Background/Objectives: Segmental non-mass enhancement (NME) is the breast MRI distribution pattern with the highest positive predictive value (PPV) for malignancy. Despite its diagnostic relevance, its imaging characteristics have rarely been examined in isolation, leaving uncertainty in clinical practice. This multicenter study aimed to evaluate multiparametric MRI features—including internal enhancement pattern, dynamic contrast enhancement (DCE) kinetics, and diffusion restriction—in segmental NME to identify malignancy predictors. Methods: This retrospective cohort reviewed 14,834 breast MRI reports from five institutions (September 2017–February 2024), identifying 103 women (mean age, 44.4 ± 9.9 years) with segmental NME (70 malignant, 33 benign). MRI was performed at 1.5T or 3T using standardized protocols. Two breast radiologists, blinded to pathology, assessed internal enhancement, DCE kinetics, diffusion restriction, and short tau inversion recovery (STIR) features according to BI-RADS. Statistical analyses included chi-square/Fisher’s tests and logistic regression. Results: Clustered ring enhancement (CRE) was significantly associated with malignancy (p = 0.004). Fast initial-phase enhancement (p < 0.001) and delayed-phase washout (p = 0.011) also correlated with malignancy. On multivariate analysis, fast initial-phase enhancement remained an independent predictor (odds ratio [OR] = 5.133, p = 0.031), whereas slow enhancement predicted benignity (OR = 0.194, p = 0.020). Histologies included ductal carcinoma in situ, invasive ductal carcinoma, granulomatous mastitis, and benign hyperplastic lesions. Conclusions: This study, focusing exclusively on segmental NME, identifies CRE, fast initial-phase enhancement, and washout kinetics as reliable imaging biomarkers. Incorporating these features into breast MRI interpretation may improve diagnostic accuracy, risk stratification, and management decisions.

Background/Objectives: Segmental non-mass enhancement (NME) is the breast MRI distribution pattern with the highest positive predictive value (PPV) for malignancy. Despite its diagnostic relevance, its imaging characteristics have rarely been examined in isolation, leaving uncertainty in clinical practice. This multicenter retrospective cohort study aimed to evaluate multiparametric MRI features—including internal enhancement pattern, dynamic contrast-enhanced (DCE) kinetics, and diffusion restriction—in segmental NME to identify malignancy predictors. Methods: This retrospective cohort review included 14,834 breast MRI reports from five institutions (September 2017–February 2024), identifying 103 women (mean age, 44.4 ± 9.9 years) with segmental NME (70 malignant, 33 benign). MRI was performed at 1.5 T or 3 T using standardized protocols. Two breast radiologists, blinded to pathology, assessed internal enhancement, DCE kinetics, diffusion restriction, and short tau inversion recovery (STIR) features according to BI-RADS. Statistical analyses included chi-square/Fisher’s tests and logistic regression. Results: Clustered ring enhancement (CRE) was significantly associated with malignancy (p = 0.004). Fast initial-phase enhancement (p < 0.001) and delayed-phase washout (p = 0.011) also correlated with malignancy. On multivariate analysis, fast initial-phase enhancement remained an independent predictor (odds ratio [OR] = 5.133, p = 0.031), whereas slow enhancement predicted benignity (OR = 0.194, p = 0.020). Histologies included ductal carcinoma in situ, invasive ductal carcinoma, granulomatous mastitis, and benign hyperplastic lesions. Conclusions: This study, focusing exclusively on segmental NME, identifies CRE, fast initial-phase enhancement, and washout kinetics as reliable imaging biomarkers. Incorporating these features into breast MRI interpretation may improve diagnostic accuracy, risk stratification, and management decisions.

Background/Objectives: The Ishak and Knodell classifications are used to evaluate fibrosis on percutaneous liver biopsy (PLB) in chronic hepatitis (CH). Hepatosteatosis (HS) can also be seen in PLBs performed on patients. In addition to PLB, the shear-wave elastography (SWE) technique is increasingly used to evaluate liver fibrosis. Whether the presence of HS contributed to fibrosis in CH cases that underwent PLB was evaluated by comparing SWE and Ishak–Knodell grades. Methods: CH cases were divided into three groups based on the presence of HS on biopsy and the percentage of HS (none, <10%, or ≥10%). Ishak–Knodell fibrosis grades and SWE values in kilopascal (kPa) were available for all included cases. Fibrosis scores and kPa values were compared within themselves and between groups for all three groups. Whether steatosis affected kPa results within the same fibrosis grades was evaluated. Results: There were 236 patients with CH: 109 (46.2%) had HS on liver biopsy, and 127 (53.8%) did not. Among the 109 patients with HS, 78 (71.5%) had pathological steatosis ≥ 10%. In all Ishak and Knodell grades (except F3), there was no significance between the liver stiffness values (kPa) of those with ≥10% HS and those with HS < 10%/none (p > 0.05). For the Ishak–Knodell F3 grade, there was a significant difference in both comparisons (p < 0.05). Conclusions: Liver kPa results are compatible with fibrosis grades, and SWE can be easily applied in the follow-up of CH patients with HS. In this way, unnecessary invasive procedures are prevented, and patient comfort can be maintained.

Background/Objectives: Standard mechanical compression applied during screening mammography is a primary barrier that reduces patient compliance. Current guidelines attempt to standardize compression based solely on the one-dimensional “breast thickness” measured by the device. This study aimed to investigate the effects of three-axis anatomical breast dimensions, applied compression force, menstrual cycle phases, and BI-RADS breast density patterns on pain scores during mammography within a comprehensive biomechanical model. Methods: This retrospective cohort study included 443 female patients who underwent routine screening or diagnostic mammography. Patients with a history of breast implants, lactation, or prior breast surgery that could alter tissue biomechanics were excluded. Maximum pain scores (1–10 on a Visual Analog Scale [VAS]) were recorded. Transverse, anteroposterior, and superoinferior breast biometric measurements for each patient were calculated using advanced radiological workstations. Data were analyzed using One-Way ANOVA and Multiple Linear Regression (OLS) models. Results: The mean age of the participants was 49.7 ± 9.4 years, the mean applied compression force was 62.4 ± 10.3 N, and the mean pain score was 2.03 ± 2.12 (range: 1–10). The multiple linear regression analysis was statistically significant overall (F = 2.516, p = 0.015). Having a BI-RADS Type D (extremely dense) breast pattern was identified as the strongest independent factor associated with an increased pain score (p = 0.082, coefficient = 1.219). Age showed a trend toward a negative effect on pain (p = 0.072), while compression force showed a trend toward a positive effect (p = 0.067). Conversely, breast thickness (p = 0.231) and the three-dimensional mean breast size index (p = 0.568) demonstrated no independent predictive power. The menstrual cycle phase did not reach independent significance in the multivariate regression model (p = 0.117); however, non-parametric univariate analysis revealed a significant difference in pain across hormonal groups (Kruskal–Wallis H = 10.04, p = 0.039), with actively menstruating and luteal-phase women reporting higher pain than menopausal women. Conclusions: The pain experienced during mammography depends on the internal fibroglandular architecture (elasticity and stiffness) of the tissue rather than its external volumetric dimensions. Notably, neither device-measured breast thickness nor manually calculated three-dimensional breast dimensions independently predicted pain, challenging the widespread assumption that breast size drives mammographic discomfort. “One-size-fits-all” or thickness-based compression strategies should be abandoned in routine practice. Instead, “personalized compression” protocols that prioritize patient comfort without compromising image quality should be developed, particularly for younger patients and those with BI-RADS Type D, and to a lesser extent Type C, density patterns.

Background/Objectives: This study aimed to evaluate the diagnostic performance and clinical decision-making impact of adding digital breast tomosynthesis (DBT) to two-dimensional digital mammography (2D DM) in a 100% biopsy-proven cohort of women with dense breast parenchyma (ACR types C and D), focusing on the relationship between tumor biology and radiologic conspicuity. Methods: This retrospective study analyzed 123 women (mean age 46.7 ± 9.9 years) with ACR type C (n = 67) or D (n = 56) breast density who underwent sequential 2D DM and DBT imaging, all with definitive histopathology (malignant, n = 78; high-risk, n = 8; benign, n = 37). A single expert radiologist performed independent readings of 2D DM alone and then the combined 2D DM + DBT dataset after a 4-week washout. Outcomes included sensitivity, specificity, PPV/NPV, lesion visibility (0–5 scale), and BI-RADS upgrade rate. Results: 2D DM + DBT significantly outperformed 2D DM alone in sensitivity (97.4% vs. 69.2%; p < 0.000001) and NPV (93.1% vs. 57.1%), with AUC improving from 0.727 to 0.922 (p < 0.001). Mean lesion visibility increased from 2.94 ± 1.19 to 4.52 ± 0.78 (p < 0.0001), with the largest gains for architectural distortion (100% sensitivity) and, notably, for Grade 1 tumors (delta +1.90), which reached the highest DBT visibility of any grade. Major BI-RADS upgrades occurred in 27 cases (22.0%; upgrade PPV 88.9%). Conclusions: In this biopsy-enriched ACR C/D cohort, adding DBT to 2D DM was diagnostically superior across all metrics. The disproportionate visibility gain for Grade 1 tumors is a hypothesis-generating finding relevant to the overdiagnosis debate, not proof that DBT reduces overdiagnosis. These findings support DBT as a valuable adjunct to 2D DM in dense breasts, pending prospective, multi-reader validation in unselected populations.