How to optimize MRI breast protocol? The value of combined analysis of ultrafast and diffusion-weighted MRI sequences

Novel approach to MRI based risk stratification of uterine myometrial lesions

BACKGROUND

Surgery for uterine mesenchymal tumors is common in gynecology. Preoperative diagnosis of malignant tumors can lead to appropriate management for the lesions.

PURPOSE

This study aims to externally validate a previous MRI-based expert consensus algorithm and evaluate the potential modification of MR-based scoring system's accuracy in diagnosing uterine mesenchymal tumors (UMT).

MATERIAL AND METHODS

With institutional ethics committee approval and a waiver of informed consent (CRM-2405-410), a bicentric retrospective observational cohort study was conducted from January 2018 to December 2023. The study included women with a pathological diagnosis of uterine mesenchymal tumor following a pelvic MRI within six months. Clinical and MR criteria were blindly recorded by two radiologists (6- and 3-years' experience in gynaecological MR imaging) who assessed several MR features. Continuous variables were analyzed using a Mann-Whitney test, and categorical variables using Fisher's exact test. Odds ratios (OR) for predicting malignancy were calculated with 95% confidence intervals and p-values.

RESULTS

The cohort included 455 women (mean age: 43 years, range: 15-82 years) with mesenchymal tumors: 437 leiomyomas, 2 STUMPs (0.4 %), and 16 malignant UMT (3.5 %). Using initial criteria (enlarged pelvic lymph nodes, T2W signal intensity, DW signal intensity compared to endometrium, and ADC cutoff value of 0.9 × 10-3 mm2/sec), the model accurately classified 421 out of 455 cases (Accuracy: 92,5% (CI 93,1-94,3) and missed with 7 tumors (5 leiomyosarcomas, 2 STUMP). The sensitivity was 61.1 % (CI95% 38.5-83.6) and specificity was 93.8 % (CI95% 91.2-95.8) A modified algorithmic approach added "irregular tumor margins" and menopausal status, modified DW signal compared to bladder, and an elevated ADC cutoff value of 1.23 × 10-3 mm2/sec, improving classification to 446 out of 455 cases (Accuracy: 98 % (CI95% 97.1 %-98.1 %) with only 3 missed tumors (2 STUMP and one leiomyosarcoma). The sensitivity was 83.3 % (CI95% 79-88) and specificity was 98.6 % (CI95% 98-99). The new algorithm significantly improved accuracy (p = 0.001), allowing the development of a 5-category scoring system.

CONCLUSION

Modified MR imaging evaluation algorithms increase true positive diagnosis of malignant UMTs leading to effective differentiation from benign leiomyomas. The new algorithm can allow for appropriate triage of potentially malignant UMTs, alleviating risk associated with morcellation in patients with uterine leiomyosarcoma.

SUMMARY

Our study demonstrates that combining 5 criteria based on multivariate analysis in a new algorithm (T2W signal, DW signal, ADC cut off value of 1.23 x 10-3 mm2/sec, tumor margins and menopausal status) allows us to distinguish benign from malignant uterine mesenchymal tumors with an accuracy of 98 % (CI95% 97,1%-98,1%), a sensitivity of 83.3 % (CI95% 79-88) and a specificity of 98.6 % (CI95% 98-99). This model allows to build a stratification score that would help in the management of typical and atypical uterine lesions.

Imaging in France: 2024 Update

Radiology in France has made major advances in recent years through innovations in research and clinical practice. French institutions have developed innovative imaging techniques and artificial intelligence applications in the field of diagnostic imaging and interventional radiology. These include, but are not limited to, a more precise diagnosis of cancer and other diseases, research in dual-energy and photon-counting computed tomography, new applications of artificial intelligence, and advanced treatments in the field of interventional radiology. This article aims to explore the major research initiatives and technological advances that are shaping the landscape of radiology in France. By highlighting key contributions in diagnostic imaging, artificial intelligence, and interventional radiology, we provide a comprehensive overview of how these innovations are improving patient outcomes, enhancing diagnostic accuracy, and expanding the possibilities for minimally invasive therapies. As the field continues to evolve, France's position at the forefront of radiological research ensures that these innovations will play a central role in addressing current healthcare challenges and improving patient care on a global scale.

Problem Solving MRI to Reduce False-Positive Biopsy Related to Breast US: Conductivity vs. DWI vs. Abbreviated Contrast-Enhanced MRI

BACKGROUND

While breast ultrasound (US) is a useful tool for diagnosing breast masses, it can entail false-positive biopsy results because of some overlapping features between benign and malignant breast masses and subjective interpretation.

PURPOSE

To evaluate the performance of conductivity imaging for reducing false-positive biopsy results related to breast US, as compared to diffusion-weighted imaging (DWI) and abbreviated MRI consisting of one pre- and one post-contrast T1-weighted imaging.

STUDY TYPE

Prospective.

SUBJECTS

Seventy-nine women (median age, 44 years) with 86 Breast Imaging Reporting and Data System (BI-RADS) category 4 masses as detected by breast US.

FIELD STRENGTH/SEQUENCE

3-T, T2-weighted turbo spin echo sequence, DWI, and abbreviated contrast-enhanced MRI (T1-weighted gradient echo sequence).

ASSESSMENT

US-guided biopsy (reference standard) was obtained on the same day as MRI. The maximum and mean conductivity parameters from whole and single regions of interest (ROIs) were measured. Apparent diffusion coefficient (ADC) values were obtained from an area with the lowest signal within a lesion on the ADC map. The performance of conductivity, ADC, and abbreviated MRI for reducing false-positive biopsies was evaluated using the following criteria: lowest conductivity and highest ADC values among malignant breast lesions and BI-RADS categories 2 or 3 on abbreviated MRI.

STATISTICAL TESTS

One conductivity parameter with the maximum area under the curve (AUC) from receiver operating characteristics was selected. A P-value <0.05 was considered statistically significant.

RESULTS

US-guided biopsy revealed 65 benign lesions and 21 malignant lesions. The mean conductivity parameter of the single ROI method was selected (AUC = 0.74). Considering conductivity (≤0.10 S/m), ADC (≥1.60 × 10-3  mm2 /sec), and BI-RADS categories 2 or 3 reduced false-positive biopsies by 23% (15 of 65), 38% (25 of 65), and 43% (28 of 65), respectively, without missing malignant lesions.

DATA CONCLUSION

Conductivity imaging may show lower performance than DWI and abbreviated MRI in reducing unnecessary biopsies.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Combining b2500 diffusion-weighted imaging with BI-RADS improves the specificity of breast MRI

PURPOSE

The purpose of this study was to evaluate the diagnostic performance of visual assessment of diffusion-weighted images (DWI) obtained with a b value of 2500 s/mm2 in addition to a conventional magnetic resonance imaging (MRI) protocol to characterize breast lesions.

MATERIALS AND METHODS

This single-institution retrospective study included participants who underwent clinically indicated breast MRI and breast biopsy from May 2017 to February 2020. The examination included a conventional MRI protocol including DWI obtained with a b value of 50 s/mm2 (b50DWI) and a b value of 800 s/mm2 (b800DWI) and DWI obtained with a b value of 2500 s/mm2 (b2500DWI). Lesions were classified using Breast Imaging Reporting and Data Systems (BI-RADS) categories. Three independent radiologists assessed qualitatively the signal intensity within the breast lesions relative to breast parenchyma on b2500DW and b800DWI and measured the b50-b800-derived apparent diffusion coefficient (ADC) value. The diagnostic performances of BI-RADS, b2500DWI, b800DWI, ADC and of a model combining b2500DWI and BI-RADS were evaluated using receiver operating characteristic (ROC) curves analysis.

RESULTS

A total of 260 patients with 212 malignant and 100 benign breast lesions were included. There were 259 women and one man with a median age of 53 years (Q1, Q3: 48, 66 years). b2500DWI was assessable in 97% of the lesions. Interobserver agreement for b2500DWI was substantial (Fleiss kappa = 0.77). b2500DWI yielded larger area under the ROC curve (AUC, 0.81) than ADC with a 1 × 10-3 mm2/s threshold (AUC, 0.58; P = 0.005) and than b800DWI (AUC, 0.57; P = 0.02). The AUC of the model combining b2500DWI and BI-RADS was 0.84 (95% CI: 0.79-0.88). Adding b2500DWI to BI-RADS resulted in a significant increase in specificity from 25% (95% CI: 17-35) to 73% (95% CI: 63-81) (P < 0.001) with a decrease in sensitivity from 100% (95% CI: 97-100) to 94% (95% CI: 90-97), (P < 0.001).

CONCLUSION

Visual assessment of b2500DWI has substantial interobserver agreement. Visual assessment of b2500DWI offers better diagnostic performance than ADC and b800DWI. Adding visual assessment of b2500DWI to BI-RADS improves the specificity of breast MRI and could avoid unnecessary biopsies.