1.25; p = 0.03) were independent predictors of recurrence. CONCLUSION: Albeit with low sensitivity, high suspicion on post-HIFU MRI may be clinically important because of its high specificity, especially when considering the possibility of sampling error in biopsies. Patients with a high number of cancer-positive cores at diagnosis should avoid HIFU as they have an increased risk of recurrence.

Prediction of treatment response following ethanol sclerotherapy of renal cysts by computed tomography.

OBJECTIVES: To investigate predictive factors of treatment response following ethanol sclerotherapy of large renal cysts via computed tomography (CT). METHODS: Retrospective study reviewed 71 patients (61.0 ± 13.2 years; M:F = 32:39) who underwent pretreatment CT and were treated with sclerotherapy of a large (> 5 cm) renal cyst (mean volume: 279.8 cc) using 99% ethanol from January 2010 to February 2019. Patients were followed up at least two times, short-term (defined as < 6 months, median 2.1 months) and long-term (defined as > 1 year, median 15.5 months), via ultrasound or CT. Suboptimal response was defined as the volume of residual cyst > 20 mL in each follow-up. Predictive variables of radiologic findings and radiomics features were analyzed using logistic regression analysis. RESULTS: Suboptimal response rates were 33.8% and 18.3% at short-term and long-term follow-ups, respectively. In radiologic findings, patients with suboptimal response in the short-term follow-up showed a more frequent estimated cyst volume ≥ 270 mL (OR 14.8, 95% CI 3.9-55.9, p < 0.001) and sinus protrusion (OR 7.0, 95% CI 1.7-28.5, p = 0.007). Cyst volume ≥ 270 mL was also associated with suboptimal response in the long-term follow-up (OR 4.6, 95% CI 1.3-16.9, p = 0.021). When radiomics features were combined, the area under the curve increased from 0.83 to 0.86 and from 0.68 to 0.82 to predict suboptimal response in short-term and long-term follow-ups, respectively. CONCLUSION: Greater estimated volume, sinus protrusion, and radiomics features of the cysts in pretreatment CT can help predict suboptimal response of renal cyst after sclerotherapy.

Differentiating renal epithelioid angiomyolipoma from clear cell carcinoma: using a radiomics model combined with CT imaging characteristics.

PURPOSE: This study aims to assess the computed tomography (CT) findings of renal epithelioid angiomyolipoma (EAML) and develop a radiomics-based model for differentiating EAMLs and clear cell renal cell carcinomas (RCCs). METHOD: This two-center retrospective study included 28 histologically confirmed EAMLs and 56 size-matched clear cell RCCs with preoperative three-phase kidney CTs. We conducted subjective image analysis to determine the CT parameters that can distinguish EAMLs from clear cell RCCs. Training and test sets were divided by chronological order of CT scans, and radiomics model was built using ten selected features among radiomics and CT features. The diagnostic performance of the radiomics model was compared with that of the three radiologists using the area under the receiver-operating characteristic curve (AUC). RESULTS: The mean size of the EAMLs was 6.2 ± 5.0 cm. On multivariate analysis, a snowman or ice cream cone tumor shape (OR 16.3; 95% CI 1.7-156.9, P = 0.02) and lower tumor-to-cortex (TOC) enhancement ratio in the corticomedullary phase (OR 33.4; 95% CI 5.7-197, P < 0.001) were significant independent factors for identifying EAMLs. The diagnostic performance of the radiomics model (AUC 0.89) was similar to those of genitourinary radiologists (AUC 0.78 and 0.81, P > 0.05) and superior to that of a third-year resident (AUC 0.63, P = 0.04). CONCLUSIONS: A snowman or ice cream cone shape and lower TOC ratio were more closely associated with EAMLs than with clear cell RCCs. A CT radiomics model was useful for differentiating EAMLs from clear cell RCCs with better diagnostic performance than an inexperienced radiologist.

Impact of no residual disease on postoperative computed tomography on survival in patients with optimally debulked advanced high-grade serous ovarian cancer during upfront surgery.

OBJECTIVE: We sought to investigate the impact of size of residual tumors as determined by postoperative computed tomography (CT) on survival of patients with advanced, high-grade serous ovarian carcinoma (HGSC) who achieved residual disease less than 1 cm after primary debulking surgery (PDS). METHODS: We collected data of patients with stage III HGSC who had residual tumor less than 1 cm after PDS between 2013 and 2018. Surgeon-assessed residual disease during surgery was defined as sR0 (no gross residual) or sR1 (gross residual <1 cm), and radiologist-assessed residual disease on postoperative CT was defined as rR0 (no evidence of disease) or rRany (existing residual disease). All patients were classified into the following groups: sR0/rR0, sR1/rR0, sR0/rRany, and sR1/rRany. RESULTS: A total of 436 patients was placed into the sR0/rR0 (n = 187, 42.9%), sR1/rR0 (n = 59, 13.5%), sR0/rRany (n = 79, 18.1%), or sR1/rRany group (n = 111, 25.5%). Discrepancies between surgical and radiological assessments were recorded for 176 patients (40.4%) including 38 cases of sR1/rRany group with discordant residual tumor location indicated between two methods. During multivariate analysis, patients with ascites on preoperative CT, sR0/rRany group inclusion, and sR1/rRany group inclusion showed unfavorable progression-free and overall survival. CONCLUSIONS: The incorporation of surgical and radiological evaluations for determining the size of residual tumors was more accurate than surgical evaluation only for predicting survival among patients with advanced ovarian cancer who underwent PDS to residual disease less than 1 cm.

Adrenal Morphology as an Indicator of Long-Term Disease Control in Adults with Classic 21-Hydroxylase Deficiency.

BACKGROUND: Monitoring adults with classical 21-hydroxylase deficiency (21OHD) is challenging due to variation in clinical and laboratory settings. Moreover, guidelines for adrenal imaging in 21OHD are not yet available. We evaluated the relationship between adrenal morphology and disease control status in classical 21OHD. METHODS: This retrospective, cross-sectional study included 90 adult 21OHD patients and 270 age- and sex-matched healthy controls. We assessed adrenal volume, width, and tumor presence using abdominal computed tomography and evaluated correlations of adrenal volume and width with hormonal status. We investigated the diagnostic performance of adrenal volume and width for identifying well-controlled status in 21OHD patients (17α-hydroxyprogesterone [17-OHP] <10 ng/mL). RESULTS: The adrenal morphology of 21OHD patients showed hypertrophy (45.6%), normal size (42.2%), and hypotrophy (12.2%). Adrenal tumors were detected in 12 patients (13.3%). The adrenal volume and width of 21OHD patients were significantly larger than those of controls (18.2±12.2 mL vs. 7.1±2.0 mL, 4.7±1.9 mm vs. 3.3±0.5 mm, P<0.001 for both). The 17-OHP and androstenedione levels were highest in patients with adrenal hypertrophy, followed by those with normal adrenal glands and adrenal hypotrophy (P<0.05 for both). Adrenal volume and width correlated positively with adrenocorticotropic hormone, 17-OHP, 11ß-hydroxytestosterone, progesterone sulfate, and dehydroepiandrosterone sulfate in both sexes (r=0.33-0.95, P<0.05 for all). For identifying well-controlled patients, the optimal cut-off values of adrenal volume and width were 10.7 mL and 4 mm, respectively (area under the curve, 0.82-0.88; P<0.001 for both). CONCLUSION: Adrenal volume and width may be reliable quantitative parameters for monitoring patients with classical 21OHD.

Prognostic role of computed tomography-based, artificial intelligence-driven waist skeletal muscle volume in uterine endometrial carcinoma.

OBJECTIVES: To investigate the impact of computed tomography (CT)-based, artificial intelligence-driven waist skeletal muscle volume on survival outcomes in patients with endometrial cancer. METHODS: We retrospectively identified endometrial cancer patients who received primary surgical treatment between 2014 and 2018 and whose pre-treatment CT scans were available (n = 385). Using an artificial intelligence-based tool, the skeletal muscle area (cm2) at the third lumbar vertebra (L3) and the skeletal muscle volume (cm3) at the waist level were measured. These values were converted to the L3 skeletal muscle index (SMI) and volumetric SMI by normalisation with body height. The relationships between L3, volumetric SMIs, and survival outcomes were evaluated. RESULTS: Setting 39.0 cm2/m2 of L3 SMI as cut-off value for sarcopenia, sarcopenia (< 39.0 cm2/m2, n = 177) and non-sarcopenia (≥ 39.0 cm2/m2, n = 208) groups showed similar progression-free survival (PFS; p = 0.335) and overall survival (OS; p = 0.241). Using the median value, the low-volumetric SMI group (< 206.0 cm3/m3, n = 192) showed significantly worse PFS (3-year survival rate, 77.3% vs. 88.8%; p = 0.004) and OS (3-year survival rate, 92.8% vs. 99.4%; p = 0.003) than the high-volumetric SMI group (≥ 206.0 cm3/m3, n = 193). In multivariate analyses adjusted for baseline body mass index and other factors, low-volumetric SMI was identified as an independent poor prognostic factor for PFS (adjusted HR, 1.762; 95% CI, 1.051-2.953; p = 0.032) and OS (adjusted HR, 5.964; 95% CI, 1.296-27.448; p = 0.022). CONCLUSIONS: Waist skeletal muscle volume might be a novel prognostic biomarker in patients with endometrial cancer. Assessing body composition before treatment can provide important prognostic information for such patients.

Impact of Computed Tomography-Based, Artificial Intelligence-Driven Volumetric Sarcopenia on Survival Outcomes in Early Cervical Cancer.

The purpose of this study was to investigate the impact of sarcopenia and body composition change during primary treatment on survival outcomes in patients with early cervical cancer. We retrospectively identified patients diagnosed with 2009 International Federation of Gynecology and Obstetrics stage IB1-IIA2 cervical cancer who underwent primary radical hysterectomy between 2007 and 2019. From pre-treatment CT scans (n = 306), the skeletal muscle area at the third lumbar vertebra (L3) and the waist skeletal muscle volume were measured using an artificial intelligence-based tool. These values were converted to the L3 and volumetric skeletal muscle indices by normalization. We defined L3 and volumetric sarcopenia using 39.0 cm2/m2 and the first quartile (Q1) value, respectively. From pre- and post-treatment CT scan images (n = 192), changes (%) in waist skeletal muscle and fat volumes were assessed. With the use of Cox regression models, factors associated with progression-free survival (PFS) and overall survival (OS) were analyzed. Between the L3 sarcopenia and non-sarcopenia groups, no differences in PFS and OS were observed. In contrast, volumetric sarcopenia was identified as a poor prognostic factor for PFS (adjusted hazard ratio [aHR], 1.874; 95% confidence interval [CI], 1.028-3.416; p = 0.040) and OS (aHR, 3.001; 95% CI, 1.016-8.869; p = 0.047). During primary treatment, significant decreases in waist skeletal muscle (median, -3.9%; p < 0.001) and total fat (median, -5.3%; p < 0.001) were observed. Of the two components, multivariate analysis revealed that the waist fat gain was associated with worse PFS (aHR, 2.007; 95% CI, 1.009-3.993; p = 0.047). The coexistence of baseline volumetric sarcopenia and waist fat gain further deteriorated PFS (aHR, 2.853; 95% CI, 1.257-6.474; p = 0.012). In conclusion, baseline volumetric sarcopenia might be associated with poor survival outcomes in patients with early cervical cancer undergoing primary RH. Furthermore, sarcopenia patients who gained waist fat during primary treatment were at a high risk of disease recurrence.

Prognostic implications of body composition change during primary treatment in patients with ovarian cancer: A retrospective study using an artificial intelligence-based volumetric technique.

OBJECTIVE: To investigate the impact of changes in body composition during primary treatment on survival outcomes in patients with epithelial ovarian cancer (EOC). METHODS: We retrospectively identified patients diagnosed with EOC between 2010 and 2019. Using an artificial intelligence-based tool, the volumes of skeletal muscle, visceral fat, and subcutaneous fat were measured automatically at the waist level from pre-treatment and post-treatment computed tomography scans. Associations between changes in body mass index (BMI) and volume of each body composition component and survival outcomes were evaluated. RESULTS: A total of 208 patients were included. A significant decrease in BMI and waist volumes of skeletal muscle and visceral fat was observed during the primary treatment. Patients with BMI loss ≥5% showed significantly worse progression-free survival (PFS) and overall survival (OS) than those with BMI loss <5%. In multivariate analyses adjusting for clinicopathologic factors, BMI loss ≥5% was identified as an independent poor prognostic factor for PFS (adjusted HR, 1.565; 95% CI, 1.074-2.280; P = 0.020) and OS (adjusted HR, 2.754; 95% CI, 1.382-5.488; P = 0.004). Meanwhile, both muscle loss ≥10% and visceral fat loss ≥20% were associated with an increased mortality rate but did not affect disease recurrence. In multivariate analyses, muscle loss ≥10% (adjusted HR, 2.069; 95% CI, 1.055-4.058; P = 0.034) and visceral fat loss ≥20% (adjusted HR, 2.292; 95% CI, 1.023-5.133; P = 0.044) were poor prognostic factors for OS. Consistent results were observed in the advanced-stage disease subgroup (n = 173). CONCLUSIONS: Changes in BMI and waist volume of skeletal muscle and visceral fat were associated with survival outcomes in patients with EOC.

Prediction of microvascular invasion of hepatocellular carcinoma: value of volumetric iodine quantification using preoperative dual-energy computed tomography.

BACKGROUND: To investigate the potential value of volumetric iodine quantification using preoperative dual-energy computed tomography (DECT) for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). METHODS: This retrospective study included patients with single HCC treated through surgical resection who underwent preoperative DECT. Quantitative DECT features, including normalized iodine concentration (NIC) to the aorta and mixed-energy CT attenuation value in the arterial phase, were three-dimensionally measured for peritumoral and intratumoral regions: (i) layer-by-layer analysis for peritumoral layers (outer layers 1 and 2; numbered in close order from the tumor boundary) and intratumoral layers (inner layers 1 and 2) with 2-mm layer thickness and (ii) volume of interest (VOI)-based analysis with different volume coverage (tumor itself; VOIO1, tumor plus outer layer 1; VOIO2, tumor plus outer layers 1 and 2; VOII1, tumor minus inner layer 1; VOII2, tumor minus inner layers 1 and 2). In addition, qualitative CT features, including peritumoral enhancement and tumor margin, were assessed. Qualitative and quantitative CT features were compared between HCC patients with and without MVI. Diagnostic performance of DECT parameters of layers and VOIs was assessed using receiver operating characteristic curve analysis. RESULTS: A total of 36 patients (24 men, mean age 59.9 ± 8.5 years) with MVI (n = 14) and without MVI (n = 22) were included. HCCs with MVI showed significantly higher NICs of outer layer 1, outer layer 2, VOIO1, and VOIO2 than those without MVI (P = 0.01, 0.04, 0.02, 0.02, respectively). Among the NICs of layers and VOIs, the highest area under the curve was obtained in outer layer 1 (0.747). Qualitative features, including peritumoral enhancement and tumor margin, and the mean CT attenuation of each layer and each VOI were not significantly different between HCCs with and without MVI (both P >  0.05). CONCLUSIONS: Volumetric iodine quantification of peritumoral and intratumoral regions in arterial phase using DECT may help predict the MVI of HCC.