Value of quantitative sound touch elastography of tissues around breast lesions in the evaluation of malignancy

Breast Imaging Reporting and Data System evaluation of breast lesions improved with virtual touch tissue imaging average grayscale values

BACKGROUND

Early breast cancer diagnosis is of great clinical importance for selecting treatment options, improving prognosis, and enhancing the quality of patients' survival.

OBJECTIVE

We investigated the value of virtual touch tissue imaging average grayscale values (VAGV) helper Breast Imaging Reporting and Data System (BI-RADS) in diagnosing breast malignancy.

METHODS

We retrospectively analyzed 141 breast tumors in 134 patients. All breast lesions were diagnosed pathologically by biopsy or surgical excision. All patients first underwent conventional ultrasound (US) followed by virtual touch tissue imaging (VTI). The measurement of the VAGV of the lesion was performed by Image J software. BI-RADS classification was performed for each lesion according to the US. We performed a two-by-two comparison of the diagnostic values of VAGV, BI-RADS, and BI-RADS+VAGV.

RESULTS

VAGV was lower in malignant tumors than in benign ones (35.82 ± 13.39 versus 73.58 ± 42.69, P< 0.001). The area under the receiver operating characteristic curve (AUC) value, sensitivity, and specificity of VAGV was 0.834, 84.09%, and 69.07%, respectively. Among BI-RADS, VAGV, and BI-RADS+VAGV, BI-RADS+VAGV had the highest AUC (0.926 versus 0.882, P= 0.0066; 0.926 versus 0.834, P= 0.0012). There was perfect agreement between the two radiologists using VAGV (ICC= 0.9796) and substantial agreement using BI-RADS (Kappa= 0.725).

CONCLUSION

Our study shows that VAGV can accurately diagnose breast cancer. VAGV effectively improves the diagnostic performance of BI-RADS.

Convolutional neural network based on automatic segmentation of peritumoral shear-wave elastography images for predicting breast cancer

Objective

Our aim was to develop dual-modal CNN models based on combining conventional ultrasound (US) images and shear-wave elastography (SWE) of peritumoral region to improve prediction of breast cancer.

Method

We retrospectively collected US images and SWE data of 1271 ACR- BIRADS 4 breast lesions from 1116 female patients (mean age ± standard deviation, 45.40 ± 9.65 years). The lesions were divided into three subgroups based on the maximum diameter (MD): ≤15 mm; >15 mm and ≤25 mm; >25 mm. We recorded lesion stiffness (SWV1) and 5-point average stiffness of the peritumoral tissue (SWV5). The CNN models were built based on the segmentation of different widths of peritumoral tissue (0.5 mm, 1.0 mm, 1.5 mm, 2.0 mm) and internal SWE image of the lesions. All single-parameter CNN models, dual-modal CNN models, and quantitative SWE parameters in the training cohort (971 lesions) and the validation cohort (300 lesions) were assessed by receiver operating characteristic (ROC) curve.

Results

The US + 1.0 mm SWE model achieved the highest area under the ROC curve (AUC) in the subgroup of lesions with MD ≤15 mm in both the training (0.94) and the validation cohorts (0.91). In the subgroups with MD between15 and 25 mm and above 25 mm, the US + 2.0 mm SWE model achieved the highest AUCs in both the training cohort (0.96 and 0.95, respectively) and the validation cohort (0.93 and 0.91, respectively).

Conclusion

The dual-modal CNN models based on the combination of US and peritumoral region SWE images allow accurate prediction of breast cancer.

Clinical use and adjustment of ultrasound elastography for breast lesions followed WFUMB guidelines and recommendations in the real world

Objective

This study aimed to explore the value of strain elastography (SE) and shear wave elastography (SWE) following the World Federation of Ultrasound in Medicine and Biology (WFUMB) guidelines and recommendations in the real world in distinguishing benign and malignant breast lesions and reducing biopsy of BI-RADS (Breast Imaging Reporting and Data System) 4a lesions.

Methods

This prospective study included 274 breast lesions. The elastography score (ES) by the Tsukuba score, the strain ratio (SR) for SE, and Emax for SWE of the lesion(A) and the regions(A') included the lesion and the margin (0.5-5 mm) surrounding the lesion were measured. The sensitivity, specificity, and AUC were calculated and compared by the cutoff values recommended by WFUMB guidelines.

Results

When scores of 1 to 3 were classified as probably benign by WFUMB recommendation, the ES was significantly higher in malignant lesions compared to benign lesions (p < 0.05) in all lesions. For the cohort by size >20 mm, the sensitivity was 100%, and the specificity was 45.5%. ES had the highest AUC: 0.79(95% CI 0.72-0.86) with a sensitivity of 96.2%, and a specificity of 61.8% for the cohort by size ≤20 mm. For the Emax-A'-S2.5mm, when the high stiffness would be considered with Emax above 80 kPa in SWE, the malignant lesions were diagnosed with a sensitivity of 95.8%, a specificity of 43.3% for all lesions, a sensitivity of 88.5% for lesions with size ≤20 mm, and sensitivity of 100.0% for lesions with size >20 mm. In 84 lesions of BI-RADS category 4a, if category 4a lesions with ES of 1-3 points or Emax-A'-S2.5 less than 80 kPa could be downgraded to category 3, 52 (61.9%) lesions could be no biopsy, including two malignancies. If category 4a lesions with ES of 1-3 points and Emax-A'-S2.5 less than 80kPa could be downgraded to category 3, 23 (27.4%) lesions could be no biopsy, with no malignancy.

Conclusions

The elastography score for SE and Emax-A' for SWE after our modification were beneficial in the diagnosis of breast cancer. The combination of SWE and SE could effectively reduce the biopsy rate of BI-RADS category 4a lesions.

The values of elastic quantitative and semi-quantitative indexes measured from different frequencies in the establishment of prediction models for breast tumor diagnosis

Objective

To obtain the elastic quantitative and semi-quantitative indexes of solid breast masses using ultrasound linear array probes with two different frequencies, and to construct prediction models and evaluate their diagnostic values.

Methods

A total of 92 patients who were scheduled for surgical treatment on solid breast masses were enrolled in this study. Linear array probes with two frequencies, 9-3 MHz (L9 group) and 14-5 MHz (L14 group), were used for sound touch elastography and strain elastography before surgery, and the maximum elasticity value (Emax), average elasticity value (Emean), minimum elasticity value (Emin), standard deviation (SD)(in kPa), elasticity ratio (E), and strain ratio to fat (SRf) were recorded and calculated for the breast mass (A) and surrounding tissues (Shell). The elastic characteristic indexes of the L9 group and L14 group were compared, and the prediction models of these two groups were constructed using Logistic regression method.

Results

The diagnostic performance of the prediction model based on L9 group was better than the model based on L14 group (AUC: 0.904 vs. 0.810, P = 0.0343, z = 2.116) and the best single index EMax-shell-L9 (P = 0.0398, z = 2.056). The sensitivity of L9 based model was 85.19% and the specificity was 84.21%.

Conclusion

The prediction model based on quantitative and semi-quantitative elastic ultrasound indexes from L9-3 probe exhibited better performance, which could improve the diagnostic accuracy for malignant breast tumors.

Different precompression does not reduce the diagnostic value of virtual touch tissue imaging and quantification (VTIQ) in breast lesions, especially for the ratio of the shear wave velocity between lesions and surrounding tissues

OBJECTIVE

To investigate the accuracy of virtual touch tissue imaging and quantification (VTIQ) in the diagnosis of benign and malignant breast lesions under four different precompression levels. The shear wave velocity (SWV) ratios of lesion to surrounding tissue were also added for diagnosis.

METHODS

167 female patients with breast lesions were included in this single center prospective study. VTIQ was performed under four different precompression levels. The SWV of the lesion, surrounding fat, and gland tissue were measured at the same depth as much as feasible 7 times. The breast lesions studied were all histopathologically confirmed. The VTIQ parameters were compared between precompression levels. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic performance of each parameter of the VTIQ.

RESULTS

The VTIQ parameters of the malignant lesions were significantly higher than those of benign lesions in all precompression levels (P < 0.001). SWV of the lesion, fat, and gland tissue increased significantly with increasing precompression. The VTIQ parameters had great diagnostic performance for breast lesions in all precompression levels (AUC = 0.765-0.911). There was no significant difference between the precompression levels of the lesion-to-fat SWV ratio and the lesion-to-gland SWV ratio in benign and malignant lesions, and the cut-off coefficients of variation were 7.42% and 8.55%, respectively.

CONCLUSIONS

Precompression can increase the stiffness of breast lesions, fat and gland tissues, but does not reduce diagnostic value of VTIQ parameters in the breast. Under different precompression levels, the diagnosis of breast lesions by the ratio of the SWV of the lesion to the surrounding tissues is more stable.

Color-map virtual touch tissue imaging (CMV) combined with BI-RADS for the diagnosis of breast lesions

OBJECTIVE

To investigate the importance of color-map virtual touch tissue imaging (CMV) in assisting Breast Imaging Reporting and Data Systems (BI-RADS) in diagnosing malignant breast lesions.

METHODS

A dataset included 134 patients and 146 breast lesions was assembled. All patients underwent biopsy or surgical excision of breast lesions, and pathological results were obtained. All patients with breast lesions also underwent conventional ultrasound (US) and CMV. Each lesion was assigned a CMV score based on the color pattern of the lesion and surrounding breast tissue and a BI-RADS classification rating based on US characteristics. We compared the diagnostic performance of using BI-RADS and CMV separately and their combination.

RESULTS

BI-RADS (odds ratio [OR]: 3.665; 95% confidence interval [CI]: 2.147, 6.258) and CMV (OR: 6.616; 95% CI: 2.272, 19.270) were independent predictors of breast malignancy (all P < 0.05). The area under the receiver operating characteristic curves (AUC) for either CMV or BI-RADS alone was inferior to that of the combination (0.877 vs. 0.962; 0.938 vs. 0.962; all P < 0.05).

CONCLUSIONS

The performance of BI-RADS in diagnosing breast lesions is significantly improved by combining CMV. Therefore, we recommend CMV as an adjunct to BI-RADS.

Role of "Stiff Rim" sign obtained by shear wave elastography in diagnosis and guiding therapy of breast cancer

Background: Because the halo around the tumor in shear wave elastography (SWE) is defined as the "stiff rim" sign, the diagnosis of breast lesions with the stiff rim sign is popular. However, only a few studies have described the stiff rim sign quantitatively. Objective: This study aimed to investigate the usefulness of the stiff rim sign in the diagnosis and tumor, node, metastasis stage of breast cancer. Methods: Two hundred and ten breast lesions were analyzed retrospectively. The maximum, mean, minimum Young's modulus (YM), and the YM standard deviation in the lesion, the peritumoral stiffness (shell), and the region containing lesion and shell were obtained. The suspicious SWE feature with the best diagnostic performance was chosen to downgrade or upgrade the Breast Imaging Reporting and Data System (BI-RADS) classification. The coincidence rates of SWE and B-mode ultrasound in T staging and their positive predictive value (PPV) for T staging were compared. Results: The presence of "stiff rim" sign was selected to upgrade or downgrade the BI-RADS classification because of its best performance. In pathological benign lesions, 18.9% (25 of 132) of lesions should undergo biopsy if BI-RADS combined with the stiff rim sign were referred while it was 57.6% (76 of 132) if BI-RADS alone was referred. The coincidence rate of T2 staging evaluated by SWE was significantly higher than B-mode ultrasound (about 30% increase, P < 0.001). The PPVs of SWE for T1 and T2 staging were higher than B-mode ultrasound (P < 0.05). Conclusions: BI-RADS combined with "stiff rim" sign is expected to improve the diagnostic performance of breast lesions to avoid unnecessary biopsy. The maximum diameter of the lesion measured in SWE is more accurate than B-mode ultrasound in the estimation of T staging, which is beneficial to the treatment and prognosis of breast cancer.