Automated abdominal organ segmentation algorithms for non-enhanced CT for volumetry and 3D radiomics analysis.

PURPOSE: To develop fully-automated abdominal organ segmentation algorithms from non-enhanced abdominal CT and low-dose chest CT and assess their feasibility for automated CT volumetry and 3D radiomics analysis of abdominal solid organs. METHODS: Fully-automated nnU-Net-based models were developed to segment the liver, spleen, and both kidneys in non-enhanced abdominal CT, and the liver and spleen in low-dose chest CT. 105 abdominal CTs and 60 low-dose chest CTs were used for model development, and 55 abdominal CTs and 10 low-dose chest CTs for external testing. The segmentation performance for each organ was assessed using the Dice similarity coefficients, with manual segmentation results serving as the ground truth. Agreements between ground-truth measurements and model estimates of organ volume and 3D radiomics features were assessed using the Bland-Altman analysis and intraclass correlation coefficients (ICC). RESULTS: The models accurately segmented the liver, spleen, right kidney, and left kidney in abdominal CT and the liver and spleen in low-dose chest CT, showing mean Dice similarity coefficients in the external dataset of 0.968, 0.960, 0.952, and 0.958, respectively, in abdominal CT, and 0.969 and 0.960, respectively, in low-dose chest CT. The model-estimated and ground truth volumes of these organs exhibited mean differences between - 0.7% and 2.2%, with excellent agreements. The automatically extracted mean and median Hounsfield units (ICCs, 0.970-0.999 and 0.994-0.999, respectively), uniformity (ICCs, 0.985-0.998), entropy (ICCs, 0.931-0.993), elongation (ICCs, 0.978-0.992), and flatness (ICCs, 0.973-0.997) showed excellent agreement with ground truth measurements for each organ; however, skewness (ICCs, 0.210-0.831), kurtosis (ICCs, 0.053-0.933), and sphericity (ICCs, 0.368-0.819) displayed relatively low and inconsistent agreement. CONCLUSION: Our nnU-Net-based models accurately segmented abdominal solid organs in non-enhanced abdominal and low-dose chest CT, enabling reliable automated measurements of organ volume and specific 3D radiomics features.

Development and validation of MRI PDFF Cut-offs for living liver donor eligibility assessment.

Hepatic steatosis (HS) criteria for living donor liver transplantation (LDLT) donor eligibility should be based on large droplet fat as per Banff consensus recommendations. We aimed to establish MRI PDFF cut-offs for HS assessment in potential LDLT donors. This retrospective study included consecutive potential LDLT donors who underwent MRI and liver biopsy between 2013 and 2023 at two tertiary institutions, each as development (n=3062; 2015 men; median [interquartile range] age of 32 [25-38] years) and external validation (n=472; 287 men; 35 [26-44] years) datasets. PDFF was measured using dedicated MRI sequences. Histologic HS defined as large droplet fat fraction was used as the reference standard. Dual PDFF cut-offs aimed at 95% sensitivity or 95% specificity, for diagnosing histologic HS of ≥10%, ≥20%, ≥30%, and ≥40%, were determined in the development dataset using ten-fold cross validation. The cut-offs were then validated in the external validation dataset. Equation for estimating histologic HS from PDFF was also derived using linear regression. The PDFF cut-offs for histologic HS of ≥10%, ≥20%, ≥30%, and ≥40%, targeting 95% sensitivity, were 3.7%, 5.5%, 8.0%, and 10.0%, respectively. External validation demonstrated high sensitivities ≥ 97.9% with specificities ranging from 60.9% to 95.1%. The PDFF cut-offs targeting 95% specificity were 6.3%, 8.0%, 9.1%, and 10.1%, respectively. External validation rendered high specificities ranging from 88.5% to 95.3% with sensitivities ranging from 76.6% to 100%. For diagnosing histologic HS ≥30%, which is the most prevalently used threshold for LDLT donor eligibility assessment, the PDFF cut-offs achieved sensitivities and specificities of both over 90%. The equation of (Histologic HS=-2.95 + 1.93 * PDFF) was derived.

Automated hepatic steatosis assessment on dual-energy CT-derived virtual non-contrast images through fully-automated 3D organ segmentation.

PURPOSE: To evaluate the efficacy of volumetric CT attenuation-based parameters obtained through automated 3D organ segmentation on virtual non-contrast (VNC) images from dual-energy CT (DECT) for assessing hepatic steatosis. MATERIALS AND METHODS: This retrospective study included living liver donor candidates having liver DECT and MRI-determined proton density fat fraction (PDFF) assessments. Employing a 3D deep learning algorithm, the liver and spleen were automatically segmented from VNC images (derived from contrast-enhanced DECT scans) and true non-contrast (TNC) images, respectively. Mean volumetric CT attenuation values of each segmented liver (L) and spleen (S) were measured, allowing for liver attenuation index (LAI) calculation, defined as L minus S. Agreements of VNC and TNC parameters for hepatic steatosis, i.e., L and LAI, were assessed using intraclass correlation coefficients (ICC). Correlations between VNC parameters and MRI-PDFF values were assessed using the Pearson's correlation coefficient. Their performance to identify MRI-PDFF ≥ 5% and ≥ 10% was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS: Of 252 participants, 56 (22.2%) and 16 (6.3%) had hepatic steatosis with MRI-PDFF ≥ 5% and ≥ 10%, respectively. LVNC and LAIVNC showed excellent agreement with LTNC and LAITNC (ICC = 0.957 and 0.968) and significant correlations with MRI-PDFF values (r = - 0.585 and - 0.588, Ps < 0.001). LVNC and LAIVNC exhibited areas under the ROC curve of 0.795 and 0.806 for MRI-PDFF ≥ 5%; and 0.916 and 0.932, for MRI-PDFF ≥ 10%, respectively. CONCLUSION: Volumetric CT attenuation-based parameters from VNC images generated by DECT, via automated 3D segmentation of the liver and spleen, have potential for opportunistic hepatic steatosis screening, as an alternative to TNC images.

Colon cancer: the 2023 Korean clinical practice guidelines for diagnosis and treatment.

Colorectal cancer is the third most common cancer in Korea and the third leading cause of death from cancer. Treatment outcomes for colon cancer are steadily improving due to national health screening programs with advances in diagnostic methods, surgical techniques, and therapeutic agents.. The Korea Colon Cancer Multidisciplinary (KCCM) Committee intends to provide professionals who treat colon cancer with the most up-to-date, evidence-based practice guidelines to improve outcomes and help them make decisions that reflect their patients' values and preferences. These guidelines have been established by consensus reached by the KCCM Guideline Committee based on a systematic literature review and evidence synthesis and by considering the national health insurance system in real clinical practice settings. Each recommendation is presented with a recommendation strength and level of evidence based on the consensus of the committee.

CT findings and clinical effects of high grade pancreatic intraepithelial neoplasia in patients with intraductal papillary mucinous neoplasms.

PURPOSE: To investigate the common CT findings of high-grade (HG) PanIN and clinical effects in the remnant pancreas in patients with intraductal papillary mucinous neoplasm (IPMN) of the pancreas. MATERIALS AND METHODS: Two hundred fifty-one patients with surgically confirmed IPMNs (118 malignant [invasive carcinoma/high-grade dysplasia] and 133 benign [low-grade dysplasia]) were retrospectively enrolled. The grade of PanIN (233 absent/low-grade and 18 high-grade) was recorded, and all patients underwent serial CT follow-up before and after surgery. Two radiologists analyzed CT findings of high-risk stigmata or worrisome features according to 2017 international consensus guidelines. They also analyzed tumor recurrence on serial follow-up CT after surgery. Statistical analyses were performed to identify significant predictors and clinical impact on postoperative outcomes of HG PanIN. RESULTS: PanIN grade showed a significant association with IPMN grade (p = 0.012). Enhancing mural nodules ≥5 mm, abrupt main pancreatic duct (MPD) changes with distal pancreatic atrophy, increased mural nodule size and MPD diameter were common findings in HG PanIN (P<0.05). In multivariate analysis, abrupt MPD change with distal pancreatic atrophy (odds ratio (OR) 6.59, 95% CI: 2.32-18.72, <0.001) and mural nodule size (OR, 1.05; 95% CI, 1.02-1.08, 0.004) were important predictors for HG PanIN. During postoperative follow-up, HG PanIN (OR, 4.98; 95% CI, 1.22-20.33, 0.025) was significantly associated with cancer recurrence in the remnant pancreas. CONCLUSION: CT can be useful for predicting HG PanIN using common features, such as abrupt MPD changes and mural nodules. In HG PanIN, extra caution is needed to monitor postoperative recurrence during follow-up.

Enhancing gadoxetic acid-enhanced liver MRI: a synergistic approach with deep learning CAIPIRINHA-VIBE and optimized fat suppression techniques.

OBJECTIVE: To investigate whether a deep learning (DL) controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE) technique can improve image quality, lesion conspicuity, and lesion detection compared to a standard CAIPIRINHA-VIBE technique in gadoxetic acid-enhanced liver MRI. METHODS: This retrospective single-center study included 168 patients who underwent gadoxetic acid-enhanced liver MRI at 3 T using both standard CAIPIRINHA-VIBE and DL CAIPIRINHA-VIBE techniques on pre-contrast and hepatobiliary phase (HBP) images. Additionally, high-resolution (HR) DL CAIPIRINHA-VIBE was obtained with 1-mm slice thickness on the HBP. Three abdominal radiologists independently assessed the image quality and lesion conspicuity of pre-contrast and HBP images. Statistical analyses involved the Wilcoxon signed-rank test for image quality assessment and the generalized estimation equation for lesion conspicuity and detection evaluation. RESULTS: DL and HR-DL CAIPIRINHA-VIBE demonstrated significantly improved overall image quality and reduced artifacts on pre-contrast and HBP images compared to standard CAIPIRINHA-VIBE (p < 0.001), with a shorter acquisition time (DL vs standard, 11 s vs 17 s). However, the former presented a more synthetic appearance (both p < 0.05). HR-DL CAIPIRINHA-VIBE showed superior lesion conspicuity to standard and DL CAIPIRINHA-VIBE on HBP images (p < 0.001). Moreover, HR-DL CAIPIRINHA-VIBE exhibited a significantly higher detection rate of small (< 2 cm) solid focal liver lesions (FLLs) on HBP images compared to standard CAIPIRINHA-VIBE (92.5% vs 87.4%; odds ratio = 1.83; p = 0.036). CONCLUSION: DL and HR-DL CAIPIRINHA-VIBE achieved superior image quality compared to standard CAIPIRINHA-VIBE. Additionally, HR-DL CAIPIRINHA-VIBE improved the lesion conspicuity and detection of small solid FLLs. DL and HR-DL CAIPIRINHA-VIBE hold the potential clinical utility for gadoxetic acid-enhanced liver MRI. CLINICAL RELEVANCE STATEMENT: DL and HR-DL CAIPIRINHA-VIBE hold promise as potential alternatives to standard CAIPIRINHA-VIBE in routine clinical liver MRI, improving the image quality and lesion conspicuity, enhancing the detection of small (< 2 cm) solid focal liver lesions, and reducing the acquisition time. KEY POINTS: • DL and HR-DL CAIPIRINHA-VIBE demonstrated improved overall image quality and reduced artifacts on pre-contrast and HBP images compared to standard CAIPIRINHA-VIBE, in addition to a shorter acquisition time. • DL and HR-DL CAIPIRINHA-VIBE yielded a more synthetic appearance than standard CAIPIRINHA-VIBE. • HR-DL CAIPIRINHA-VIBE showed improved lesion conspicuity than standard CAIPIRINHA-VIBE on HBP images, with a higher detection of small (< 2 cm) solid focal liver lesions.

Utilizing fully-automated 3D organ segmentation for hepatic steatosis assessment with CT attenuation-based parameters.

OBJECTIVES: To investigate the clinical utility of fully-automated 3D organ segmentation in assessing hepatic steatosis on pre-contrast and post-contrast CT images using magnetic resonance spectroscopy (MRS)-proton density fat fraction (PDFF) as reference standard. MATERIALS AND METHODS: This retrospective study analyzed 362 adult potential living liver donors with abdominal CT scans and MRS-PDFF. Using a deep learning-based tool, mean volumetric CT attenuation of the liver and spleen were measured on pre-contrast (liver(L)_pre and spleen(S)_pre) and post-contrast (L_post and S_post) images. Agreements between volumetric and manual region-of-interest (ROI)-based measurements were assessed using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. Diagnostic performances of volumetric parameters (L_pre, liver-minus-spleen (L-S)_pre, L_post, and L-S_post) were evaluated for detecting MRS-PDFF ≥ 5% and ≥ 10% using receiver operating characteristic (ROC) curve analysis and compared with those of ROI-based parameters. RESULTS: Among the 362 subjects, 105 and 35 had hepatic steatosis with MRS-PDFF ≥ 5% and ≥ 10%, respectively. Volumetric and ROI-based measurements revealed ICCs of 0.974, 0.825, 0.992, and 0.962, with mean differences of -4.2 HU, -3.4 HU, -1.2 HU, and -7.7 HU for L_pre, S_pre, L_post, and S_post, respectively. Volumetric L_pre, L-S_pre, L_post, and L-S_post yielded areas under the ROC curve of 0.813, 0.813, 0.734, and 0.817 for MRS-PDFF ≥ 5%; and 0.901, 0.915, 0.818, and 0.868 for MRS-PDFF ≥ 10%, comparable with those of ROI-based parameters (0.735-0.818; and 0.816-0.895, Ps = 0.228-0.911). CONCLUSION: Automated 3D segmentation of the liver and spleen in CT scans can provide volumetric CT attenuation-based parameters to detect and grade hepatic steatosis, applicable to pre-contrast and post-contrast images. CLINICAL RELEVANCE STATEMENT: Volumetric CT attenuation-based parameters of the liver and spleen, obtained through automated segmentation tools from pre-contrast or post-contrast CT scans, can efficiently detect and grade hepatic steatosis, making them applicable for large population data collection. KEY POINTS: • Automated organ segmentation enables the extraction of CT attenuation-based parameters for the target organ. • Volumetric liver and spleen CT attenuation-based parameters are highly accurate in hepatic steatosis assessment. • Automated CT measurements from pre- or post-contrast imaging show promise for hepatic steatosis screening in large cohorts.

Fully-automated multi-organ segmentation tool applicable to both non-contrast and post-contrast abdominal CT: deep learning algorithm developed using dual-energy CT images.

A novel 3D nnU-Net-based of algorithm was developed for fully-automated multi-organ segmentation in abdominal CT, applicable to both non-contrast and post-contrast images. The algorithm was trained using dual-energy CT (DECT)-obtained portal venous phase (PVP) and spatiotemporally-matched virtual non-contrast images, and tested using a single-energy (SE) CT dataset comprising PVP and true non-contrast (TNC) images. The algorithm showed robust accuracy in segmenting the liver, spleen, right kidney (RK), and left kidney (LK), with mean dice similarity coefficients (DSCs) exceeding 0.94 for each organ, regardless of contrast enhancement. However, pancreas segmentation demonstrated slightly lower performance with mean DSCs of around 0.8. In organ volume estimation, the algorithm demonstrated excellent agreement with ground-truth measurements for the liver, spleen, RK, and LK (intraclass correlation coefficients [ICCs] > 0.95); while the pancreas showed good agreements (ICC = 0.792 in SE-PVP, 0.840 in TNC). Accurate volume estimation within a 10% deviation from ground-truth was achieved in over 90% of cases involving the liver, spleen, RK, and LK. These findings indicate the efficacy of our 3D nnU-Net-based algorithm, developed using DECT images, which provides precise segmentation of the liver, spleen, and RK and LK in both non-contrast and post-contrast CT images, enabling reliable organ volumetry, albeit with relatively reduced performance for the pancreas.

Prognostic value of initial and longitudinal changes in body composition in metastatic pancreatic cancer.

BACKGROUND: Sarcopenia or visceral adipose tissue has been reported to be related to pancreatic cancer prognosis. However, clinical relevance of the comprehensive analysis of body compositions and their longitudinal changes is lacking. This study analysed the association between body composition changes after chemotherapy and survival in patients with metastatic pancreatic cancer. METHODS: We retrospectively included 456 patients (mean age ± standard deviation, 61.2 ± 10.0 years; 272 males and 184 females) with metastatic pancreatic cancer who received palliative chemotherapy from May 2011 to December 2019. Using deep learning-based, fully automated segmentation of contrast-enhanced computed tomography (CT) at the time of diagnosis, cross-sectional areas of muscle, subcutaneous adipose tissue and visceral adipose tissue were extracted from a single axial image of the portal venous phase at L3 level. Skeletal muscle index (SMI), visceral adipose tissue index (VATI), subcutaneous adipose tissue index (SATI) and mean skeletal muscle attenuation (MA) were calculated, and their effect on overall survival (OS) was analysed. Longitudinal changes in body composition and prognostic values were also analysed in a subgroup of patients with 2- and 6-month follow-up CT (n = 349). RESULTS: A total of 452 deaths occurred during follow-up in the entire cohort. The survival rate was 49.3% (95% confidence interval [CI], 44.9-54.2) at 1 year and 3.7% (95% CI, 2.0-6.8) at 5 years. In multivariable analysis, higher MA (≥44.4 HU in males and ≥34.8 HU in females) at initial CT was significantly associated with better OS in both males and females (adjusted hazard ratio [HR], 0.706; 95% CI, 0.538-0.925; P = 0.012 for males, and HR, 0.656; 95% CI, 0.475-0.906; P = 0.010 for females), whereas higher SATI (≥42.8 cm2/m2 in males and ≥65.8 cm2/m2 in females) was significantly associated with better OS in female patients only (adjusted HR, 0.568; 95% CI, 0.388-0.830; P = 0.003). In longitudinal analysis, SMI, VATI and SATI significantly decreased between initial and 2-month follow-up CT, whereas mean MA significantly decreased between 2- and 6-month follow-up CT. In multivariable Cox regression analysis of longitudinal changes, which was stratified by disease control state, SATI change was significantly associated with OS in male patients (adjusted HR, 0.513; 95% CI, 0.354-0.745; P < 0.001), while other body composition parameters were not. CONCLUSIONS: In patients with metastatic pancreatic cancer, body composition mostly changed during the first 2 months after starting chemotherapy, and the prognostic factors associated with OS differed between males and females. Initial and longitudinal changes of body composition are associated with OS of metastatic pancreatic cancer.

Inter-platform reproducibility of ultrasound-based fat fraction for evaluating hepatic steatosis in nonalcoholic fatty liver disease.

OBJECTIVES: To evaluate the inter-platform reproducibility of ultrasound-based fat fraction examination in nonalcoholic fatty liver disease (NAFLD). METHODS: Patients suspected of having NAFLD were prospectively enrolled from January 2023. Ultrasound-based fat fraction examinations were performed using two different platforms (ultrasound-derived fat fraction [UDFF] and quantitative ultrasound-derived estimated fat fraction [USFF]) on the same day. The correlation between UDFF and USFF was assessed using Pearson correlation coefficient. Intraclass correlation coefficient (ICC), Bland-Altman analysis with 95% limits of agreement (LOAs), and the coefficient of variation (CV) were used to assess inter-platform reproducibility. RESULTS: A total of 41 patients (21 men and 20 women; mean age, 53.9 ± 12.6 years) were analyzed. Moderate correlation was observed between UDFF and USFF (Pearson's r = 0.748; 95% confidence interval [CI]: 0.572-0.858). On Bland-Altman analysis, the mean difference between UDFF and USFF values was 1.3% with 95% LOAs ranging from -8.0 to 10.6%. The ICC between UDFF and USFF was 0.842 (95% CI: 0.703-0.916), with a CV of 29.9%. CONCLUSION: Substantial inter-platform variability was observed among different ultrasound-based fat fraction examinations. Therefore, it is not appropriate to use ultrasound-based fat fraction values obtained from different vendors interchangeably. CRITICAL RELEVANCE STATEMENT: Considering the substantial inter-platform variability in ultrasound-based fat fraction assessments, caution is imperative when interpreting and comparing fat fraction values obtained from different ultrasound platforms in clinical practice. KEY POINTS: • Inter-platform reproducibility of ultrasound-based fat fraction examinations is important for its clinical application. • Significant variability across different ultrasound-based fat fraction examinations was observed. • Using ultrasound-based fat fraction values from different vendors interchangeably is not advisable.

Added value of positive intraluminal contrast CT over fluoroscopic examination for detecting gastrointestinal leakage after gastrointestinal surgery.

We aimed to evaluate the added value of positive intraluminal contrast computed tomography (CT) over fluoroscopy in detecting anastomotic leakage after gastrointestinal (GI) surgery. A total of 141 GI surgery patients who underwent fluoroscopic examination and CT were included. Two radiologists reviewed the fluoroscopic images with and without CT to determine anastomotic leakage on a 5-point confidence scale and graded the leakage on a 4-point grading system. The hospital stay duration and treatment type were recorded. The radiologists' diagnostic performance in determining leakage was compared using the receiver operating characteristics analysis, and interobserver agreement was analyzed. Fifty-three patients developed GI leakage. When CT was added to the fluoroscopic images, the area under the curve (AUC) values significantly increased for both reviewers. The interobserver agreement for leakage between the two reviewers was excellent and improved with the addition of CT (weighted kappa value, 0.869 versus 0.805). Postoperative intervention was more frequently performed (P < 0.001), and patients with leakage had a significantly longer mean postoperative hospital stay (45 days vs. 27 days) (P = 0.003). Thus, positive intraluminal contrast CT provides added value over fluoroscopic examination for detecting GI leakage in patients undergoing GI tract surgery, increasing AUC values, and improving interobserver agreement.

Intraductal papillary neoplasm of the bile duct: diagnostic value of MRI features in differentiating pathologic subclassifications-type 1 versus type 2.

OBJECTIVES: To identify MRI features for differentiating type 2 from type 1 intraductal papillary neoplasms of bile duct (IPNB) and assessing malignant potential of IPNB. METHODS: This retrospective study included 60 patients with surgically proven IPNB who had undergone preoperative MRI between January 2007 and December 2020. All surgical specimens were reviewed retrospectively to classify types 1 and 2 IPNBs and assess tumor grade. Significant MRI features for differentiating type 2 (n = 40) from type 1 IPNB (n = 20); and for IPNB with an associated invasive carcinoma (n = 43) from intraepithelial neoplasia (n = 17) were determined using logistic regression analysis. RESULTS: An associated invasive carcinoma was more frequently found in type 2 than in type 1 IPNB (85.0% [34/40] vs. 45.0% [9/20], p = 0.003). At univariable analysis, MRI features including extrahepatic location, no dilatation of tumor-bearing segment of bile duct, isolated upstream bile duct dilatation, and single lesion were associated with type 2 IPNB (all p ≤ 0.012). At multivariable analysis, significant MRI findings for differentiating type 2 from type 1 IPNB were extrahepatic location and no dilatation of tumor-bearing segment of bile duct (odds ratio [OR], 7.24 and 46.40, respectively). At univariable and multivariable analysis, tumor size ≥ 2.5 cm (OR, 8.45), bile duct wall thickening (OR, 4.82), and irregular polypoid or nodular tumor shape (OR, 6.44) were significant MRI features for differentiating IPNB with an associated invasive carcinoma from IPNB with intraepithelial neoplasia. CONCLUSION: MRI with MR cholangiopancreatography may be helpful in differentiating type 2 IPNB from type 1 IPNB and assessing malignant potential of IPNB. CLINICAL RELEVANCE STATEMENT: Preoperative MRI with MR cholangiopancreatography may be helpful in differentiating type 2 intraductal papillary neoplasms of bile duct (IPNB) from type 1 IPNB and assessing malignant potential of IPNB. KEY POINTS: • In terms of tumor grade, the incidence of invasive carcinoma was significantly higher in type 2 intraductal papillary neoplasm of the bile duct (IPNB) than in type 1 IPNB. • At MRI, extrahepatic location and no dilatation of tumor-bearing segment are significant features for differentiating type 2 IPNBs from type 1 IPNBs. • At MRI, large tumor size, bile duct wall thickening, and irregular polypoid or nodular tumor shape are significant features for differentiating IPNB with an associated invasive carcinoma from IPNB with intraepithelial neoplasia.

Prognostic role of computed tomography analysis using deep learning algorithm in patients with chronic hepatitis B viral infection.

BACKGROUND/AIMS: The prediction of clinical outcomes in patients with chronic hepatitis B (CHB) is paramount for effective management. This study aimed to evaluate the prognostic value of computed tomography (CT) analysis using deep learning algorithms in patients with CHB. METHODS: This retrospective study included 2,169 patients with CHB without hepatic decompensation who underwent contrast-enhanced abdominal CT for hepatocellular carcinoma (HCC) surveillance between January 2005 and June 2016. Liver and spleen volumes and body composition measurements including subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle indices were acquired from CT images using deep learning-based fully automated organ segmentation algorithms. We assessed the significant predictors of HCC, hepatic decompensation, diabetes mellitus (DM), and overall survival (OS) using Cox proportional hazard analyses. RESULTS: During a median follow-up period of 103.0 months, HCC (n=134, 6.2%), hepatic decompensation (n=103, 4.7%), DM (n=432, 19.9%), and death (n=120, 5.5%) occurred. According to the multivariate analysis, standardized spleen volume significantly predicted HCC development (hazard ratio [HR]=1.01, P=0.025), along with age, sex, albumin and platelet count. Standardized spleen volume (HR=1.01, P<0.001) and VAT index (HR=0.98, P=0.004) were significantly associated with hepatic decompensation along with age and albumin. Furthermore, VAT index (HR=1.01, P=0.001) and standardized spleen volume (HR=1.01, P=0.001) were significant predictors for DM, along with sex, age, and albumin. SAT index (HR=0.99, P=0.004) was significantly associated with OS, along with age, albumin, and MELD. CONCLUSION: Deep learning-based automatically measured spleen volume, VAT, and SAT indices may provide various prognostic information in patients with CHB.

Comparison Between Contrast-Enhanced Computed Tomography and Contrast-Enhanced Magnetic Resonance Imaging With Magnetic Resonance Cholangiopancreatography for Resectability Assessment in Extrahepatic Cholangiocarcinoma.

OBJECTIVE: To compare the diagnostic performance and interobserver agreement between contrast-enhanced computed tomography (CECT) and contrast-enhanced magnetic resonance imaging (CE-MRI) with magnetic resonance cholangiopancreatography (MRCP) for evaluating the resectability in patients with extrahepatic cholangiocarcinoma (eCCA). MATERIALS AND METHODS: This retrospective study included treatment-naïve patients with pathologically confirmed eCCA, who underwent both CECT and CE-MRI with MRCP using extracellular contrast media between January 2015 and December 2020. Among the 214 patients (146 males; mean age ± standard deviation, 68 ± 9 years) included, 121 (56.5%) had perihilar cholangiocarcinoma. R0 resection was achieved in 108 of the 153 (70.6%) patients who underwent curative-intent surgery. Four fellowship-trained radiologists independently reviewed the findings of both CECT and CE-MRI with MRCP to assess the local tumor extent and distant metastasis for determining resectability. The pooled area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of CECT and CE-MRI with MRCP were compared using clinical, surgical, and pathological findings as reference standards. The interobserver agreement of resectability was evaluated using Fleiss kappa (κ). RESULTS: No significant differences were observed between CECT and CE-MRI with MRCP in the pooled AUC (0.753 vs. 0.767), sensitivity (84.7% [366/432] vs. 90.3% [390/432]), and specificity (52.6% [223/424] vs. 51.4% [218/424]) (P > 0.05 for all). The AUC for determining resectability was higher when CECT and CE-MRI with MRCP were reviewed together than when CECT was reviewed alone in patients with discrepancies between the imaging modalities or with indeterminate resectability (0.798 [0.754-0.841] vs. 0.753 [0.697-0.808], P = 0.014). The interobserver agreement for overall resectability was fair for both CECT (κ = 0.323) and CE-MRI with MRCP (κ = 0.320), without a significant difference (P = 0.884). CONCLUSION: CECT and CE-MRI with MRCP showed no significant differences in the diagnostic performance and interobserver agreement in determining the resectability in patients with eCCA.

Development and validation of multivariable quantitative ultrasound for diagnosing hepatic steatosis.

This study developed and validated multivariable quantitative ultrasound (QUS) model for diagnosing hepatic steatosis. Retrospective secondary analysis of prospectively collected QUS data was performed. Participants underwent QUS examinations and magnetic resonance imaging proton density fat fraction (MRI-PDFF; reference standard). A multivariable regression model for estimating hepatic fat fraction was determined using two QUS parameters from one tertiary hospital (development set). Correlation between QUS-derived estimated fat fraction(USFF) and MRI-PDFF and diagnostic performance of USFF for hepatic steatosis (MRI-PDFF ≥ 5%) were assessed, and validated in an independent data set from the other health screening center(validation set). Development set included 173 participants with suspected NAFLD with 126 (72.8%) having hepatic steatosis; and validation set included 452 health screening participants with 237 (52.4%) having hepatic steatosis. USFF was correlated with MRI-PDFF (Pearson r = 0.799 and 0.824; development and validation set). The model demonstrated high diagnostic performance, with areas under the receiver operating characteristic curves of 0.943 and 0.924 for development and validation set, respectively. Using cutoff of 6.0% from development set, USFF showed sensitivity, specificity, positive predictive value, and negative predictive value of 87.8%, 78.6%, 81.9%, and 85.4% for diagnosing hepatic steatosis in validation set. In conclusion, multivariable QUS parameters-derived estimated fat fraction showed high diagnostic performance for detecting hepatic steatosis.

Abbreviated MRI for Secondary Surveillance of Recurrent Hepatocellular Carcinoma After Presumed Curative Treatment.

BACKGROUND: Little is known about the performance of abbreviated MRI (AMRI) for secondary surveillance of recurrent hepatocellular carcinoma (HCC) after curative treatment. PURPOSE: To evaluate the detection performance of AMRI for secondary surveillance of HCC after curative treatment. STUDY TYPE: Retrospective. POPULATION: A total of 243 patients (183 men and 60 women; median age, 65 years) who underwent secondary surveillance for HCC using gadoxetic acid-enhanced MRI after more than 2 year of disease-free period following curative treatment, including surgical resection or radiofrequency ablation (RFA). FIELD STRENGTH/SEQUENCE: A 3.0 T/noncontrast AMRI (NC-AMRI) (T2-weighted fast spin-echo, T1-weighted gradient echo, and diffusion-weighted images), hepatobiliary phase AMRI (HBP-AMRI) (T2-weighted fast spin-echo, diffusion-weighted, and HBP images), and full-sequence MRI ASSESSMENT: Four board-certified radiologists independently reviewed NC-AMRI, HBP-AMRI, and full-sequence MRI sets of each patient for detecting recurrent HCC. STATISTICAL TESTS: Per-lesion sensitivity, per-patient sensitivity and specificity for HCC detection at each set were compared using generalized estimating equation. RESULTS: A total of 42 recurred HCCs were confirmed in the 39 patients. The per-lesion and per-patient sensitivities did not show significant differences among the three image sets for either reviewer (P ≥ 0.358): per-lesion sensitivity: 59.5%-83.3%, 59.5%-85.7%, and 59.5%-83.3%, and per-patient sensitivity: 53.9%-83.3%, 56.4%-85.7%, and 53.9%-83.3% for NC-AMRI, HBP-AMRI, and full-sequence MRI, respectively. Per-lesion pooled sensitivities of NC-AMRI, HBP-AMRI, and full-sequence MRI were 72.6%, 73.2%, and 73.2%, with difference of -0.6% (95% confidence interval: -6.7, 5.5) between NC-AMRI and full-sequence MRI and 0.0% (-6.1, 6.1) between HBP-AMRI and full-sequence MRI. Per-patient specificity was not significantly different among the three image sets for both reviewers (95.6%-97.1%, 95.6%-97.1%, and 97.6%-98.5% for NC-AMRI and HBP-AMRI, respectively; P ≥ 0.117). DATA CONCLUSION: NC-AMRI and HBP-AMRI showed no significant difference in detection performance to that of full-sequence gadoxetic acid-enhanced MRI during secondary surveillance for HCC after more than 2-year disease free interval following curative treatment. Based on its good detection performance, short scan time, and lack of contrast agent-associated risks, NC-AMRI is a promising option for the secondary surveillance of HCC. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Two-dimensional Convolutional Neural Network Using Quantitative US for Noninvasive Assessment of Hepatic Steatosis in NAFLD.

Background Quantitative US (QUS) using radiofrequency data analysis has been recently introduced for noninvasive evaluation of hepatic steatosis. Deep learning algorithms may improve the diagnostic performance of QUS for hepatic steatosis. Purpose To evaluate a two-dimensional (2D) convolutional neural network (CNN) algorithm using QUS parametric maps and B-mode images for diagnosis of hepatic steatosis, with the MRI-derived proton density fat fraction (PDFF) as the reference standard, in patients with nonalcoholic fatty liver disease (NAFLD). Materials and Methods: Consecutive adult participants with suspected NAFLD were prospectively enrolled at a single academic medical center from July 2020 to June 2021. Using radiofrequency data analysis, two QUS parameters (tissue attenuation imaging [TAI] and tissue scatter-distribution imaging [TSI]) were measured. On B-mode images, hepatic steatosis was graded using visual scoring (none, mild, moderate, or severe). Using B-mode images and two QUS parametric maps (TAI and TSI) as input data, the algorithm estimated the US fat fraction (USFF) as a percentage. The correlation between the USFF and MRI PDFF was evaluated using the Pearson correlation coefficient. The diagnostic performance of the USFF for hepatic steatosis (MRI PDFF ≥5%) was evaluated using receiver operating characteristic curve analysis and compared with that of TAI, TSI, and visual scoring. Results Overall, 173 participants (mean age, 51 years ± 14 [SD]; 96 men) were included, with 126 (73%) having hepatic steatosis (MRI PDFF ≥5%). USFF correlated strongly with MRI PDFF (Pearson r = 0.86, 95% CI: 0.82, 0.90; P < .001). For diagnosing hepatic steatosis (MRI PDFF ≥5%), the USFF yielded an area under the receiver operating characteristic curve of 0.97 (95% CI: 0.93, 0.99), higher than those of TAI, TSI, and visual scoring (P = .015, .006, and < .001, respectively), with a sensitivity of 90% (95% CI: 84, 95 [114 of 126]) and a specificity of 91% (95% CI: 80, 98 [43 of 47]) at a cutoff value of 5.7%. Conclusion A deep learning algorithm using quantitative US parametric maps and B-mode images accurately estimated the hepatic fat fraction and diagnosed hepatic steatosis in participants with nonalcoholic fatty liver disease. ClinicalTrials.gov registration nos. NCT04462562, NCT04180631 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sidhu and Fang in this issue.

Additional value of superb microvascular imaging of ultrasound examinations to evaluate focal liver lesions.

PURPOSE: To evaluate the additional value of superb microvascular imaging (SMI) to characterize focal liver lesions (FLLs). METHOD: Between July 2020 and December 2020, 70 patients (39 men and 31 women; mean age [± standard deviation], 61.1 ± 10.1 years) with FLLs were prospectively enrolled and underwent B-mode ultrasound (US), color Doppler imaging (CDI), power Doppler imaging (PDI), and SMI examinations on the same day. All the malignant FLLs were confirmed by histological diagnosis, while the benign FLLs were confirmed by typical imaging features at contrast-enhanced CT and/or MRI. Tumor vascularity scores in CDI, PDI, and SMI were graded using a 5-point scale. For tumors in which vascularity was detected on SMI, tumor vascular pattern on SMI was assessed in each lesion. The diagnostic performance of a combination of B-mode US and SMI, based on vascular pattern on SMI, was compared to B-mode US alone to diagnose malignant lesions; and hemangiomas. RESULTS: Seventy FLLs (34 benign [31 hemangiomas, 3 focal nodular hyperplasias] and 36 malignant tumors [16 hepatocellular carcinomas, 10 cholangiocarcinomas, 10 metastases]) were enrolled. Tumor vascularity score in SMI was significantly higher than those in CDI and PDI (P < 0.001). Using a combination of B-mode US and SMI, the diagnostic performance was improved from 0.867 and 0.834 to 0.945 and 0.921 (P = 0.035 and 0.112) to diagnose malignant tumors and from 0.896 and 0.853 to 0.975 and 0.987 (P = 0.027 and 0.006) to diagnose hemangiomas by reviewers 1 and 2, respectively. CONCLUSIONS: SMI provides higher sensitivity than CDI and PDI to detect tumor vascularity, and a combination of B-mode US and SMI can improve the characterization of FLLs when vascular pattern of tumor is considered.

Role of Dedicated Subspecialized Radiologists in Multidisciplinary Team Discussions on Lower Gastrointestinal Tract Cancers.

OBJECTIVE: To determine the impact of dedicated subspecialized radiologists in multidisciplinary team (MDT) discussions on the management of lower gastrointestinal (GI) tract malignancies. MATERIALS AND METHODS: We retrospectively analyzed the data of 244 patients (mean age ± standard deviation, 61.7 ± 11.9 years) referred to MDT discussions 249 times (i.e., 249 cases, as five patients were discussed twice for different issues) for lower GI tract malignancy including colorectal cancer, small bowel cancer, GI stromal tumor, and GI neuroendocrine tumor between April 2018 and June 2021 in a prospective database. Before the MDT discussions, dedicated GI radiologists reviewed all imaging studies again besides routine clinical reading. The referring clinician's initial diagnosis, initial treatment plan, change in radiologic interpretation compared with the initial radiology report, and the MDT's consensus recommendations for treatment were collected and compared. Factors associated with changes in treatment plans and the implementation of MDT decisions were analyzed. RESULTS: Of the 249 cases, radiologic interpretation was changed in 73 cases (29.3%) after a review by dedicated GI radiologists, with 78.1% (57/73) resulting in changes in the treatment plan. The treatment plan was changed in 92 cases (36.9%), and the rate of change in the treatment plan was significantly higher in cases with changes in radiologic interpretation than in those without (78.1% [57/73] vs. 19.9% [35/176], p < 0.001). Follow-up records of patients showed that 91.2% (227/249) of MDT recommendations for treatment were implemented. Multiple logistic regression analysis revealed that the nonsurgical approach (vs. surgical approach) decided through MDT discussion was a significant factor for patients being managed differently than the MDT recommendations (Odds ratio, 4.48; p = 0.017). CONCLUSION: MDT discussion involving additional review of radiology examinations by dedicated GI radiologists resulted in a change in the treatment plan in 36.9% of cases. Changes in treatment plans were significantly associated with changes in radiologic interpretation.