Otso Arponent

Objectives: The aim of this exploratory study was to evaluate whether three-dimensional texture analysis (3D-TA) features of non-contrast-enhanced T 1 weighted MRI associate with traditional prognostic factors and disease-free survival (DFS) of breast cancer. Methods: 3D-T 1 weighted images from 78 patients with 81 malignant histopathologically verified breast lesions were retrospectively analysed using standard-size volumes of interest. Grey-level co-occurrence matrix (GLCM)-based features were selected for statistical analysis. In statistics the Mann–Whitney U and the Kruskal–Wallis tests, the Cox proportional hazards model and the Kaplan–Meier method were used. Results: Tumours with higher histological grade were significantly associated with higher contrast (1 voxel: p = 0.033, 2 voxels: p = 0.036). All the entropy parameters showed significant correlation with tumour grade (p = 0.015–0.050) but there were no statistically significant associations between other TA parameters and tumour grade. The Nottingham Prognostic Index (NPI) was correlated with contrast and sum entropy parameters. A higher sum variance TA parameter was a significant predictor of shorter DFS. Conclusion: Texture parameters, assessed by 3D-TA from non-enhanced T 1 weighted images, indicate tumour heterogeneity but have limited independent prognostic value. However, they are associated with tumour grade, NPI, and DFS. These parameters could be used as an adjunct to contrast-enhanced TA parameters. Advances in knowledge: 3D-TA of non-contrast enhanced T 1 weighted breast MRI associates with tumour grade, NPI, and DFS. The use of non-contrast 3D-TA parameters in adjunct with contrast-enhanced 3D-TA parameters warrants further research.

To retrospectively evaluated the influence of administration of the gadolinium based intravenous contrast agent (G-CA) on apparent diffusion coefficient (ADC) values in ADC maps generated using multiple b value combinations. A total of 106 women underwent bilateral 3.0 T breast MRI. As an internal validation, diffusion-weighted imaging (b values of 0, 200, 400, 600, 800 s/mm²) was performed before and after the G-CA (gadoterate meglumine (0.2 ml/kg, 3 ml/s)). Whole lesion and fibroglandular tissue (FGT) covering region-of-interests (ROIs) were drawn on the b = 800 s/mm² images; ROIs were then propagated to multiple retrospectively generated ADC maps. Twenty-seven patients (mean age 55.8 ± 10.8 years) with 32 mass-like enhancing breast lesions including 25 (78.1 %) histopathologically malignant lesions were enrolled. Lesion ADC values were statistically significantly higher in pre-G-CA than post-G-CA ADC maps (ADC_{0,200,400,600,800}: 1.05 ± 0.35 × 10⁻³ mm²/s vs. 1.02 ± 0.36 × 10⁻³ mm²/s (P < 0.05); ADC_0,200,400: 1.25 ± 0.42 × 10⁻³ mm²/s vs. 1.20 ± 0.35 × 10⁻³ mm²/s (P < 0.05)). ADC values between pre- and post-contrast maps were not statistically different when the maps were generated using other b value combinations. Contrast agent administration did not affect the FGT ADC values. G-CA statistically significantly reduced the ADC values of breast lesions on ADC maps generated using the clinically widely utilized b values.

To investigate whether very low mammographic breast density (VLD), HER2, and hormone receptor status holds any prognostic significance within the different prognostic categories of the widely used Nottingham Prognostic Index (NPI). We also aimed to see whether these factors could be incorporated into the NPI in an effort to enhance its performance. This study included 270 patients with newly diagnosed invasive breast cancer. Patients with mammographic breast density of <10 % were considered as VLD. In this study, we compared the performance of NPI with and without VLD, HER2, ER and PR. Cox multivariate analysis, time-dependent receiver operating characteristic curve (tdROC), concordance index (c-index) and prediction error (0.632+ bootstrap estimator) were used to derive an updated version of NPI. Both mammographic breast density (VLD) (p < 0.001) and HER2 status (p = 0.049) had a clinically significant effect on the disease free survival of patients in the intermediate and high risk groups of the original NPI classification. The incorporation of both factors (VLD and HER2 status) into the NPI provided improved patient outcome stratification by decreasing the percentage of patients in the intermediate prognostic groups, moving a substantial percentage towards the low and high risk prognostic groups. Very low density (VLD) and HER2 positivity were prognostically significant factors independent of the NPI. Furthermore, the incorporation of VLD and HER2 to the NPI served to enhance its accuracy, thus offering a readily available and more accurate method for the evaluation of patient prognosis.

Objectives To evaluate the value of adding T2- and diffusion-weighted imaging (DWI) to the BI-RADS® classification in MRI-detected lesions. Methods This retrospective study included 112 consecutive patients who underwent 3.0T structural breast MRI with T2- and DWI on the basis of EUSOMA recommendations. Morphological and kinetic features, T2 signal intensity (T2 SI) and apparent diffusion coefficient (ADC) findings were assessed. Results Thirty-three (29.5 %) patients (mean age 57.0 ± 12.7 years) had 36 primarily MRI-detected incidental lesions of which 16 (44.4 %) proved to be malignant. No single morphological or kinetic feature was associated with malignancy. Both low T2 SI (P = 0.009) and low ADC values (≤0.87 × 10⁻³ mm²s⁻¹, P < 0.001) yielded high specificity (80.0 %/80.0 %). The BI-RADS classification supplemented with information from DWI and T2-WI improved the diagnostic performance of the BI-RADS classification as sensitivity remained 100 % and specificity improved from 30 % to 65.0 %. The numbers of false positive lesions declined from 39 % (N = 14) to 19 % (N = 7). Conclusion MRI-detected incidental lesions may be challenging to characterize as they have few specific malignancy indicating features. The specificity of MRI can be improved by incorporating T2 SI and ADC values into the BI-RADS assessment. Key Points • MRI-detected incidental lesions have few specific malignancy indicating features. • ≥ 1 suspicious morphologic or kinetic feature may warrant biopsy. • T2 signal intensity and DWI assessment are feasible in primarily MRI-detected lesions. • T2 SI and DWI assessment improve the BI-RADS specificity in MRI-detected lesions.

Apparent diffusion coefficient (ADC) values are increasingly reported in breast MRI. As there is no standardized method for ADC measurements, we evaluated the effect of the size of region of interest (ROI) to diagnostic utility and correlation to prognostic markers of breast cancer. This prospective study was approved by the Institutional Ethics Board; the need for written informed consent for the retrospective analyses of the breast MRIs was waived by the Chair of the Hospital District. We compared diagnostic accuracy of ADC measurements from whole-lesion ROIs (WL-ROIs) to small subregions (S-ROIs) showing the most restricted diffusion and evaluated correlations with prognostic factors in 112 consecutive patients (mean age 56.2±11.6 years, 137 lesions) who underwent 3.0-T breast MRI. Intra- and interobserver reproducibility were substantial (κ = 0.616–0.784; Intra-Class Correlation 0.589–0.831). In receiver operating characteristics analysis, differentiation between malignant and benign lesions was excellent (area under curve 0.957–0.962, cut-off ADC values for WL-ROIs: 0.87×10⁻³ mm²s^-1; S-ROIs: 0.69×10⁻³ mm²s^-1, P<0.001). WL-ROIs/S-ROIs achieved sensitivities of 95.7%/91.3%, specificities of 89.5%/94.7%, and overall accuracies of 89.8%/94.2%. In S-ROIs, lower ADC values correlated with presence of axillary metastases (P = 0.03), high histological grade (P = 0.006), and worsened Nottingham Prognostic Index Score (P<0.05). In both ROIs, ADC values correlated with progesterone receptors and advanced stage (P<0.01), but not with HER2, estrogen receptors, or Ki-67. ADC values assist in breast tumor characterization. Small ROIs were more accurate than whole-lesion ROIs and more frequently associated with prognostic factors. Cut-off values differed significantly depending on measurement procedure, which should be recognized when comparing results from the literature. Instead of using a whole lesion covering ROI, a small ROI could be advocated in diffusion-weighted imaging.