Acoustic radiation force impulse elastography in evaluation of triple-negative breast cancer: A preliminary experience

Preoperative discrimination of invasive and non-invasive breast cancer using machine learning based on automated breast volume scanning (ABVS) radiomics and virtual touch quantification (VTQ)

PURPOSE

Evaluating the efficacy of machine learning for preoperative differentiation between invasive and non-invasive breast cancer through integrated automated breast volume scanning (ABVS) radiomics and virtual touch quantification (VTQ) techniques.

METHODS

We conducted an extensive retrospective analysis on a cohort of 171 breast cancer patients, differentiating them into 124 invasive and 47 non-invasive cases. The data was meticulously divided into a training set (n = 119) and a validation set (n = 52), maintaining a 70:30 ratio. Several machine learning models were developed and tested, including Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), and Support Vector Machine (SVM). Their performance was evaluated using the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC), and visualized the feature contributions of the optimal model using Shapley Additive Explanations (SHAP).

RESULTS

Through both univariate and multivariate logistic regression analyses, we identified key independent predictors in differentiating between invasive and non-invasive breast cancer types: coronal plane features, Shear Wave Velocity (SWV), and Radscore. The AUC scores for our machine learning models varied, ranging from 0.625 to 0.880, with the DT model demonstrating a notably high AUC of 0.874 in the validation set.

CONCLUSION

Our findings indicate that machine learning models, which integrate ABVS radiomics and VTQ, are significantly effective in preoperatively distinguishing between invasive and non-invasive breast cancer. Particularly, the DT model stood out in the validation set, establishing it as the primary model in our study. This highlights its potential utility in enhancing clinical decision-making processes.

Calcification, Posterior Acoustic, and Blood Flow: Ultrasonic Characteristics of Triple-Negative Breast Cancer

Previous studies suggest that triple-negative breast cancer (TNBC) may have unique imaging characteristics, however, studies focused on the imaging characteristics of TNBC are still limited. The aim of the present study is to analyze the ultrasonic characteristics of TNBC and to provide more reliable information on imaging diagnosis of TNBC. This retrospective study was performed including 162 TNBC patients with 184 TNBC lesions. 174 non-TNBC cases with 196 lesions were used as the control group. The median size of TNBC lesions and non-TNBC lesions were 23 mm × 16 mm and 21 mm × 15 mm, respectively. The shape of most breast cancer lesions was irregular. However, 15.30% (28/183) TNBC lesions and 16.84% (33/196) non-TNBC lesions were oval-shaped. Most breast cancer lesions (79.78% TNBC & 85.71% non-TNBC) were ill-defined. In comparison to non-TNBC, the distinctive ultrasonic characteristics of TNBC were summarized as three features: calcifications, posterior acoustic, and blood flow. Microcalcifications was less common in non-TNBC. The remarkable posterior acoustic characteristics on TNBC were no posterior acoustic features (136, 73.91%). Avascular pattern (21.74%) was also more common in TNBC. The other feature of TNBC was markedly hypoechoic lesions (23.91%). The above-mentioned differences between TNBC and non-TNBC were significant. 93.48% TBNC and 94.39% non–TNBC lesions were in BI-RADS-US category of 4A-5. The results indicate that TNBC has some distinctive ultrasound characteristics. Ultrasound is a useful adjunct in early detection of breast cancer. A combination of ultrasound with mammography is excellent for detecting breast cancer.

The value of color-map virtual touch tissue imaging (CMV) in the differential diagnosis of benign and malignant breast lesions

BACKGROUND

Researchers have evaluated the virtual touch tissue imaging (VTI) value in the diagnosis of breast lesions, mostly based on gray-scale.

PURPOSE

This study aimed to evaluate the value of color-map virtual touch tissue imaging (CMV) in the diagnosis of breast lesions.

METHODS

We retrospectively analyzed the VTI images of 55 breast lesions in 49 female patients who underwent an examination of breast lesions in our hospital from January 2019 to December 2019. The pathological results were taken as the gold standard. The receiver operating characteristic (ROC) curve of CMV was analyzed, and its diagnostic performance was evaluated. Weighted Kappa (k) statistics were used to assess the inter-observer agreement for CMV.

RESULTS

A total of 55 breast lesions were included, including 19 malignant lesions and 36 benign lesions. Multivariate analysis showed that patients with higher CMV scores (P = 0.014, odds ratio [OR] = 13.667, 95% confidence interval = 1.702-109.773) were independent predictors of breast cancer. The sensitivity, specificity, and the area under curve (AUC) of CMV were 94.47%, 72.22%, and 0.912. The CMV's inter-observer agreement was almost perfect among radiologists with different work experience (k = 0.854, standard error = 0.049, 95% CI = 0.758-0.950).

CONCLUSIOS

CMV has high accuracy and repeatability in the diagnosis of malignant breast lesions.

The value of acoustic radiation force impulse imaging in preoperative prediction for efficacy of high-Intensity focused ultrasound uterine fibroids ablation

Objective: To investigate the application value of acoustic radiation force impulse imaging in preoperative prediction for efficacy of High-Intensity Focused Ultrasound uterine fibroids ablationMethods: A prospective study was conducted on 32 women (41 fibroids) undergoing HIFU uterine fibroids ablation between January 2019 and September 2019. The virtual touch tissue quantification (VTQ) technique was used for the preoperative determination of uterine fibroids shear wave velocity (SWV). The stiffness of the preoperative uterine fibroids was graded on a virtual touch tissue image (VTI). All uterine fibroids were ablated with a single point ablation acoustic power of 400 W. All patients underwent pelvic cavity MRI examination for the measurement of the size, volume and non-perfused volume (NPV) of fibroids within the first month after HIFU ablation. The ablation rate of uterine fibroids was calculated according to the formula: ablation rate = NPV × 100/target fibroid volume. The patients were divided into two groups based on the postoperative ablation rate: ≥70% ablation rate group, and＜70% ablation rate group. The preoperative SWV and VTI grade of uterine fibroids were compared between the two groups. The correlation of preoperative uterine fibroids' SWV and VTI grade with HIFU ablation rate were analyzed using the Spearman's correlation coefficient. The optimal cutoff points in preoperative uterine fibroids SWV of 70% ablation rate were determined by receiver operating curve (ROC) analysis.Results: A total of 30 patients (73.17%, 30/41) showed ablation rate ≥70%, with preoperative uterine fibroids' SWV values of (3.42 ± 0.71) m/s. Of these, 24 patients (80%, 24/30) had VTI grades II-III. On the other hand, 26.83% (11/41) showed ablation rate <70%, with preoperative uterine fibroids' SWV values of (4.02 ± 0.69) m/s; of these, 63.6% (7/11) had VTI grade IV. The SWV values and VTI grades of preoperative uterine fibroids were significantly different in the two groups (p < 0.05). Interestingly, postoperative ablation rate was negatively correlated with preoperative uterine fibroids' SWV values (r= -0.536, p = 0.0003) and VTI grades (r= -0.511, p = 0.001). The area under the ROC curve of preoperative uterine fibroids' SWV values with ablation rate <70% was 0.75 at a cutoff value of 3.915 m/s (p < 0.05). Specificity was 72.7% and sensitivity was 80.1%; the positive predictive value was 72.7%, and the negative predictive value was 80%.Conclusion: ARFI technique is an effective and feasible noninvasive ultrasound technique for the preoperative prediction of the efficacy of HIFU uterine fibroids ablation.

Quantitative Multiparametric Breast Ultrasound: Application of Contrast-Enhanced Ultrasound and Elastography Leads to an Improved Differentiation of Benign and Malignant Lesions

OBJECTIVES

The aim of this study was to evaluate breast multiparametric ultrasound (mpUS) and its potential to reduce unnecessary breast biopsies with 1, 2, or 3 additional quantitative parameters (Doppler, elastography, and contrast-enhanced ultrasound [CEUS]) to B-mode and investigate possible variations with different reader experience.

MATERIALS AND METHODS

This prospective study included 124 women (age range, 18-82 years; mean, 52 years), each with 1 new breast lesion, scheduled for ultrasound-guided biopsy between October 2015 and September 2016. Each lesion was examined with B-mode, elastography (Virtual Touch IQ [VTIQ]), Doppler, and CEUS, and different quantitative parameters were recorded for each modality. Four readers (2 experienced breast radiologists and 2 in-training) independently evaluated B-mode images of each lesion and assigned a BI-RADS (Breast Imaging Reporting and Data System) score. Using the area under the receiver operating characteristic curve (AUC), the most accurate quantitative parameter for each modality was chosen. These were then combined with the BI-RADS scores of all readers. Descriptive statistics and AUC were used to evaluate the diagnostic performance of mpUS.

RESULTS

Sixty-five lesions were malignant. MpUS with B-mode and 2 additional quantitative parameters (VTIQ and CEUS or Doppler) showed the highest diagnostic performance for all readers (averaged AUCs, 0.812-0.789 respectively vs 0.683 for B-mode, P = 0.0001). Both combinations significantly reduced the number of false-positive findings up to 46.9% (P < 0.0001).

CONCLUSIONS

Quantitative mpUS with 2 different triple assessment modalities (B-mode, VTIQ elastography, CEUS, or Doppler) shows the best diagnostic performance for breast cancer diagnosis and leads to a significant reduction of false-positive biopsy recommendations, for both experienced and inexperienced readers.

Changes in Muscle Stiffness in Infants with Congenital Muscular Torticollis

Congenital muscular torticollis (CMT) results from unilateral shortening of the sternocleidomastoid (SCM) muscle, usually associated with a fibrotic mass. Although CMT may resolve with physical therapy, some cases persist, resulting in long-term musculoskeletal problems. It is therefore helpful to be able to monitor and predict the outcomes of physical therapy. Shear-wave velocity (SWV) determined by acoustic radiation force impulse (ARFI) elastography can provide a quantitative measure of muscle stiffness. We therefore measured SCM SWV in 22 infants with unilateral CMT before and after 3 months of physical therapy and evaluated the relationships between SWV and SCM thickness and various clinical features, including cervical range of motion (ROM). SWV was initially higher and the ROM was smaller in affected muscles before physical therapy. SWV decreased significantly (2.33 ± 0.47 to 1.56 ± 0.63 m/s, p < 0.001), indicating reduced stiffness, and muscle thickness also decreased after physical therapy (15.64 ± 5.24 to 11.36 ± 5.71 mm, p < 0.001), both in line with increased neck ROM of rotation (64.77 ± 18.87 to 87.27 ± 6.31°, p < 0.001) and lateral flexion (37.50 ± 11.31 to 53.64 ± 9.41°, p < 0.001). However, the improved ROM more closely reflected the changes in SWV than in muscle thickness. These results suggest that a change in SWV detected by ARFI elastography could help to predict improvements in clinical outcomes, such as stiffness-related loss of motion, in patients with CMT undergoing physical therapy.