Can Ultrasonographic Vascular and Elastographic Features of Invasive Ductal Breast Carcinoma Predict Histologic Aggressiveness?

The utility of ultrafast MRI and conventional DCE-MRI for predicting histologic aggressiveness in patients with breast cancer

BACKGROUND

Prediction of histologic prognostic markers is important for determining management strategy and predicting prognosis.

PURPOSE

To identify important features of ultrafast and conventional dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) that can predict histopathologic prognostic markers in patients with breast cancer.

MATERIAL AND METHODS

Preoperative MRI scans of 158 consecutive women (mean age = 54.0 years; age range = 29-86 years) with 163 breast cancers between February 2021 and August 2022 were retrospectively reviewed. Inter-observer agreements for ultrafast MRI parameters were analyzed by two radiologists. The qualitative and quantitative MRI parameters were correlated with histopathologic prognostic markers including molecular subtypes and histologic invasiveness.

RESULTS

Inter-observer agreements for ultrafast MRI parameters were excellent (intraclass correlation coefficients of area under the kinetic curve [AUC], maximum slope [MS], maximum enhancement [ME], and slope = 0.987, 0.844, 0.822, and 0.760, respectively). Triple-negative breast cancers (TNBC) were significantly associated with rim enhancement (odds ratio [OR] = 9.4, P = 0.003) and peritumoral edema (OR = 17.9, P = 0.002), compared to luminal cancers. Invasive cancers were associated with lesion type-mass, increased delayed washout, angiovolume, ME, slope, MS, and AUC, compared to in situ cancers. In regression analysis, the combination of MS (>46.2%/s) (OR = 5.7, P = 0.046) and delayed washout (>17.5%) (OR = 17.6, P = 0.01), and that of AUC (>27,410.3) (OR = 9.6, P = 0.04), delayed washout (>17.5%) (OR = 8.9, P = 0.009), and lesion-type mass (OR = 4.6, P = 0.04) were predictive of histologic invasiveness.

CONCLUSION

Conventional DCE-MRI with ultrafast imaging can provide useful information for predicting histologic underestimation and aggressive molecular subtype. MS and AUC on ultrafast MRI can be potential imaging markers for predicting histologic upgrade from DCIS to invasive cancer with high reliability.

Prediction of complete response after neoadjuvant chemotherapy for invasive breast cancers: The utility of shear wave elastography and superb microvascular imaging in pretreatment breast ultrasound

PURPOSE

To investigate whether multiparametric parameters of pretreatment breast ultrasound (US) and clinicopathologic factors are associated with pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) for breast cancer.

METHODS

Between November 2018 and September 2022, 88 patients who underwent NAC and subsequent surgery were included in this study (median age, 55 years; interquartile range [IQR], 45, 59.3). Multiparametric breast US including grayscale, shear wave elastography (SWE) and superb microvascular imaging (SMI) of pathologically proven invasive breast cancers were retrospectively reviewed. Clinicopathological and multiparametric parameters of breast US, including size, SWEmax, SWEratio and vascular index on SMI (SMIVI) were compared between the groups. Univariate and multivariate logistic regression analyses were performed to determine factors predicting pCR after NAC. AUROC curve analysis was performed to determine the predictors' optimal cut-off values and diagnostic performance.

RESULTS

The pCR group (n = 24) showed a significantly smaller tumor size, lower SWEmax, higher Ki-67 index, higher hormone receptor negativity and negative axillary lymph node metastasis compared to the non-pCR group (n = 64). Multivariate regression analysis showed that SWEmax (adjusted odds ratio[aOR] = 0.956, 95 % confidence interval [CI] = 0.919-0.994, P = 0.025) and Ki-67 index (aOR = 1.083, 95 % CI = 1.012-1.159, P = 0.021) were independently associated with pathologically complete response. The optimal cut-off values for predicting pCR were 27.5 % for Ki-67 with an AUC of 0.743 and 134.8 kPa for SWEmax with an AUC of 0.779. A combination model including clinical factors and SWEmax showed the best diagnostic performance with an AUC of 0.876.

CONCLUSION

A higher Ki-67 index and lower SWEmax measured on pretreatment breast US were independently associated with pCR in invasive breast cancer after NAC.

Correlation of shear-wave elastography parameters with the molecular subtype and axillary lymph node status in breast cancer

PURPOSE

To examine correlations between shear-wave elastography (SWE) parameters with molecular subtype and axillary lymph node (LN) status of breast cancer.

METHODS

We retrospectively analyzed 545 consecutive women (mean age, 52.7 ± 10.7 years; range, 26-83) with breast cancer who underwent preoperative breast ultrasound with SWE between December 2019 and January 2021. SWE parameters (E_max, E_mean, and E_ratio) and the histopathologic information from surgical specimens including histologic type, histologic grade, size of invasive cancer, hormone receptor and HER2 status, Ki-67 proliferation index, and axillary LN status were analyzed. The relationships between SWE parameters and histopathologic findings were analyzed using an independent sample t-test, one-way ANOVA test with Tukey's post hoc test, and logistic regression analyses.

RESULTS

Higher stiffness values of SWE were associated with larger lesion size (>20 mm) on ultrasound, high histologic grade, larger invasive cancer size (>20 mm), high Ki-67, and axillary LN metastasis. E_max and E_mean were the lowest in the luminal A-like subtype, and all three parameters were the highest in the triple-negative subtype. Lower value of E_max was independently associated with the luminal A-like subtype (P = 0.04). Higher value of E_mean was independently associated with axillary LN metastasis for tumors ≤ 20 mm (P = 0.03).

CONCLUSION

Increases in the tumor stiffness values on SWE were significantly associated with aggressive histopathologic features of breast cancer. Lower stiffness values were associated with the luminal A-like subtype, and tumors with higher stiffness values were associated with axillary LN metastasis in small breast cancers.

The Utility of Quantitative Parameters of Shear-Wave Elastography to Predict Prognostic Histologic Features of Breast Cancer

ABSTRACT

In this study, we aimed to investigate the correlation of stiffness values of shear-wave elastography (SWE) and histopathological prognostic factors in patients with breast cancer. Between January 2021 and June 2022, SWE images of 138 core-biopsy proven breast cancer lesions from 132 patients were retrospectively reviewed. Histopathogic prognostic factors, including tumor size, histologic grade, histologic type, hormone receptor positivity, human epidermal growth factor receptor (HER2) status, immunohistochemical subtype and Ki-67 index were documented. Elasticity values including mean and maximum elasticity ( Emean and Emax ) and lesion-to-fat ratio ( Eratio ) were recorded. The association between histopathological prognostic factors and elasticity values were assessed using Mann-Whitney U and Kruskal-Wallis test, and multiple linear regression analysis. Tumor size, histological grade, and Ki-67 index were significantly associated with the Eratio ( P < 0.05). Larger tumor size and higher Ki-67 index also showed significantly higher Emean and Emax values ( P < 0.05). However, hormone receptor positivity, HER2 status, and immunohistochemical subtype were not significantly associated with elasticity values ( P > 0.05). Multivariate logistic regression analysis revealed that tumor size was significantly associated with Emean , Emax , and Eratio values ( P < 0.05). A high Ki-67 index was also significantly associated with high Eratio values. Larger tumor size and higher Ki-67 index are independently associated with high Eratio values. Preoperative SWE may improve the performance of conventional ultrasound in predicting prognosis and treatment planning.

Prediction of clinical response to neoadjuvant therapy in advanced breast cancer by baseline B-mode ultrasound, shear-wave elastography, and pathological information

Background

Neoadjuvant therapy (NAT) is the preferred treatment for advanced breast cancer nowadays. The early prediction of its responses is important for personalized treatment. This study aimed at using baseline shear wave elastography (SWE) ultrasound combined with clinical and pathological information to predict the clinical response to therapy in advanced breast cancer.

Methods

This retrospective study included 217 patients with advanced breast cancer who were treated in West China Hospital of Sichuan University from April 2020 to June 2022. The features of ultrasonic images were collected according to the Breast imaging reporting and data system (BI-RADS), and the stiffness value was measured at the same time. The changes were measured according to the Response evaluation criteria in solid tumors (RECIST1.1) by MRI and clinical situation. The relevant indicators of clinical response were obtained through univariate analysis and incorporated into a logistic regression analysis to establish the prediction model. The receiver operating characteristic (ROC) curve was used to evaluate the performance of the prediction models.

Results

All patients were divided into a test set and a validation set in a 7:3 ratio. A total of 152 patients in the test set, with 41 patients (27.00%) in the non-responders group and 111 patients (73.00%) in the responders group, were finally included in this study. Among all unitary and combined mode models, the Pathology + B-mode + SWE model performed best, with the highest AUC of 0.808 (accuracy 72.37%, sensitivity 68.47%, specificity 82.93%, P<0.001). HER2+, Skin invasion, Post mammary space invasion, Myometrial invasion and Emax were the factors with a significant predictive value (P<0.05). 65 patients were used as an external validation set. There was no statistical difference in ROC between the test set and the validation set (P>0.05).

Conclusion

As the non-invasive imaging biomarkers, baseline SWE ultrasound combined with clinical and pathological information can be used to predict the clinical response to therapy in advanced breast cancer.

Association between vascular ultrasound features and DNA sequencing in breast cancer: a preliminary study

There are few radiogenomic studies to correlate ultrasound features of breast cancer with genomic changes. We investigated whether vascular ultrasound phenotypes are associated with breast cancer gene profiles for predicting angiogenesis and prognosis. We prospectively correlated quantitative and qualitative features of microvascular ultrasound (vascular index, vessel morphology, distribution, and penetrating vessel) and contrast-enhanced ultrasound (time-intensity curve parameters and enhancement pattern) with genomic characteristics in 31 breast cancers. DNA obtained from breast tumors and normal tissues were analyzed using targeted next-generation sequencing of 105 genes. The single-variant association test was used to identify correlations between vascular ultrasound features and genomic profiles. Chi-square analysis was used to detect single nucleotide polymorphisms (SNPs) associated with ultrasound features by estimating p values and odds ratios (ORs). Eight ultrasound features were significantly associated with 9 SNPs (p < 0.05). Among them, four ultrasound features were positively associated with 5 SNPs: high vascular index with rs1136201 in ERBB2 (p = 0.04, OR = 7.75); large area under the curve on contrast-enhanced ultrasound with rs35597368 in PDGFRA (p = 0.04, OR = 4.07); high peak intensity with rs35597368 in PDGFRA (p = 0.049, OR = 4.05) and rs2305948 in KDR (p = 0.04, OR = 5.10); and long mean transit time with rs2275237 in ARNT (p = 0.02, OR = 10.25) and rs755793 in FGFR2 (p = 0.02, OR = 10.25). We identified 198 non-silent SNPs in 71 various cancer-related genes. Vascular ultrasound features can reflect genomic changes associated with angiogenesis and prognosis in breast cancer.

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.

Feasibility of Shear Wave Elastography Imaging for Evaluating the Biological Behavior of Breast Cancer

Objective

To explore the feasibility of shear wave elastography (SWE) parameters for assessing the biological behavior of breast cancer.

Materials and Methods

In this prospective study, 224 breast cancer lesions in 216 female patients were examined by B-mode ultrasound and shear wave elastography in sequence. The maximum size (S_max) of the lesion was measured by B-mode ultrasound, and then shear wave elastography was performed on this section to obtain relevant parameters, including maximum elasticity (E_max), mean elasticity (E_mean), standard deviation of elasticity (SD), and the area ratio of shear wave elastography to B-mode ultrasound (AR). The relationship between SWE parameters and pathological type, histopathological classification, histological grade, lymphovascular invasion status (LVI), axillary lymph node status (ALN), and immunohistochemistry of breast cancer lesions was performed according to postoperative pathology.

Results

In the univariate analysis, the pathological type and histopathological classification of breast cancer were not significantly associated with SWE parameters; with an increase in the histological grade of invasive ductal carcinoma (IDC), SD (p = 0.016) and S_max (p = 0.000) values increased. In the ALN-positive group, S_max (p = 0.004) was significantly greater than in the ALN-negative group; S_max (p = 0.003), E_max (p = 0.034), and SD (p = 0.045) were significantly higher in the LVI-positive group than in the LVI-negative group; SD (p = 0.043, p = 0.047) and S_max (p = 0.000, p = 0.000) were significantly lower in the ER⁺ and PR⁺ groups than in the ER^- and PR^- groups, respectively; AR (p = 0.032) was significantly higher in the ER⁺ groups than in the ER^- groups, and S_max (p = 0.002) of the HER2⁺ group showed higher values than that of the HER2^- group; S_max (p = 0.000), SD (p = 0.006), and E_max (p = 0.004) of the Ki-67 high-expression group showed significantly higher values than those of the Ki-67 low-expression group. In the multivariate analysis, Ki-67 was an independent factor of S_max (p = 0.005), E_max (p = 0.004), and SD (p = 0.006); ER was an independent influencing factor of S_max (p = 0.000) and AR (p = 0.032). LVI independently influences S_max (p = 0.006).

Conclusions

The SWE parameters E_max, SD, and AR can be used to evaluate the biological behavior of breast cancer.

Hybrid high-definition microvessel imaging/shear wave elastography improves breast lesion characterization

BACKGROUND

Low specificity in current breast imaging modalities leads to increased unnecessary follow-ups and biopsies. The purpose of this study is to evaluate the efficacy of combining the quantitative parameters of high-definition microvasculature imaging (HDMI) and 2D shear wave elastography (SWE) with clinical factors (lesion depth and age) for improving breast lesion differentiation.

METHODS

In this prospective study, from June 2016 through April 2021, patients with breast lesions identified on diagnostic ultrasound and recommended for core needle biopsy were recruited. HDMI and SWE were conducted prior to biopsies. Two new HDMI parameters, Murray's deviation and bifurcation angle, and a new SWE parameter, mass characteristic frequency, were included for quantitative analysis. Lesion malignancy prediction models based on HDMI only, SWE only, the combination of HDMI and SWE, and the combination of HDMI, SWE and clinical factors were trained via elastic net logistic regression with 70% (360/514) randomly selected data and validated with the remaining 30% (154/514) data. Prediction performances in the validation test set were compared across models with respect to area under the ROC curve as well as sensitivity and specificity based on optimized threshold selection.

RESULTS

A total of 508 participants (mean age, 54 years ± 15), including 507 female participants and 1 male participant, with 514 suspicious breast lesions (range, 4-72 mm, median size, 13 mm) were included. Of the lesions, 204 were malignant. The SWE-HDMI prediction model, combining quantitative parameters from SWE and HDMI, with AUC of 0.973 (95% CI 0.95-0.99), was significantly higher than the result predicted with the SWE model or HDMI model alone. With an optimal cutoff of 0.25 for the malignancy probability, the sensitivity and specificity were 95.5% and 89.7%, respectively. The specificity was further improved with the addition of clinical factors. The corresponding model defined as the SWE-HDMI-C prediction model had an AUC of 0.981 (95% CI 0.96-1.00).

CONCLUSIONS

The SWE-HDMI-C detection model, a combination of SWE estimates, HDMI quantitative biomarkers and clinical factors, greatly improved the accuracy in breast lesion characterization.

Prediction of Invasive Breast Cancer Using Mass Characteristic Frequency and Elasticity in Correlation with Prognostic Histologic Features and Immunohistochemical Biomarkers

This purpose of this study is to correlate a new shear-wave elastography (SWE) parameter, mass characteristic frequency (fmass) and other elasticity measure with the prognostic histological factors and immunohistochemical (IHC) biomarkers for the evaluation of heterogeneous breast carcinomas. The new parameter, fmass, first introduced in this paper, is defined as the ratio of the averaged minimum shear wave speed taken spatially within regions of interest to the largest mass dimension. 264 biopsy-proven breast cancerous masses were included in this study. Mean (Emean), maximum (Emax), minimum (Emin) shear wave elasticity and standard deviation (Esd) of shear wave elasticity were found significantly correlated with tumor size, axillary lymph node (ALN) status, histological subtypes and IHC subtypes. The areas under the curve for the ALN prediction are 0.73 (95% confidence interval [CI]: 0.67-0.80) and 0.75 (95% CI: 0.69-0.81) for the combination of Emean with Breast Imaging Reporting and Data System (BI-RADS) score and Emax with BI-RADS score, respectively. fmass was significantly correlated with the presence of calcifications, ALN status, histological grade, the expressions of IHC biomarkers and IHC subtypes. To conclude, poor prognostic factors were associated with high shear wave elasticity values and low mass characteristic frequency value. Therefore, SWE provides valuable information that may help with prediction of breast cancer invasiveness.

Breast Ultrasound Microvascular Imaging and Radiogenomics

Microvascular ultrasound (US) techniques are advanced Doppler techniques that provide high sensitivity and spatial resolution for detailed visualization of low-flow vessels. Microvascular US imaging can be applied to breast lesion evaluation with or without US contrast agents. Microvascular US imaging without a contrast agent uses a sophisticated wall filtering system to selectively obtain low-flow Doppler signals from overlapped artifacts. Microvascular US imaging with second-generation contrast agents amplifies flow signals and makes them last longer, which facilitates hemodynamic evaluation of breast lesions. In this review article, we will introduce various microvascular US techniques, explain their clinical applications in breast cancer diagnosis and radiologic-histopathologic correlation, and provide a summary of a recent radiogenomic study using microvascular US.

Breast Elasticity Imaging Techniques: Comparison of Strain Elastography and Shear-Wave Elastography in the Same Population

Our purpose was to compare the diagnostic performances of strain elastography (SE) and shear-wave elastography (SWE) in differentiating breast lesions by combining with conventional ultrasound (US). A total of 198 patients with 203 breast lesions underwent conventional US, SE and SWE examination using MyLab 90 and Aixplorer US systems. The SE parameters were SEscore, fat-to-lesion ratio, gland-to-lesion ratio, muscle-to-lesion ratio and SEmean, and the SWE parameters were Emax, Emean, Emin and Esd. Conventional US had the best diagnostic performance, with an area under the curve (AUC) of 0.896. Among all SE parameters, the AUCs of SEscore, fat-to-lesion ratio and SEmean were 0.802, 0.810 and 0.833. For SWE parameters, they were 0.845, 0.746 and 0.845, respectively, for Emax, Emean and Esd. When combined with US, the sensitivity and AUC of SWE seemed to be better than those of SE (96.55% vs. 93.10%, 0.958 vs. 0.947), but no statistically significant difference existed between them.

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

AIM

To assess the value of quantitative analysis of sound touch elastography of tissues around breast lesions to facilitate the evaluation of malignancy of the lesions.

MATERIALS AND METHODS

With the permission of the Ethics Committee, every patient signed informed consent forms before the study. One hundred and eighty-two solid breast lesions were analysed retrospectively. Postoperative histopathology proved that 63 lesions were malignant and 119 were benign. All lesions were examined by two-dimensional ultrasonography, colour Doppler ultrasonography and ultrasound elastography including sound touch elastography (STE) and strain elastography. Using pathological diagnosis as the reference, the correlation between each ultrasound marker and the malignancy of the solid breast masses was evaluated by chi-square test, and the logistic regression model was constructed to determine the best diagnostic model with multiple markers.

RESULTS

The areas under the receiver operating characteristic (ROC) curve (AUCs) of various elastography markers were compared and the markers with the largest AUC values, including quantitative, semi-quantitative, and distance markers were identified. Logistic regression analysis showed that the combination of accuracy of Breast Imaging Reporting and Data System (BI-RADS) classification + age + maximum elasticity value of the tissue around the lesion (EMax_shell) in predicting malignant lesions was higher than that of the other combinations. The prediction model verified that the sensitivity of diagnosis of the mammary lump was 94.12% and the specificity was 84.13%.

CONCLUSIONS

EMax_shell in the elasticity is the most valuable marker for the diagnosis of breast cancer, and age combined with EMax_shell can effectively improve the diagnostic efficacy of the BI-RADS classification in breast cancer.