Should Hypervascular Incidentalomas Detected on Per-Interventional Cone Beam Computed Tomography during Intra-Arterial Therapies for Hepatocellular Carcinoma Impact the Treatment Plan in Patients Waiting for Liver Transplantation?

BACKGROUND: Current guidelines do not indicate any comprehensive management of hepatic hypervascular incidentalomas (HVIs) discovered in hepatocellular carcinoma (HCC) patients during intra-arterial therapies (IATs). This study aims to evaluate the prognostic value of HVIs detected on per-interventional cone beam computed tomography (CBCT) during IAT for HCC in patients waiting for liver transplantation (LT). MATERIAL AND METHODS: In this retrospective single-institutional study, all liver-transplanted HCC patients between January 2014 and December 2018 who received transarterial chemoembolization (TACE) or radioembolization (TARE) before LT were included. The number of ≥10 mm HCCs diagnosed on contrast-enhanced pre-interventional imaging (PII) was compared with that detected on per-interventional CBCT with a nonparametric Wilcoxon test. The correlation between the presence of an HVI and histopathological criteria associated with poor prognosis (HPP) on liver explants was investigated using the chi-square test. Tumor recurrence (TR) and TR-related mortality were investigated using the chi-square test. Recurrence-free survival (RFS), TR-related survival (TRRS), and overall survival (OS) were assessed according to the presence of HVI using Kaplan-Meier analysis. RESULTS: Among 63 included patients (average age: 59 ± 7 years, H/F = 50/13), 36 presented HVIs on per-interventional CBCT. The overall nodule detection rate of per-interventional CBCT was superior to that of PII (median at 3 [Q1:2, Q3:5] vs. 2 [Q1:1, Q3:3], respectively, p < 0.001). No significant correlation was shown between the presence of HVI and HPP (p = 0.34), TR (p = 0.095), and TR-related mortality (0.22). Kaplan-Meier analysis did not show a significant impact of the presence of HVI on RFS (p = 0.07), TRRS (0.48), or OS (p = 0.14). CONCLUSIONS: These results may indicate that the treatment plan during IAT should not be impacted or modified in response to HVI detection.

Interest of Integrated Whole-Body PET/MR Imaging in Gastroenteropancreatic Neuroendocrine Neoplasms: A Retro-Prospective Study.

INTRODUCTION AND AIM: Simultaneous positron emission tomography/magnetic resonance imaging (PET-MRI) combines the high sensitivity of PET with the high specificity of MRI and is a tool for the assessment of gastroenteropancreatic neuroendocrine neoplasms (G-NENs). However, it remains poorly evaluated with no clear recommendations in current guidelines. Thus, we evaluated the prognostic impact of PET-MRI in G-NEN patients. METHODS: From June 2017 to December 2021, 71 G-NEN patients underwent whole-body PET-MRI for staging and/or follow-up purposes. A whole-body emission scan with 18F-6-fluoro-L-dihydroxyphenylalanine (18FDOPA, n = 30), 18F-fluoro-2-deoxy-D-glucose (18FDG, n = 21), or 68Ga-(DOTA(0)-Phe(1)-Tyr(3))-octreotide (68Ga-DOTATOC, n = 20) with the simultaneous acquisition of a T1-Dixon sequence and diffusion-weighed imaging (DWI), followed by a dedicated step of MRI sequences with a Gadolinium contrast was performed. The patients underwent PET-MRI every 6-12 months during the follow-up period until death. Over this period, 50 patients with two or more PET-MRI were evaluated. RESULTS: The mean age was 61 [extremes, 31-92] years. At the baseline, PET-MRI provided new information in 12 cases (17%) as compared to conventional imaging: there were more metastases in eight, an undescribed location (myocardia) in two, and an unknown primary location in two cases. G grading at the baseline influenced overall survival. During the follow-up (7-381 months, mean 194), clinical and therapy managements were influenced by PET-MRI in three (6%) patients due to new metastases findings when neither overall, nor disease-free survivals in these two subgroups (n = 12 vs. n = 59), were different. CONCLUSION: Our study suggests that using PET/MRI with the appropriate radiotracer improves the diagnostic performance with no benefit on survival. Further studies are warranted to evaluate the cost-effectiveness of this procedure.

Selective internal radiation therapy for unresectable HCC: The SIRT downstaging study.

BACKGROUND: Selective internal radiation therapy (SIRT) is recommended as a downstaging (DS) strategy for solitary unresectable HCC <8 cm. The aim of this study was to report the results of acquired experience in a tertiary center for all unresectable HCCs. METHODS: We conducted a retrospective, observational study using data collected from consecutive patients undergoing SIRT between October 2013 and June 2020. DS was considered achieved when a curative treatment could be proposed 6 months after SIRT. RESULTS: One hundred twenty-seven patients were included (male = 90%, 64 ± 11 y), of whom 112 (n = 88%) had cirrhosis. HCC was classified as BCLC stage C in 64 patients (50%), with a median diameter of 61 mm, an infiltrative pattern in 51 patients (40%), and portal vein invasion in 62 (49%) patients. Fifty patients (39%) achieved DS 6 months following SIRT, with 29 of them (23%) undergoing curative treatment in a median time of 4.3 months: 17 (13%) were transplanted, 11 (85%) had liver resection, and 1 patient had a radiofrequency ablation. The median overall survival of patients with or without DS was 51 versus 10 months, respectively (p < 0.001). In patients who achieved DS, progression-free survival was higher in patients who underwent surgery: 47 versus 11 months (p < 0.001). Four variables were independently associated with DS: age (OR: 0.96, 95% CI: [0.92, 0.99]; p = 0.032), baseline α-fetoprotein (OR: 1.00, 95% CI: [1.00, 1.00]; p = 0.034), HCC distribution (OR: 0.3, 95% CI: [0.11, 0.75]; p = 0.012), and ALBI grade (OR: 0.34. 95% CI: [0.14, 0.80]; p = 0.014). CONCLUSIONS: These results suggest that SIRT in patients with unresectable HCC could be an effective treatment: DS was achieved for around 39% of the patients and more than half of these then underwent curative treatment.

Performance Comparison of Augmented Reality Versus Ultrasound Guidance for Puncture: A Phantom Study.

PURPOSE: Augmented reality (AR) is an innovative approach that could assist percutaneous procedures; by directly seeing "through" a phantom, targeting a lesion might be more intuitive than using ultrasound (US). The objective of this study was to compare the performance of experienced interventional radiologists and operators untrained in soft tissue lesion puncture using AR guidance and standard US guidance. MATERIAL AND METHODS: Three trained interventional radiologists with 5-10 years of experience and three untrained operators performed punctures of five targets in an abdominal phantom, with US guidance and AR guidance. Correct targeting, accuracy (defined as the Euclidean distance between the tip and the center of the target), planning time, and puncture time were documented. RESULTS: Accuracy was higher for the trained group than the untrained group using US guidance (1 mm versus 4 mm, p = 0.001), but not when using AR guidance (4 mm vs. 4 mm, p = 0.76). All operators combined, no significant difference was found concerning accuracy between US and AR guidance (2 mm vs. 4 mm, p = 0.09), but planning time and puncture time were significantly shorter using AR (respectively, 15.1 s vs. 74 s, p < 0.001; 16.1 s vs. 59 s; p < 0.001). CONCLUSION: Untrained and trained operators obtained comparable accuracy in percutaneous punctures when using AR guidance whereas US performance was better in the experienced group. All operators together, accuracy was similar between US and AR guidance, but shorter planning time, puncture time were found for AR guidance.

Association of LI-RADS and Histopathologic Features with Survival in Patients with Solitary Resected Hepatocellular Carcinoma.

Background Both Liver Imaging Reporting and Data System (LI-RADS) and histopathologic features provide prognostic information in patients with hepatocellular carcinoma (HCC), but whether LI-RADS is independently associated with survival is uncertain. Purpose To assess the association of LI-RADS categories and features with survival outcomes in patients with solitary resected HCC. Materials and Methods This retrospective study included patients with solitary resected HCC from three institutions examined with preoperative contrast-enhanced CT and/or MRI between January 2008 and December 2019. Three independent readers evaluated the LI-RADS version 2018 categories and features. Histopathologic features including World Health Organization tumor grade, microvascular and macrovascular invasion, satellite nodules, and tumor capsule were recorded. Overall survival and disease-free survival were assessed with Cox regression models. Marginal effects of nontargetoid features on survival were estimated using propensity score matching. Results A total of 360 patients (median age, 64 years [IQR, 56-70 years]; 280 male patients) were included. At CT and MRI, the LI-RADS LR-M category was associated with increased risk of recurrence (CT: hazard ratio [HR] = 1.83 [95% CI: 1.26, 2.66], P = .001; MRI: HR = 2.22 [95% CI: 1.56, 3.16], P < .001) and death (CT: HR = 2.47 [95% CI: 1.72, 3.55], P < .001; MRI: HR = 1.80 [95% CI: 1.32, 2.46], P < .001) independently of histopathologic features. The presence of at least one nontargetoid feature was associated with an increased risk of recurrence (CT: HR = 1.80 [95% CI: 1.36, 2.38], P < .001; MRI: HR = 1.93 [95% CI: 1.81, 2.06], P < .001) and death (CT: HR = 1.51 [95% CI: 1.10, 2.07], P < .010) independently of histopathologic features. In matched samples, recurrence was associated with the presence of at least one nontargetoid feature at CT (HR = 2.06 [95% CI: 1.15, 3.66]; P = .02) or MRI (HR = 1.79 [95% CI: 1.01, 3.20]; P = .048). Conclusion In patients with solitary resected HCC, LR-M category and nontargetoid features were negatively associated with survival independently of histopathologic characteristics. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kartalis and Grigoriadis in this issue.

Whole-Body Positron Emission Tomography with 18F-Fluorodeoxyglucose/Magnetic Resonance Imaging as a Screening Tool for the Detection of Malignant Transformation in Individuals with Neurofibromatosis Type 1.

Malignant peripheral nerve sheath tumors (MPNSTs) are the leading cause of death in patients with neurofibromatosis type 1. They can result from premalignant neurofibromas, including neurofibromas with atypia and atypical neurofibromatous neoplasms of uncertain biologic potential. Some phenotypic characteristics have been described as associated with their development. The aim of this study was to outline our use of whole-body positron emission tomography with 18F-fluorodeoxyglucose/magnetic resonance imaging in adults with neurofibromatosis type 1, especially in the screening of asymptomatic individuals with a higher risk of developing an MPNST, and to study its impact on neurofibroma classification (malignant vs premalignant) and MPNST staging over time. Individuals with neurofibromatosis type 1 who underwent a positron emission tomography with 18F-fluorodeoxyglucose/magnetic resonance imaging between 2017 and 2021 were included, analyzing separately the screened population. Maximum standard uptake value and diffusion-weighted imaging were assessed. Biopsy/surgery confirmed the diagnosis. In all, 345 positron emission tomography with 18F-fluorodeoxyglucose/magnetic resonance imaging were performed in 241 patients, including 149 asymptomatic (62%) but at-risk patients. Eight MPNSTs in 8 screened individuals (5%), 6 neurofibromas with atypia in 4 individuals (3%), and 29 atypical neurofibromatous neoplasms of uncertain biologic potential in 23 individuals (15%) were diagnosed. Over time, the proportion of grade 3 MPNST and the malignant/premalignant ratio in screened individuals significantly decreased (P = .03 and P < .001, respectively). This study emphasizes the diagnostic and screening performances of whole-body positron emission tomography with 18F-fluorodeoxyglucose/magnetic resonance imaging in adults with neurofibromatosis type 1.

Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution.

PURPOSE: The purpose of this study was to propose a deep learning-based approach to detect pulmonary embolism and quantify its severity using the Qanadli score and the right-to-left ventricle diameter (RV/LV) ratio on three-dimensional (3D) computed tomography pulmonary angiography (CTPA) examinations with limited annotations. MATERIALS AND METHODS: Using a database of 3D CTPA examinations of 1268 patients with image-level annotations, and two other public datasets of CTPA examinations from 91 (CAD-PE) and 35 (FUME-PE) patients with pixel-level annotations, a pipeline consisting of: (i), detecting blood clots; (ii), performing PE-positive versus negative classification; (iii), estimating the Qanadli score; and (iv), predicting RV/LV diameter ratio was followed. The method was evaluated on a test set including 378 patients. The performance of PE classification and severity quantification was quantitatively assessed using an area under the curve (AUC) analysis for PE classification and a coefficient of determination (R²) for the Qanadli score and the RV/LV diameter ratio. RESULTS: Quantitative evaluation led to an overall AUC of 0.870 (95% confidence interval [CI]: 0.850-0.900) for PE classification task on the training set and an AUC of 0.852 (95% CI: 0.810-0.890) on the test set. Regression analysis yielded R² value of 0.717 (95% CI: 0.668-0.760) and of 0.723 (95% CI: 0.668-0.766) for the Qanadli score and the RV/LV diameter ratio estimation, respectively on the test set. CONCLUSION: This study shows the feasibility of utilizing AI-based assistance tools in detecting blood clots and estimating PE severity scores with 3D CTPA examinations. This is achieved by leveraging blood clots and cardiac segmentations. Further studies are needed to assess the effectiveness of these tools in clinical practice.

Applicability of Bosniak 2019 for renal mass classification on portal venous phase at the era of spectral CT imaging using rapid kV-switching dual-energy CT.

OBJECTIVES: To evaluate the applicability of Bosniak 2019 criteria on a monophasic portal venous phase using rapid kilovoltage-switching DECT (rsDECT). MATERIALS AND METHODS: One hundred twenty-seven renal masses assessed on rsDECT were included, classified according to Bosniak 2019 classification using MRI as the reference standard. Using the portal venous phase, virtual monochromatic images at 40, 50, and 77 keV; virtual unenhanced (VUE) images; and iodine map images were reconstructed. Changes in attenuation values between VUE and 40 keV, 50 keV, and 77 keV measurements were computed and respectively defined as ∆HU40keV, ∆HU50keV, and ∆HU77keV. The values of ∆HU40keV, ∆HU50keV, and ∆HU77keV thresholds providing the optimal diagnostic performance for the detection of internal enhancement were determined using Youden index. RESULTS: Population study included 25 solid renal masses (25/127, 20%) and 102 cystic renal masses (102/127, 80%). To differentiate solid to cystic masses, the specificity of the predefined 20 HU threshold reached 88% (95%CI: 82, 93) using ∆HU77keV and 21% (95%CI: 15, 28) using ∆HU40keV. The estimated optimal threshold of attenuation change was 19 HU on ∆HU77keV, 69 HU on ∆HU50eV, and 111 HU on ∆HU40eV. The rsDECT classification was highly similar to that of MRI for solid renal masses (23/25, 92%) and for Bosniak 1 masses (62/66, 94%). However, 2 hyperattenuating Bosniak 2 renal masses (2/26, 8%) were classified as solid renal masses on rsDECT. CONCLUSION: DECT is a promising tool for Bosniak classification particularly to differentiate solid from Bosniak I-II cyst. However, known enhancement thresholds must be adapted especially to the energy level of virtual monochromatic reconstructions. CLINICAL STATEMENT: DECT is a promising tool for Bosniak classification; however, known enhancement thresholds must be adapted according to the types of reconstructions used and especially to the energy level of virtual monochromatic reconstructions. KEY POINTS: • To differentiate solid to cystic renal masses, predefined 20 HU threshold had a poor specificity using 40 keV virtual monochromatic images. • Most of Bosniak 1 masses according to MRI were also classified as Bosniak 1 on rapid kV-switching dual-energy CT (rsDECT). • Bosniak 2 hyperattenuating renal cysts mimicked solid lesion on rsDECT.

Pushing MP2RAGE boundaries: Ultimate time-efficient parameterization combined with exhaustive T1 synthetic contrasts.

PURPOSE: MP2RAGE parameter optimization is redefined to allow more time-efficient MR acquisitions, whereas the T1 -based synthetic imaging framework is used to obtain on-demand T1 -weighted contrasts. Our aim was to validate this concept on healthy volunteers and patients with multiple sclerosis, using plug-and-play parallel-transmission brain imaging at 7 T. METHODS: A "time-efficient" MP2RAGE sequence was designed with optimized parameters including TI and TR set as small as possible. Extended phase graph formalism was used to set flip-angle values to maximize the gray-to-white-matter contrast-to-noise ratio (CNR). Several synthetic contrasts (UNI, EDGE, FGATIR, FLAWSMIN , FLAWSHCO ) were generated online based on the acquired T1 maps. Experimental validation was performed on 4 healthy volunteers at various spatial resolutions. Clinical applicability was evaluated on 6 patients with multiple sclerosis, scanned with both time-efficient and conventional MP2RAGE parameterizations. RESULTS: The proposed time-efficient MP2RAGE protocols reduced acquisition time by 40%, 30%, and 19% for brain imaging at (1 mm)3 , (0.80 mm)3 and (0.65 mm)3 , respectively, when compared with conventional parameterizations. They also provided all synthetic contrasts and comparable contrast-to-noise ratio on UNI images. The flexibility in parameter selection allowed us to obtain a whole-brain (0.45 mm)3 acquisition in 19 min 56 s. On patients with multiple sclerosis, a (0.67 mm)3 time-efficient acquisition enhanced cortical lesion visualization compared with a conventional (0.80 mm)3 protocol, while decreasing the scan time by 15%. CONCLUSION: The proposed optimization, associated with T1 -based synthetic contrasts, enabled substantial decrease of the acquisition time or higher spatial resolution scans for a given time budget, while generating all typical brain contrasts derived from MP2RAGE.

Glomerular Filtration Rate Measured Based on Iomeprol Clearance Assessed at CT Urography in Living Kidney Donor Candidates.

Background Estimating glomerular filtration rate (GFR) from serum creatinine can be inaccurate, and current procedures for measuring GFR are time-consuming and cumbersome. Purpose To develop a method for measuring GFR based on iomeprol clearance assessed at CT urography in kidney donor candidates and compare this with iohexol clearance (reference standard for measuring GFR). Materials and Methods This cross-sectional retrospective study included data from kidney donor candidates who underwent both iohexol clearance and CT urography between July 2016 and October 2022. CT-measured GFR was calculated as the iomeprol excretion rate in the urinary system between arterial and excretory phases (Hounsfield units times milliliters per minute) divided by a surrogate for serum iomeprol concentration in the aorta at the midpoint (in Hounsfield units). Performance of CT-measured GFR was assessed with use of mean bias (mean difference between CT-measured GFR and iohexol clearance), precision (the distance between quartile 1 and quartile 3 of the bias [quartile 3 minus quartile 1], with a small value indicating high precision), and accuracy (percentage of CT-measured GFR values falling within 10%, 20%, and 30% of iohexol clearance values). Intraobserver agreement was assessed for 30 randomly selected individuals with the Lin concordance correlation coefficient. Results A total of 75 kidney donor candidates were included (mean age, 51 years ± 13 [SD]; 45 female). The CT-measured GFR was unbiased (1.1 mL/min/1.73 m2 [95% CI: -1.9, 4.1]) and highly precise (16.2 mL/min/1.73 m2 [quartiles 1 to 3, -6.6 to 9.6]). The accuracy of CT-measured GFR within 10%, 20%, and 30% was 61.3% (95% CI: 50.3, 72.4), 88.0% (95% CI: 80.7, 95.4), and 100%, respectively. Concordance between CT-based GFR measurements taken 2 months apart was almost perfect (correlation coefficient, 0.99 [95% CI: 0.98, 0.99]). Conclusion In living kidney donors, GFR measured based on iomeprol clearance assessed at CT urography showed good agreement with GFR measured based on iohexol clearance. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Davenport in this issue.

Focal loss of mural stratification as a radiological predictor for small bowel adenocarcinoma in Crohn's disease.

AIM: Patients with Crohn's disease (CD) are at higher risk of small bowel adenocarcinoma (SBA). We aimed to identify radiological predictors of SBA in CD. METHODS: We conducted a retrospective case-control study at two tertiary inflammatory bowel disease centers and identified CD patients diagnosed with SBA between 2003 and 2019. Patients were matched with up to four controls. Pre-operative imaging (magnetic resonance imaging (MRI) or computed tomography (CT)) were reviewed by three gastrointestinal radiologists. RESULTS: Nineteen patients with CD-associated SBA with a mean age of 54.9 and 32 matched controls were included. Mean length of small bowel involvement was 216 (± 188) mm in the SBA group versus 156 (± 167) mm in the control group (p = 0.76). Only 11.8 % of cases had a diagnosis of SBA made preoperatively. In univariate analysis, focal loss of mural stratification (odds ratio [OR], 11; 95%CI, 2.43-49.5, p = 0.002), and wall thickening (OR, 1.32; 95%CI, 1.05-1.66, p = 0.02) were significantly associated with SBA. After adjustment, focal loss of mural stratification was the only independent risk factor (OR, 11; 95 % CI, 2.43-49.5, p = 0.002). CONCLUSIONS: Focal loss of mural stratification was identified as a predictor of CD-associated SBA, which should be described in imaging reports and further validated.

The liver in sickle cell disease.

Liver involvement in SCD patients is frequent but often misdiagnosed or underestimated, except in case of advanced liver diseases. Because of so far poorly recognized forms of chronic SCD-related vascular injury that can silently evolved towards end stages or facilitate ACLF, any persisting liver function tests abnormalities should be carefully investigated, following the above proposed algorithm. Work up and management must be considered multidisciplinary in relationship with a Hepatologist. Early SCD hepatopathy should prompt revision of SCD management to prevent further liver injury and decompensation, discussing transfusion exchanges and hydro urea when not yet initiated, and control for any cofactor of liver injury. The role of HSCT in early SCD hepatopathies also deserves evaluation. In advanced SCD hepatopathies, liver transplantation, which has been rarely performed so far, is the only therapeutic option associated with improved survival. It should definitely be discussed- either electively in case of decompensation in SCD cirrhosis or jaundice/recurrent cholangitis in cholestatic diseases, with excellent outcome, - or emergently in case of ALF or ACLF with more mitigate results. To improve knowledge and management of SCD liver diseases, creation of national and international registries, as well as longitudinal observational cohorts are encouraged.

Automated CT LI-RADS v2018 scoring of liver observations using machine learning: A multivendor, multicentre retrospective study.

Background & Aims: Assessment of computed tomography (CT)/magnetic resonance imaging Liver Imaging Reporting and Data System (LI-RADS) v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. We assessed the performance and added-value of a machine learning (ML)-based algorithm in assessing CT LI-RADS major features and categorisation of liver observations compared with qualitative assessment performed by a panel of radiologists. Methods: High-risk patients as per LI-RADS v2018 with pathologically proven liver lesions who underwent multiphase contrast-enhanced CT at diagnosis between January 2015 and March 2019 in seven centres in five countries were retrospectively included and randomly divided into a training set (n = 84 lesions) and a test set (n = 345 lesions). An ML algorithm was trained to classify non-rim arterial phase hyperenhancement, washout, and enhancing capsule as present, absent, or of uncertain presence. LI-RADS major features and categories were compared with qualitative assessment of two independent readers. The performance of a sequential use of the ML algorithm and independent readers were also evaluated in a triage and an add-on scenario in LR-3/4 lesions. The combined evaluation of three other senior readers was used as reference standard. Results: A total of 318 patients bearing 429 lesions were included. Sensitivity and specificity for LR-5 in the test set were 0.67 (95% CI, 0.62-0.72) and 0.91 (95% CI, 0.87-0.96) respectively, with 242 (70.1%) lesions accurately categorised. Using the ML algorithm in a triage scenario improved the overall performance for LR-5. (0.86 and 0.93 sensitivity, 0.82 and 0.76 specificity, 78% and 82.3% accuracy for the two independent readers). Conclusions: Quantitative assessment of CT LI-RADS v2018 major features is feasible and diagnoses LR-5 observations with high performance especially in combination with the radiologist's visual analysis in patients at high-risk for HCC. Impact and implications: Assessment of CT/MRI LI-RADS v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. Rather than replacing radiologists, our results highlight the potential benefit from the radiologist-artificial intelligence interaction in improving focal liver lesions characterisation by using the developed algorithm as a triage tool to the radiologist's visual analysis. Such an AI-enriched diagnostic pathway may help standardise and improve the quality of analysis of liver lesions in patients at high risk for HCC, especially in non-expert centres in liver imaging. It may also impact the clinical decision-making and guide the clinician in identifying the lesions to be biopsied, for instance in patients with multiple liver focal lesions.

Development and validation of a new equation based on plasma creatinine and muscle mass assessed by CT scan to estimate glomerular filtration rate: a cross-sectional study.

Background: Inter-individual variations of non-glomerular filtration rate (GFR) determinants of serum creatinine, such as muscle mass, account for the imperfect performance of estimated GFR (eGFR) equations. We aimed to develop an equation based on creatinine and total lumbar muscle cross-sectional area measured by unenhanced computed tomography scan at the third lumbar vertebra. Methods: The muscle mass-based eGFR (MMB-eGFR) equation was developed in 118 kidney donor candidates (iohexol clearance) using linear regression. Validation cohorts included 114 healthy subjects from another center (51Cr-EDTA clearance, validation population 1), 55 patients with chronic diseases (iohexol, validation population 2), and 60 patients with highly discordant creatinine and cystatin C-based eGFR, thus presumed to have atypical non-GFR determinants of creatinine (51Cr-EDTA, validation population 3). Mean bias was the mean difference between eGFR and measured GFR, precision the standard deviation (SD) of the bias, and accuracy the percentage of eGFR values falling within 20% and 30% of measured GFR. Results: In validation population 1, performance of MMB-eGFR was not different from those of CKD-EPICr2009 and CKD-EPICr2021. In validation population 2, MMB-eGFR was unbiased and displayed better precision than CKD-EPICr2009, CKD-EPICr2021 and EKFC (SD of the biases: 13.1 vs 16.5, 16.8 and 15.9 mL/min/1.73 m2). In validation population 3, MMB-eGFR had better precision and accuracy {accuracy within 30%: 75.0% [95% confidence interval (CI) 64.0-86.0] vs 51.5% (95% CI 39.0-64.3) for CKD-EPICr2009, 43.3% (95% CI 31.0-55.9) for CKD-EPICr2021, and 53.3% (95% CI 40.7-66.0) for EKFC}. Difference in bias between Black and white subjects was -2.1 mL/min/1.73 m2 (95% CI -7.2 to 3.0), vs -8.4 mL/min/1.73 m2 (95% CI -13.2 to -3.6) for CKD-EPICr2021. Conclusion: MMB-eGFR displayed better performances than equations based on demographics, and could be applied to subjects of various ethnic backgrounds.

Anterior Versus Classical Approach During Right Hepatectomy for Hepatocellular Carcinoma: Inverse Propensity Score Weighted Analysis.

BACKGROUND: Eastern data highlight the oncological benefits of the anterior approach (AA) during right hepatectomy (RH) for hepatocellular carcinoma (HCC). However, to our knowledge, previous western data on this topic are scarce. In this study, the oncological outcomes of AA and classical approach (CA) during RH for HCC were compared. METHODS: A retrospective inverse propensity score-weighted fashion (IPTW) case-control study was performed in two French hepatobiliary surgery departments. Overall survival (OS), disease-free survival (DFS), and early recurrence rate (within 2 years after surgery) were analyzed. RESULTS: Survival analysis was performed for 114 patients (CA group,60 patients; AA group, 54 patients). Before IPTW adjustment, the 3-year DFS rates were 29.4% (AA group) and 44% (CA group), respectively. No significant differences were found in DFS (HR = 1.1, 95%CI:0.62-1.9, p = 0.77) and OS (HR = 1.2, 95%CI:0.54-2.6, p = 0.66). After IPTW, DFS and OS analyses showed no differences between the two groups (p = 0.77 and p = 0.46, respectively). Early recurrence rates were similar before and after IPTW. Satellite nodules were the only significant independent risk factor for recurrence. CONCLUSION: AA and CA did not result in significant differences in DFS, OS, or early recurrence after right hepatectomy for HCC before and after IPTW.

Impact of COVID-19 on the management of hepatocellular carcinoma in a high-prevalence area: What's new 12 months later?

INTRODUCTION AND OBJECTIVES: The lockdown policy introduced in 2020 to minimize the spread of the COVID-19 pandemic, significantly affected the management and care of patients affected by hepatocellular carcinoma (HCC). The aim of this follow-up study was to determine the 12 months impact of the COVID-19 pandemic on the cohort of patients affected by HCC during the lockdown, within six French academic referral centers in the metropolitan area of Paris. MATERIALS AND METHODS: We performed a 12 months follow-up of the cross-sectional study cohort included in 2020 on the management of patients affected by HCC during the first six weeks of the COVID-19 pandemic (exposed), compared to the same period in 2019 (unexposed). Overall survival were compared between the groups. Predictors of mortality were analysed with Cox regression. RESULTS: From the initial cohort, 575 patients were included (n = 263 Exposed_COVID, n = 312 Unexposed_COVID). Overall and disease free survival at 12 months were 59.9 ± 3.2% vs 74.3 ± 2.5% (p<0.001) and 40.2 ± 3.5% vs 63.5 ± 3.1% (p<0.001) according to the period of exposure (Exposed_COVID vs Unexposed_COVID, respectively). Adjusted Cox regression revealed that the period of exposure (Exposed_COVID HR: 1.79, 95%CI (1.36, 2.35) p<0.001) and BCLC stage B, C and D (BCLC B HR: 1.82, 95%CI (1.07, 3.08) p = 0.027 - BCLC C HR: 1.96, 95%CI (1.14, 3.38) p = 0.015 - BCLC D HR: 3.21, 95%CI (1.76, 5.85) p<0.001) were predictors of death. CONCLUSIONS: Disruption of routine healthcare services because of the pandemic translated to reduced 1 year overall and disease-free survival among patients affected by HCC, in the metropolitan area of Paris, France.

Deep learning-assisted model-based off-resonance correction for non-Cartesian SWI.

PURPOSE: Patient-induced inhomogeneities in the static magnetic field cause distortions and blurring (off-resonance artifacts) during acquisitions with long readouts such as in SWI. Conventional versatile correction methods based on extended Fourier models are too slow for clinical practice in computationally demanding cases such as 3D high-resolution non-Cartesian multi-coil acquisitions. THEORY: Most reconstruction methods can be accelerated when performing off-resonance correction by reducing the number of iterations, compressed coils, and correction components. Recent state-of-the-art unrolled deep learning architectures could help but are generally not adapted to corrupted measurements as they rely on the standard Fourier operator in the data consistency term. The combination of correction models and neural networks is therefore necessary to reduce reconstruction times. METHODS: Hybrid pipelines using UNets were trained stack-by-stack over 99 SWI 3D SPARKLING 20-fold accelerated acquisitions at 0.6 mm isotropic resolution using different off-resonance correction methods. Target images were obtained using slow model-based corrections based on self-estimated Δ B 0 $$ \Delta {B}_0 $$ field maps. The proposed strategies, tested over 11 volumes, are compared to model-only and network-only pipelines. RESULTS: The proposed hybrid pipelines achieved scores competing with two to three times slower baseline methods, and neural networks were observed to contribute both as pre-conditioner and through inter-iteration memory by allowing more degrees of freedom over the model design. CONCLUSION: A combination of model-based and network-based off-resonance correction was proposed to significantly accelerate conventional methods. Different promising synergies were observed between acceleration factors (iterations, coils, correction) and model/network that could be expanded in the future.

Detection and quantification of pulmonary embolism with artificial intelligence: The SFR 2022 artificial intelligence data challenge.

PURPOSE: In 2022, the French Society of Radiology together with the French Society of Thoracic Imaging and CentraleSupelec organized their 13th data challenge. The aim was to aid in the diagnosis of pulmonary embolism, by identifying the presence of pulmonary embolism and by estimating the ratio between right and left ventricular (RV/LV) diameters, and an arterial obstruction index (Qanadli's score) using artificial intelligence. MATERIALS AND METHODS: The data challenge was composed of three tasks: the detection of pulmonary embolism, the RV/LV diameter ratio, and Qanadli's score. Sixteen centers all over France participated in the inclusion of the cases. A health data hosting certified web platform was established to facilitate the inclusion process of the anonymized CT examinations in compliance with general data protection regulation. CT pulmonary angiography images were collected. Each center provided the CT examinations with their annotations. A randomization process was established to pool the scans from different centers. Each team was required to have at least a radiologist, a data scientist, and an engineer. Data were provided in three batches to the teams, two for training and one for evaluation. The evaluation of the results was determined to rank the participants on the three tasks. RESULTS: A total of 1268 CT examinations were collected from the 16 centers following the inclusion criteria. The dataset was split into three batches of 310, 580 and 378 C T examinations provided to the participants respectively on September 5, 2022, October 7, 2022 and October 9, 2022. Seventy percent of the data from each center were used for training, and 30% for the evaluation. Seven teams with a total of 48 participants including data scientists, researchers, radiologists and engineering students were registered for participation. The metrics chosen for evaluation included areas under receiver operating characteristic curves, specificity and sensitivity for the classification task, and the coefficient of determination r2 for the regression tasks. The winning team achieved an overall score of 0.784. CONCLUSION: This multicenter study suggests that the use of artificial intelligence for the diagnosis of pulmonary embolism is possible on real data. Moreover, providing quantitative measures is mandatory for the interpretability of the results, and is of great aid to the radiologists especially in emergency settings.