Strain wave elastography in response assessment to neo-adjuvant chemotherapy in patients with locally advanced breast cancer

Strain ultrasonic elastography imaging features of locally advanced breast cancer: association with response to neoadjuvant chemotherapy and recurrence-free survival

BACKGROUND

Due to the highly heterogeneity of the breast cancer, it would be desirable to obtain a non-invasive method to early predict the treatment response and survival outcome of the locally advanced breast cancer (LABC) patients undergoing neoadjuvant chemotherapy (NAC). This study aimed at investigating whether strain elastography (SE) can early predict the pathologic complete response (pCR) and recurrence-free survival (RFS) in LABC patients receiving NAC.

METHODS

In this single-center retrospective study, 122 consecutive women with LABC who underwent SE examination pre-NAC and after one and two cycles of NAC enrolled in the SHPD001(NCT02199418) and SHPD002 (NCT02221999) trials between January 2014 and August 2017 were included. The SE parameters (Elasticity score, ES; Strain ratio, SR; Hardness percentage, HP, and Area ratio, AR) before and during NAC were assessed. The relative changes in SE parameters after one and two cycles of NAC were describe as ΔA1 and ΔA2, respectively. Logistic regression analysis and Cox proportional hazards model were used to identify independent variables associated with pCR and RFS.

RESULTS

Forty-nine (40.2%) of the 122 patients experienced pCR. After 2 cycles of NAC, SR2 (odds ratio [OR], 1.502; P = 0.003) and ΔSR2 (OR, 0.013; P = 0.015) were independently associated with pCR, and the area under the receiver operating characteristic curve for the combination of them to predict pCR was 0.855 (95%CI: 0.779, 0.912). Eighteen (14.8%) recurrences developed at a median follow-up of 60.7 months. A higher clinical T stage (hazard ratio [HR] = 4.165; P = 0.005.), a higher SR (HR = 1.114; P = 0.002.) and AR (HR = 1.064; P <  0.001.) values at pre-NAC SE imaging were independently associated with poorer RFS.

CONCLUSION

SE imaging features have the potential to early predict pCR and RFS in LABC patients undergoing NAC, and then may offer valuable predictive information to guide personalized treatment.

Stretchable ultrasonic arrays for the three-dimensional mapping of the modulus of deep tissue

Serial assessment of the biomechanical properties of tissues can be used to aid the early detection and management of pathophysiological conditions, to track the evolution of lesions and to evaluate the progress of rehabilitation. However, current methods are invasive, can be used only for short-term measurements, or have insufficient penetration depth or spatial resolution. Here we describe a stretchable ultrasonic array for performing serial non-invasive elastographic measurements of tissues up to 4 cm beneath the skin at a spatial resolution of 0.5 mm. The array conforms to human skin and acoustically couples with it, allowing for accurate elastographic imaging, which we validated via magnetic resonance elastography. We used the device to map three-dimensional distributions of the Young's modulus of tissues ex vivo, to detect microstructural damage in the muscles of volunteers before the onset of soreness and to monitor the dynamic recovery process of muscle injuries during physiotherapies. The technology may facilitate the diagnosis and treatment of diseases affecting tissue biomechanics.

Deep Learning Model Based on Dual-Modal Ultrasound and Molecular Data for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer

RATIONALE AND OBJECTIVES

To carry out radiomics analysis/deep convolutional neural network (CNN) based on B-mode ultrasound (BUS) and shear wave elastography (SWE) to predict response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

MATERIALS AND METHODS

In this prospective study, 255 breast cancer patients who received NAC between September 2016 and December 2021 were included. Radiomics models were designed using a support vector machine classifier based on US images obtained before treatment, including BUS and SWE. And CNN models also were developed using ResNet architecture. The final predictive model was developed by combining the dual-modal US and independently associated clinicopathologic characteristics. The predictive performances of the models were assessed with five-fold cross-validation.

RESULTS

Pretreatment SWE performed better than BUS in predicting the response to NAC for breast cancer for both the CNN and radiomics models (P < 0.001). The predictive results of the CNN models were significantly better than the radiomics models, with AUCs of 0.72 versus 0.69 for BUS and 0.80 versus 0.77 for SWE, respectively (P = 0.003). The CNN model based on the dual-modal US and molecular data exhibited outstanding performance in predicting NAC response, with an accuracy of 83.60% ± 2.63%, a sensitivity of 87.76% ± 6.44%, and a specificity of 77.45% ± 4.38%.

CONCLUSION

The pretreatment CNN model based on the dual-modal US and molecular data achieved excellent performance for predicting the response to chemotherapy in breast cancer. Therefore, this model has the potential to serve as a non-invasive objective biomarker to predict NAC response and aid clinicians with individual treatments.

Predictive value of acoustic radiation force impulse imaging in breast cancer after neoadjuvant chemotherapy

To investigate the predictive value of acoustic radiation force impulse imaging for neoadjuvant chemotherapy in breast cancer. Seventy-eight breast cancer patients treated in our hospital from March 2019 to March 2022 were recruited. They received neoadjuvant chemotherapy and were examined by conventional ultrasound and acoustic radiation force impulse imaging before chemotherapy and after two cycles of chemotherapy. The lesion diameter, intralesional blood flow pulsatility index (PI), resistance index (RI), shear wave velocity (SWV), and change rate (Δlesion diameter, ΔPI, ΔRI, ΔSWV) were compared between the two groups before and after chemotherapy. The receiver operating characteristic curve was drawn to evaluate the predictive power of related parameters on the efficacy of neoadjuvant chemotherapy in breast cancer. After two cycles of neoadjuvant chemotherapy, according to the Miller-Payne grading, 57 cases (73.08%) with significant neoadjuvant chemotherapy response were classified as the response group, and 21 cases (26.92%) with non-significant response were classified as the non-response group. Before and after chemotherapy, the difference in lesion diameter, PI, RI, SWV, and change rate (Δlesion diameter, ΔPI, ΔRI, and ΔSWV) was statistically significant between the two groups (P < 0.05). The area under the curve of ΔSWV in predicting the efficacy of neoadjuvant chemotherapy 0.876 (95%CI 0.781 ~ 0.939) was significantly higher than that of Δlesion diameter 0.652 (95%CI 0.535 ~ 0.756), that of ΔPI 0.712 (95%CI 0.599 ~ 0.809), and that of ΔRI 0.678 (95%CI 0.563 ~ 0.780) (P < 0.05). The change rate of tissue stiffness has a relatively high predictive value for the effect of neoadjuvant chemotherapy in breast cancer.

Nomogram for Early Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Combining Both Clinicopathological and Imaging Indicators

To construct a nomogram for early prediction of pathological complete response (pCR) in patients with breast cancer (BC) after neoadjuvant chemotherapy (NAC). A total of 257 patients with BC from the fourth hospital of Hebei Medical University were included in the study. The patients were divided into training (n = 128) and validation groups (n = 129). Variables were screened using univariate and multivariate logistic regression analyses, and the nomogram model was set up based on the training group. The training and validation groups were validated using the receiver operating characteristic (ROC) curves and calibration plots. The diagnostic value of the nomogram was evaluated using decision curve analysis (DCA). Indicators such as hormone receptor status, clinical TNM stage, and change rate in apparent diffusion coefficient of breast magnetic resonance imaging after two NAC cycles were used for nomogram construction. The calibration plots showed high consistency between nomogram-predicted and actual pCR probabilities in the training and validation groups. The areas under the curve of the ROC curve with discrimination ability were 0.942 and 0.921 in the training and validation groups, respectively. This showed an excellent discrimination ability of our nomogram for pCR prediction. Further, DCA showed favorable diagnostic value in our model. The nomogram may be instructive to clinicians for early prediction of pCR and helpful to adjust the treatment program on time in neoadjuvant management.

Clinical studies of magnetic resonance elastography from 1995 to 2021: Scientometric and visualization analysis based on CiteSpace

BACKGROUND

To assess the knowledge framework around magnetic resonance elastography (MRE) and to explore MRE research hotspots and emerging trends.

METHODS

The Science Citation Index Expanded of the Web of Science Core Collection was searched on 22 October 2021 for MRE-related studies published between 1995 and 2021. Excel 2016 and CiteSpace V (version 5.8.R3) were used to analyze the downloaded data.

RESULTS

In all, 1,236 articles published by 726 authors from 540 institutions in 40 countries were included in this study. The top 10 authors published 57.6% of all included articles. The 3 most productive countries were the USA (n=631), Germany (n=202), and France (n=134), and the 3 most productive institutions were the Mayo Clinic (n=240), Charité (n=131), and the University of Illinois (n=56). The USA and the Mayo Clinic had the highest betweenness centrality among countries and institutions, respectively, and played an important role in the field of MRE. In this study, the 24,347 distinct references were clustered into 48 categories via reasonable clustering using specific keywords, forming the knowledge framework. Among the 294 co-occurring keywords, "hepatic fibrosis", "stiffness", "skeletal muscle", "acoustic strain wave", "in vivo", and "non-invasive assessment" were research hotspots. "Diagnostic performance", "diagnostic accuracy", "hepatic steatosis", "chronic hepatitis B", "radiation force impulse", "children", and "echo" were frontier topics.

CONCLUSIONS

Scientometric and visualized analysis of MRE can provide information regarding the knowledge framework, research hotspots, frontier areas, and emerging trends in this field.

Diagnostic Performance of Strain and Shear Wave Elastography for the Response to Neoadjuvant Chemotherapy in Breast Cancer Patients: Systematic Review and Meta-Analysis

OBJECTIVES

To investigate the diagnostic performance of strain and shear wave elastography for the response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

METHODS

Relevant studies were searched in the databases of PubMed, Web of Science and Cochrane Library until October 2021. The diagnostic performance of ultrasonic elastography for the response to NAC were estimated by calculating the area under the curve (AUC) with sensitivity and specificity using Stata 14.0.

RESULTS

A total of 15 studies that comprise 1147 breast cancer patients were included in this meta-analysis. The pooled AUC of strain elastography in diagnosing responses were 0.89 (95% CI = 0.86-0.91) with 87% (95% CI = 75-94%) of sensitivity and 80% (95% CI = 72-84%) of specificity. The pooled AUC of shear wave elastography in diagnosing response were 0.82 (95% CI = 0.78-0.85) with 79% (95% CI = 72-84%) of sensitivity and 81% (95% CI = 71-88%). No publication bias was observed across the studies using Deek's funnel plot.

CONCLUSIONS

Based on current evidence, this meta-analysis confirmed that strain and shear wave elastography exhibited favorable performance for predicting responses to NAC. Strain and shear wave elastography may be a useful, noninvasive method for the assessment of response to NAC in breast cancer patients.

Advances in Imaging in Evaluating the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer

Neoadjuvant chemotherapy (NAC) is increasingly widely used in breast cancer treatment, and accurate evaluation of its response provides essential information for treatment and prognosis. Thus, the imaging tools used to quantify the disease response are critical in evaluating and managing patients treated with NAC. We discussed the recent progress, advantages, and disadvantages of common imaging methods in assessing the efficacy of NAC for breast cancer.

Accuracy of ultrasound elastography for predicting breast cancer response to neoadjuvant chemotherapy: A systematic review and meta-analysis

BACKGROUND

Several studies have reported the prognostic value of ultrasound elastography (UE) in patients receiving neoadjuvant chemotherapy (NACT) for breast cancer. However, the assessment of parameters differed between shear-wave elastography and strain elastography in terms of measured elasticity parameter and mode of imaging. It is important, therefore, to assess the accuracy of the two modes of elastography.

AIM

To assess the accuracy of UE for predicting the pathologic complete response (pCR) in breast cancer patients following NACT.

METHODS

A comprehensive and systematic search was performed in the databases of MEDLINE, EMBASE, SCOPUS, PubMed Central, CINAHL, Web of Science and Cochrane library from inception until December 2020. Meta-analysis was performed using STATA software “Midas” package.

RESULTS

A total of 14 studies with 989 patients were included. The pooled sensitivities were 86% [95% confidence interval (CI): 76%-92%] for UE, 77% (95%CI: 68%-84%) for shear-wave elastography, and 92% (95%CI: 73%-98%) for strain-wave elastography. The pooled score specificities were 86% (95%CI: 80%-90%) for UE, 84% (95%CI: 72%-91%) for shear-wave elasticity, and 87% (95%CI: 81%-92%) for strain-wave elastography. A significant heterogeneity was found among studies based on the chi-square test results and an I² statistic > 75%.

CONCLUSION

Strain-wave type of UE can accurately predict the pCR following NACT amongst breast cancer patients. Studies exploring its accuracy in different ethnic populations are required to strengthen the evidence.

Usefulness of new shear wave elastography in early predicting the efficacy of neoadjuvant chemotherapy for patients with breast cancer: where and when to measure is optimal?

BACKGROUND

The aim of this study was to investigate the diagnosis performance of new shear wave elastography (sound touch elastography, STE) in the prediction of neoadjuvant chemotherapy (NAC) response at an early stage in breast cancer patients and to determine the optimal measurement locations around the lesion in different ranges.

METHODS

One hundred and eight patients were analyzed in this prospective study from November 2018 to December 2020. All patients completed NAC treatment and underwent STE examination at three time points [the day before NAC (t0); the day before the second course (t1); the day before third course (t2)]. The stiffness of the whole lesion (G), 1-mm shell (S1) and 2-mm shell (S2) around the lesion was expressed by STE parameters. The relative changes (∆stiffness) of STE parameters after the first and second course of NAC were calculated and shown as the variables [Δ(t1) and Δ(t2)]. The diagnostic accuracy of STE was evaluated by means of receiver operating characteristic curve analysis.

RESULTS

The ∆stiffness (%) including ∆G_mean(t2), ∆S1_mean(t2) and ∆S2_mean(t2) all showed significant differences between pathological complete response (pCR) and non-pCR groups. ∆S2_mean(t2) displayed the best predictive performance for pCR (AUC = 0.842) with an ideal ∆stiffness threshold value - 26%.

CONCLUSIONS

Measuring the relative changes in the stiffness of surrounding tissue or entire lesion with STE holds promise for effectively predicting the response to NAC at its early stage for breast cancer patients and ∆stiffness of shell 2 mm after the second course of NAC may be a potential prediction parameter.

Contrast enhanced ultrasound quantitative parameters for assessing neoadjuvant chemotherapy response in patients with locally advanced breast cancer

OBJECTIVES

To evaluate the role of contrast-enhanced ultrasound (CEUS) quantitative parameters in predicting neoadjuvant chemotherapy (NACT) response in patients with locally advanced breast cancer (LABC).

METHODS

30 patients with histologically proven LABC scheduled for NACT were recruited. CEUS was performed using a contrast bolus of 4.8 ml and time intensity curves (TICs) were obtained by contrast dynamics software. CEUS quantitative parameters assessed were peak enhancement (PE), time-to-peak (TTP), area under the curve (AUC) and mean transit time (MTT). The parameters were documented on four consecutive instances: before NACT and 3 weeks after each of the three cycles. The gold-standard was pathological response using Miller Payne Score obtained pre NACT and post-surgery.

RESULTS

A decrease in mean values of PE and an increase in mean values of TTP and MTT was observed with each cycle of NACT among responders. Post each cycle of NACT (compared with baseline pre-NACT), there was a statistically significant difference in % change of mean values of PE, TTP and MTT between good responders and poor responders (p-value < 0.05). The diagnostic accuracy of TTP post-third cycle was 87.2% (p = 0.03), and MTT post--second and third cycle was 76.7% (p = 0.004) and 86.7% (p = 0.006) respectively.

CONCLUSION

In responders, a decrease in the tumor vascularity was reflected in the CEUS quantitative parameters as a reduction in PE, and a prolongation in TTP, MTT.

ADVANCES IN KNOWLEDGE

Prediction of NACT response by CEUS has the potential to serve as a diagnostic modality for modification of chemotherapy regimens during ongoing NACT among patients with LABC, thus affecting patient prognosis.

A Novel Model Incorporating Tumor Stiffness, Blood Flow Characteristics, and Ki-67 Expression to Predict Responses After Neoadjuvant Chemotherapy in Breast Cancer

Objective

To investigate the ability of tumor stiffness, tumor blood flow, and Ki-67 expression alone or in combination in predicting the pathological response to neoadjuvant chemotherapy (NACT) in breast cancer.

Patients and Methods

This prospective cohort study included 145 breast cancer patients treated with NACT. Tumor stiffness (maximum stiffness (Emax), mean stiffness (Emean)), blood score (BS), and their relative changes, were evaluated before (t0), during (t1-t5), and at the end of NACT (t6) by shear-wave elastography and optical imaging. Ki-67 expression was quantitatively evaluated by immunohistochemistry using core biopsy specimens obtained before NACT. Pathological responses were evaluated by residual cancer burden. The ability of tumor stiffness, BS, Ki-67, and predRCB-which combined ΔEmean (t2) (the relative changes in Emean after the second NACT cycle), BS2 (BS after the second NACT cycle), and Ki-67-in predicting tumor responses was compared using receiver operating characteristic curves and the Z-test.

Results

Tumor stiffness and BS decreased during NACT. ΔEmean (t2), BS2, and Ki-67 had better predictive performance than other indexes in identifying a favorable response (AUC = 0.82, 0.81, and 0.80) and resistance responses (AUC = 0.85, 0.79, and 0.84), with no significant differences between the three (p > 0.05). PredRCB had better predictive performance than any parameter alone for a favorable response (AUC = 0.90) and resistance (AUC = 0.93).

Conclusion

Tumor stiffness, BS, and Ki-67 expression showed good and similar abilities for predicting the pathological response to NACT, and predRCB was a significantly better predictor than each index alone. These results may help design therapeutic strategies for breast cancer patients undergoing NACT.

Breast Ultrasound Versus MRI in Prediction of Pathologic Complete Response to Neoadjuvant Chemotherapy for Breast Cancer: A Systematic Review and Meta-Analysis

Introduction:

Neoadjuvant chemotherapy (NAC) is widely used to treat breast cancer. Sentinel lymph node biopsy has replaced axillary lymph node dissection in patients who convert to node-negative status, after NAC. However, few studies have evaluated the diagnostic performance of ultrasonography (US) and magnetic resonance imaging (MRI) in determining axillary lymph node status after NAC. The aim of this study was to evaluate the diagnostic performance of breast US and MRI in predicting a response to NAC, for breast cancer.

Methods:

A systematic search, in PubMed, the Cochrane Library, and Web of Science, for original studies was performed. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess the methodological quality of the included studies. Patient, study, and imaging characteristics were extracted, and sufficient data were used to reconstruct 2 × 2 tables. Data pooling, heterogeneity testing, forest plot construction, meta-regression analysis, and sensitivity analysis were performed using Meta-DiSc and Stata version 14.0 (StataCorp LP, College Station, TX, USA).

Results:

Nine studies met all the eligibility criteria and were included. The pooled sensitivity and specificity of MRI were 0.78 and 0.92, while the corresponding values for US were 0.80 and 0.90, respectively. The prevalence of pathologic complete response (pCR), among breast cancer patients, after neoadjuvant therapy was 26%. The prevalence of patients with estrogen receptor (ER)-, human epidermal growth factor receptor (HER)-, and progesterone receptor (PR)-positive tumors were 65%, 22%, and 37%, respectively.

Conclusion:

These results showed that MRI and US have almost the same accuracy in predicting pCR in patients with breast cancer undergoing neoadjuvant surgery. There is still a need for further investigations to prove that US is not inferior to MRI for this diagnosis.

Efficacy of shear-wave elastography versus dynamic optical breast imaging for predicting the pathological response to neoadjuvant chemotherapy in breast cancer

PURPOSE

Explore the value of shear-wave elastography (SWE) parameters and dynamic optical breast imaging features for predicting pathological responses to neoadjuvant chemotherapy (NACT) in breast cancer (BC).

METHOD

This prospective cohort study included 91 BC patients receiving NACT. Tumor size, SWE (maximum stiffness [Emax] and mean stiffness [Emean]), blood score (BS), and oxygen score (OS) and their relative changes were collected before (t0), during (t1-t5), and after NACT (t6). The pathological response was classified according to the residual cancer burden. Relationships between tumor size, SWE stiffness, BS, and OS at t0-t6 were analyzed, and their predictive power was compared.

RESULTS

During six NACT cycles, tumor size, tumor stiffness, and BS decreased, and tumor OS increased. ΔEmean (t2), E2mean, BS2, and OS2 had a greater power than other indexes for predicting a favorable response (AUC = 0.79, 0.71, 0.77, 0.78) and a resistance response (0.86, 0.74, 0.71, 0.71). For the favorable response, predictive power did not differ significantly between ΔEmean (t2), E2mean, BS2, and OS2, whereas for the resistance response, ΔEmean (t2) showed better prediction than E2mean, BS2, and OS2.

CONCLUSIONS

SWE stiffness, BS, and OS exhibited good and similar performances in predicting a NACT favorable response, and SWE stiffness showed better performance than BS and OS in predicting NACT resistance. These results may provide an important reference for individualized treatment in BC patients receiving NACT.

HIF-1α, TWIST-1 and ITGB-1, associated with Tumor Stiffness, as Novel Predictive Markers for the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer

Purpose

To investigate the relationship between hypoxia-inducible factor 1-alpha (HIF-1α), Twist family BHLH transcription factor 1 (TWIST-1), and β1 integrin (ITGB-1) expression and tumor stiffness, and evaluate performance of HIF-1α, TWIST-1, and ITGB-1 alone and in combination with Ki-67 for predicting pathological responses to neoadjuvant chemotherapy (NACT) in breast cancer (BC).

Patients and Methods

This was a prospective cohort study of 104 BC patients receiving NACT. Tumor stiffness and oxygen score (OS) were evaluated before NACT by shear-wave elastography and optical imaging; HIF-1α, TWIST-1, ITGB-1, and Ki-67 expression were quantitatively assessed by immunohistochemistry of paraffin-embedded tumor samples obtained by core needle biopsy. Indexes were compared among different residual cancer burden (RCB) groups, and associations of HIF-1α, TWIST-1, ITGB-1, and Ki-67 with tumor stiffness and OS were examined. The value of HIF-1α, TWIST-1, ITGB-1, and Ki-67, and a possible new combined index (predRCB) for predicting NACT responses was assessed by receiver operating characteristic (ROC) curves.

Results

HIF-1α, TWIST-1, and ITGB-1 expression were positively correlated with tumor stiffness and negatively with OS. Area under the ROC curves (AUCs) measuring the performance of HIF-1α, TWIST-1, ITGB-1, and Ki-67 for predicting responses to NACT were 0.81, 0.85, 0.79, and 0.80 for favorable responses, and 0.83, 0.86, 0.84, and 0.85 for resistant responses, respectively. PredRCB showed better prediction than the other individual indexes for favorable responses (AUC = 0.88) and resistant responses (AUC = 0.92).

Conclusion

HIF-1α, TWIST-1, ITGB-1, and Ki-67 performed well in predicting favorable responses and resistance to NACT, and predRCB improved the predictive power of the individual indexes. These results support individualized treatment of BC patients receiving NACT.