Sung Eun Rha

Purpose: This study evaluated serial ultrasonographic (US) changes during defibrotide therapy for sinusoidal obstruction syndrome (SOS) after hematopoietic stem cell transplantation, identifying parameters whose temporal trajectories differed by treatment response.Methods: This retrospective study included adults treated with defibrotide for SOS between January 2015 and August 2024 with baseline US and at least one follow-up US examination. Response was defined a priori as total bilirubin <2 mg/dL with resolution of SOS-related multiorgan dysfunction. US was repeated weekly until response assessment. HokUS-10 parameters and additional US findings were analyzed using generalized estimating equations and linear mixed-effects models to test the group-by-time interaction. The fully adjusted model was primary, with a minimal model used for sensitivity analysis. P-values were adjusted using the Benjamini-Hochberg procedure.Results: Among 39 patients (23 responders [59.0%] and 16 non-responders [41.0%]; median defibrotide duration, 23 days), only HokUS-10 score showed a significant group-by-time interaction after multiple-testing adjustment in both models, declining more rapidly among responders (fully adjusted model: β=−0.048; 95% confidence interval [CI], −0.083 to −0.013; P=0.017; minimal model: β=−0.053; 95% CI, −0.087 to −0.019; P=0.006). The odds of hepatofugal portal vein flow decreased faster among responders in the fully adjusted model (odds ratio [OR], 0.92; 95% CI, 0.85 to 0.99; P=0.032), whereas the association was directionally similar but non-significant in the minimal model (OR, 0.95; 95% CI, 0.88 to 1.02; P=0.162). Hepatic artery resistive index ≥0.75 was not significantly associated with differential temporal change.Conclusion: Serial US trajectories differed by treatment response. Longitudinal HokUS-10 changes may help distinguish defibrotide responders from non-responders.

Background: Deep learning reconstruction can shorten breath‐hold MRI for liver proton density fat fraction (DL‐PDFF), but agreement with conventional PDFF (Conv‐PDFF) and the impact of measurement approach (regional vs. whole‐liver segmentation) remain unclear. Purpose: To evaluate linearity and agreement of DL‐PDFF with Conv‐PDFF and MR spectroscopy PDFF (MRS‐PDFF), and reconstruction‐dependent whole‐liver distribution metrics. Study Type: Retrospective. Population: Fat phantom three vials per nominal fat mass fraction (27.86%, 18.32%, and 9.12%); 96 adults (53 males; median age, 64). Field Strength/Sequence: 3 T; Chemical shift‐encoded multi‐echo gradient‐echo; acquisition time, 10 s (DL‐PDFF; acceleration factor [AF], 6) and 14 s (Conv‐PDFF; AF, 4). Assessment: Central region of interest (ROI) for phantom PDFF; In vivo, single ROI by radiology technologists, multiple ROIs by a resident and a medical student, and automated whole‐liver segmentation, yielding voxel‐based histograms and residual fitting error; inter‐observer agreement. Statistical Tests: Wilcoxon signed‐rank tests, linear regression (slope/intercept/ R ² ), Bland–Altman bias and 95% limits of agreement (LoA) with proportional‐bias slope ( β ), Lin's concordance correlation coefficient (CCC), Hodges–Lehmann method, and Spearman ( ρ ). Two‐sided p < 0.05. Results: DL‐PDFF versus Conv‐PDFF showed excellent phantom linearity ( R ² = 1.00). In patients, within the same approach: single ROI (bias, −0.24%; widest LoA, −2.76 to 2.28; CCC, 0.94); multiple ROIs (bias, −0.002; LoA, −1.04 to 1.04; CCC, 0.99); and whole‐liver segmentation (bias, 0.12; LoA, −0.54 to 0.78; CCC, 0.99). Cross‐method comparison (DL‐PDFF segmentation vs. Conv‐PDFF multiple ROIs) showed larger bias (0.57; LoA, −0.77 to 1.91; CCC, 0.97). Against MRS‐PDFF, bias was similar (−0.05 to −0.02; LoA, −3.00 to 2.96). For DL‐PDFF, whole‐liver SD (Hodges–Lehmann difference, 0.55%; ρ = 0.95) and residual fitting error significantly higher (median, 2.80 vs. 1.92). Inter‐observer agreement was high (CCC, 0.99). Data Conclusion: DL‐PDFF demonstrated high agreement with Conv‐PDFF while reducing acquisition time. However, measurement approach (segmentation vs. ROI) contributes larger systematic differences relevant to longitudinal and cross‐study comparisons. Evidence Level: 3. Stage of Technical Efficacy: 2.

Background/Objectives: We comparatively evaluated the prognostic performance of the 2009 and 2023 International Federation of Gynecology and Obstetrics (FIGO) staging systems for early-stage endometrial cancer based on histological subtype stratification. Methods: A retrospective cohort of 472 patients with FIGO 2009 stage I–II between 2004 and 2019 was analyzed. Patients were restaged using both systems. Overall survival (OS) and recurrence-free survival (RFS) were determined according to histopathological aggressiveness. Kaplan–Meier survival analysis with log-rank testing compared the performance of the systems. Cox proportional hazards regression identified independent prognostic factors. A hypothetical modification of the FIGO 2023 system was evaluated for aggressive subtypes. Results: In all, 388 patients had nonaggressive histology, and 84 patients had aggressive histology. For cases of nonaggressive histology, FIGO 2023 demonstrated superior prognostic discrimination for OS and RFS (p < 0.05), whereas FIGO 2009 showed significant stratification for OS (p < 0.001) but not RFS (p = 0.149). For cases of aggressive histology, FIGO 2009 showed significant stratification for RFS (p = 0.017) but not OS (p = 0.31), whereas FIGO 2023 showed no significant stratification for either endpoint. The hypothetical modification of the FIGO 2023 staging system showed significantly improved discrimination for RFS (p = 0.019) but not OS. Multivariate analysis identified age and lymphovascular space invasion as independent prognostic factors in nonaggressive cancers, whereas cervical stromal involvement was significant in aggressive subtypes. Conclusions: The prognostic utility of the FIGO staging system is histology dependent. Although FIGO 2023 offers enhanced risk stratification for nonaggressive endometrial cancers, its discriminatory power for aggressive subtypes remains limited, indicating the need for histology-specific refinements of future staging frameworks.

Objectives This study aimed to evaluate the diagnostic performance of Magnetic Resonance Imaging (MRI) for staging patients with International Federation of Gynecology and Obstetrics (FIGO) stage I endometrial cancer, by comparing the original 2009 system with the revised 2023 system. Materials and methods This retrospective study included 432 patients (mean age, 54.9 years) with histopathologically confirmed FIGO 2009 stage I endometrial cancer who underwent preoperative MRI. The patients were categorized into non-aggressive (n = 364; low-grade endometrioid histology) and aggressive (n = 68; grade 3 endometrioid or non-endometrioid histology, including serous, clear cell carcinoma, and carcinosarcoma) tumor groups. Preoperative MRI-based assessment of myometrial invasion was compared with histopathological results to assess the myometrial invasion depth, which was classified as no invasion, superficial invasion (< 50%), and deep invasion (≥ 50%). Diagnostic accuracy, sensitivity, specificity, and agreement of preoperative MRI-based staging determination were calculated for both FIGO 2009 and 2023 systems. Results In non-aggressive tumors, the 2009 FIGO staging demonstrated superior accuracy (kappa 0.82, 95% CI 0.74–0.89) compared to the 2023 staging (kappa 0.66, 95% CI 0.59–0.74), with a statistically significant difference (p = 0.0029). MRI performance varied across invasion depths, with excellent diagnostic accuracy for deep myometrial invasion (sensitivity, 87.0%; specificity, 95.9%). For aggressive tumors, no significant difference was observed between the two staging systems (p = 0.160). Subgroup analysis demonstrated that the presence of lymphovascular space invasion did not result in statistically significant differences in diagnostic agreement between MRI and pathological staging (p = 0.452). Conclusion This study provides evidence that 2023 FIGO staging revisions present measurable challenges for MRI-based staging accuracy, particularly in the assessment of non-aggressive endometrial tumors confined to the uterus. Despite these challenges, MRI maintains reliable diagnostic performance for detecting deep myometrial invasion in uterus-confined disease, supporting its continued utility in preoperative staging protocols. Key take‑home Radiologists should recognize the statistically significant reduction in diagnostic accuracy for detecting the absence of myometrial invasion under FIGO 2023 criteria, particularly in non-aggressive endometrioid tumors, and consider integrating complementary quantitative imaging parameters or molecular biomarkers to enhance the preoperative staging precision.

A commercial MRI-based deep learning algorithm for prostate cancer detection showed greater positive predictive value, despite its lower sensitivity, potentially allowing it to assist radiologists in biopsy planning.

Kim H, et al. Korean J Radiol. 2025 Apr;26:e48. https://doi.org/10.3348/kjr.2024.1228

This study evaluated the magnetic resonance imaging (MRI) findings of endometrial cancer (EC) patients and identified differences based on risk group and molecular classification. The study involved a total of 175 EC patients. The MRI data were retrospectively reviewed and compared based on the risk of recurrence. Additionally, the associations between imaging phenotypes and genomic signatures were assessed. The low-risk and non-low-risk groups (intermediate, high-intermediate, high, metastatic) showed significant differences in tumor diameter (p < 0.001), signal intensity and heterogeneity on diffusion-weighted imaging (DWI) (p = 0.003), deep myometrial invasion (involvement of more than 50% of the myometrium), cervical invasion (p < 0.001), extrauterine extension (p = 0.002), and lymphadenopathy (p = 0.003). Greater diffusion restriction and more heterogeneity on DWI were exhibited in the non-low-risk group than in the low-risk group. Deep myometrial invasion, cervical invasion, extrauterine extension, lymphadenopathy, recurrence, and stage discrepancy were more common in the non-low-risk group (p < 0.001). A significant difference in microsatellite stability status was observed in the heterogeneity of the contrast-enhanced T1-weighted images (p = 0.027). However, no significant differences were found in MRI parameters related to TP53 mutation. MRI features can be valuable predictors for differentiating risk groups in patients with EC. However, further investigations are needed to explore the imaging markers based on molecular classification.