Magnetic Resonance Imaging Combined With Second-look Ultrasonography in Predicting Pathologic Complete Response After Neoadjuvant Chemotherapy in Primary Breast Cancer Patients

Comparison of MRI vs. [18F]FDG PET/CT for Treatment Response Evaluation of Primary Breast Cancer after Neoadjuvant Chemotherapy: Literature Review and Future Perspectives

The purpose of this systematic review was to investigate the diagnostic accuracy of [18F]FDG PET/CT and breast MRI for primary breast cancer (BC) response assessment after neoadjuvant chemotherapy (NAC) and to evaluate future perspectives in this setting. We performed a critical review using three bibliographic databases (i.e., PubMed, Scopus, and Web of Science) for articles published up to the 6 June 2023, starting from 2012. The Quality Assessment of Diagnosis Accuracy Study (QUADAS-2) tool was adopted to evaluate the risk of bias. A total of 76 studies were identified and screened, while 14 articles were included in our systematic review after a full-text assessment. The total number of patients included was 842. Eight out of fourteen studies (57.1%) were prospective, while all except one study were conducted in a single center. In the majority of the included studies (71.4%), 3.0 Tesla (T) MRI scans were adopted. Three out of fourteen studies (21.4%) used both 1.5 and 3.0 T MRI and only two used 1.5 T. [18F]FDG was the radiotracer used in every study included. All patients accepted surgical treatment after NAC and each study used pathological complete response (pCR) as the reference standard. Some of the studies have demonstrated the superiority of [18F]FDG PET/CT, while others proved that MRI was superior to PET/CT. Recent studies indicate that PET/CT has a better specificity, while MRI has a superior sensitivity for assessing pCR in BC patients after NAC. The complementary value of the combined use of these modalities represents probably the most important tool to improve diagnostic performance in this setting. Overall, larger prospective studies, possibly randomized, are needed, hopefully evaluating PET/MR and allowing for new tools, such as radiomic parameters, to find a proper place in the setting of BC patients undergoing NAC.

Pretreatment ultrasound-based deep learning radiomics model for the early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer

OBJECTIVES

To investigate the predictive performance of the deep learning radiomics (DLR) model integrating pretreatment ultrasound imaging features and clinical characteristics for evaluating therapeutic response after neoadjuvant chemotherapy (NAC) in patients with breast cancer.

METHODS

A total of 603 patients who underwent NAC were retrospectively included between January 2018 and June 2021 from three different institutions. Four different deep convolutional neural networks (DCNNs) were trained by pretreatment ultrasound images using annotated training dataset (n = 420) and validated in a testing cohort (n = 183). Comparing the predictive performance of these models, the best one was selected for image-only model structure. Furthermore, the integrated DLR model was constructed based on the image-only model combined with independent clinical-pathologic variables. Areas under the curve (AUCs) of these models and two radiologists were compared by using the DeLong method.

RESULTS

As the optimal basic model, Resnet50 achieved an AUC and accuracy of 0.879 and 82.5% in the validation set. The integrated DLR model, yielding the highest classification performance in predicting response to NAC (AUC 0.962 and 0.939 in the training and validation cohort), outperformed the image-only model and the clinical model and also performed better than two radiologists' prediction (all p < 0.05). In addition, predictive efficacy of the radiologists was improved under the assistance of the DLR model significantly.

CONCLUSION

The pretreatment US-based DLR model could hold promise as a clinical guidance for predicting NAC response of patients with breast cancer, thereby providing benefit of timely treatment strategy adjustment to potential poor NAC responders.

KEY POINTS

• Multicenter retrospective study showed that deep learning radiomics (DLR) model based on pretreatment ultrasound image and clinical parameter achieved satisfactory prediction of tumor response to neoadjuvant chemotherapy (NAC) in breast cancer. • The integrated DLR model could become an effective tool to guide clinicians in identifying potential poor pathological responders before chemotherapy. • The predictive efficacy of the radiologists was improved under the assistance of the DLR model.

Avoiding breast cancer surgery in a select cohort of complete responders to neoadjuvant chemotherapy: The long-term outcomes

BACKGROUND

Lately, there has been a resurgence of interest in de-escalation of breast surgery in complete responders to neoadjuvant chemotherapy (NAC). Advanced cytotoxic & targeted therapies have improved tumour response.This study evaluates long-term outcomes of post-NAC breast cancer patients, in relation to their surgical management dictated by the NAC response.

MATERIALS AND METHODS

Post-NAC breast cancer patients from January 2000 to December 2010 were divided into "No surgery", "WLE" and "Mastectomy" groups. ANOVA and Kaplan-Meier statistical analyses were used to compare overall survival (OS) and disease-free-survival (DFS) in these groups.

RESULTS

This retrospective study included 121 patients with a long median follow-up of 11.5 years. At 10 years the OS was 66.10% and DFS was 59.82%. Complete NAC-responders did not undergo breast surgery but received radiotherapy. Patients were divided into No surgery (n = 28), WLE (n = 44), Mastectomy (n = 49) groups.Comparisons of OS and DFS between groups showed statistically significant differences (p = 0.0003, p = 0.0007 respectively). The no surgery group showed low local recurrence (7.14%).

CONCLUSION

The observed slightly better long-term outcomes with low local recurrences in complete NAC-responders who did not undergo breast surgery but received radiotherapy could be linked to cautious response assessment and meticulous patient selection with early, biologically favourable breast cancer.Importance of PCR assessment cannot be underestimated if breast surgery were to be de-escalated or even omitted in complete NAC-responders.Considering the study limitations, avoiding surgery in all complete NAC-responders may still not be the preferred option. Future appropriate clinical trials with well-defined protocols may pave the way forward.

Prediction of Pathologic Complete Response in Breast Cancer Patients Comparing Magnetic Resonance Imaging with Ultrasound in Neoadjuvant Setting

BACKGROUND

Some subgroups of breast cancer patients receiving neoadjuvant chemotherapy (NACT) show high rates of pathologic complete response (pCR) in the breast, proposing the possibility of omitting surgery. Prediction of pCR is dependent on accurate imaging methods. This study investigated whether magnetic resonance imaging (MRI) is better than ultrasound (US) in predicting pCR in breast cancer patients receiving NACT.

METHODS

This institutional, retrospective study enrolled breast cancer patients receiving NACT who were examined by either MRI or combined US and mammography before surgery from 2016 to 2019. Imaging findings were compared with pathologic response evaluation of the tumor. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for prediction of pCR were calculated and compared between MRI and US.

RESULTS

Among 307 patients, 151 were examined by MRI and 156 by US. In the MRI group, 37 patients (24.5 %) had a pCR compared with 51 patients (32.7 %) in the US group. Radiologic complete response (rCR) was found in 35 patients (23.2 %) in the MRI group and 26 patients (16.7 %) in the US group. In the MRI and US groups, estimates were calculated respectively for sensitivity (87.7 % vs 91.4 %), specificity (56.8 % vs 33.3 %), PPV (86.2 % vs 73.8 %), NPV (60.0 % vs 65.4 %), and accuracy (80.1 % vs 72.4 %).

CONCLUSIONS

In predicting pCR, MRI was more specific than US, but not sufficiently specific enough to be a valid predictor of pCR for omission of surgery. As an imaging method, MRI should be preferred when future studies investigating prediction of pCR in NACT patients are planned.

Early Assessment Window for Predicting Breast Cancer Neoadjuvant Therapy using Biomarkers, Ultrasound, and Diffuse Optical Tomography

PURPOSE

The purpose of the study was to assess the utility of tumor biomarkers, ultrasound (US) and US-guided diffuse optical tomography (DOT) in early prediction of breast cancer response to neoadjuvant therapy (NAT).

METHODS

This prospective HIPAA compliant study was approved by the institutional review board. Forty one patients were imaged with US and US-guided DOT prior to NAT, at completion of the first three treatment cycles, and prior to definitive surgery from February 2017 to January 2020. Miller-Payne grading was used to assess pathologic response. Receiver operating characteristic curves (ROCs) were derived from logistic regression using independent variables, including: tumor biomarkers, US maximum diameter, percentage reduction of the diameter (%US), pretreatment maximum total hemoglobin concentration (HbT) and percentage reduction in HbT (%HbT) at different treatment time points. Resulting ROCs were compared using area under the curve (AUC). Statistical significance was tested using two-sided two-sample student t-test with P < 0.05 considered statistically significant. Logistic regression was used for ROC analysis.

RESULTS

Thirty-eight patients (mean age = 47, range 24-71 years) successfully completed the study, including 15 HER2 + of which 11 were ER + ; 12 ER + or PR + /HER2-, and 11 triple negative. The combination of HER2 and ER biomarkers, %HbT at the end of cycle 1 (EOC1) and %US (EOC1) provided the best early prediction, AUC = 0.941 (95% CI 0.869-1.0). Similarly an AUC of 0.910 (95% CI 0.810-1.0) with %US (EOC1) and %HbT (EOC1) can be achieved independent of HER2 and ER status. The most accurate prediction, AUC = 0.974 (95% CI 0.933-1.0), was achieved with %US at EOC1 and %HbT (EOC3) independent of biomarker status.

CONCLUSION

The combined use of tumor HER2 and ER status, US, and US-guided DOT may provide accurate prediction of NAT response as early as the completion of the first treatment cycle.

CLINICAL TRIAL REGISTRATION NUMBER

NCT02891681. https://clinicaltrials.gov/ct2/show/NCT02891681 , Registration time: September 7, 2016.

Can breast MRI and adjunctive Doppler ultrasound improve the accuracy of predicting pathological complete response after neoadjuvant chemotherapy?

BACKGROUND

To examine the accuracy of MRI and Doppler ultrasound (US) for detecting residual tumor after neoadjuvant chemotherapy (NAC) for breast cancer and evaluate whether adjunctive Doppler US improves the MRI accuracy.

METHODS

We reviewed 276 invasive breast cancer cases treated with NAC. Tumors were classified into four subtypes based on estrogen receptor and HER2 status. Response to NAC was evaluated using contrast-enhanced MRI and Doppler US. Residual Doppler flow was assumed to indicate a residual tumor. MRI and Doppler findings were compared with the histopathological findings of resected specimens. Pathological complete response (pCR) was defined as neither in situ nor invasive cancer left.

RESULTS

Of the 276 tumors, imaging complete responses were observed using MRI and Doppler US in 62 (22%) and 111 (40%), respectively, whereas pCR was achieved in 44 (16%). MRI and Doppler US predicted residual tumor with 88% and 69% sensitivity, 80% and 91% specificity, 87% and 73% accuracy, 96% and 98% PPV, and 56% and 36% NPV, respectively. The accuracies of MRI and Doppler US were significantly higher for HER2-negative than HER2-positive tumors (p < 0.001 and p = 0.043, respectively). Seven (26%) of 27 false-negative cases identified by MRI were correctly diagnosed as positives with adjunctive Doppler US.

CONCLUSIONS

Although MRI accurately detected residual tumor with 87% accuracy, this was still not sufficient to meet clinical demands and differed with tumor subtype. Adjunctive Doppler US in cases that appear to show a complete response on MRI might reduce chances of false negatives and increase the NPV of MRI for predicting residual tumor.

Role of Magnetic Resonance Imaging in the Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy

BACKGROUND/AIM

The aim of the study was to evaluate whether residual tumor assessment by magnetic resonance imaging (MRI) after neoadjuvant chemotherapy (NACT) is fundamental for a successive surgical strategy.

PATIENTS AND METHODS

We collected 55 MRIs performed after NACT.

RESULTS

Pathological response rate was 20%. MRI's sensitivity, specificity, PPV and NPV were 50%, 88%, 54% and 86%, respectively. We observed a high variability between the different subgroups, with high number of false positives in luminal A/B tumors. Triple negative and HER2+ tumors had almost the same specificity and sensitivity (81% and 50%). Nevertheless, in the HER2+ group, PPV was greater than that in the triple negative group (71% and 33% respectively) and the NPV of the triple negative group was greater than that of the HER2+ one (90% and 64%, respectively). Statistical analysis showed a weak but significant correlation between MRI and pathological assessment of residual tumor dimension.

CONCLUSION

The present study, confirms literature data about MRI accuracy in diagnosing HER2+ and triple negative tumors, but suggests caution in case of luminal tumors' evaluation.

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.

Enhanced axillary assessment using intradermally injected microbubbles and contrast-enhanced ultrasound (CEUS) before neoadjuvant systemic therapy (NACT) identifies axillary disease missed by conventional B-mode ultrasound that may be clinically relevant

PURPOSE

The purpose of this study is to measure pre-treatment diagnostic yield of malignant lymph nodes (LN) using contrast-enhanced ultrasound (CEUS) in addition to B-mode axillary ultrasound and compare clinicopathological features, response to NACT and long-term outcomes of patients with malignant LN detected with B-mode ultrasound versus CEUS.

METHODS

Between August 2009 and October 2016, NACT patients were identified from a prospective database. Follow-up data were collected until May 2019.

RESULTS

288 consecutive NACT patients were identified; 77 were excluded, 110 had malignant LN identified by B-mode ultrasound (Group A) and 101 patients with negative B-mode axillary ultrasound had CEUS with biopsy of sentinel lymph nodes (SLN). In two cases CEUS failed. Malignant SLN were identified in 35/99 (35%) of B-mode ultrasound-negative cases (Group B). Patients in Group A were similar to those in Group B in age, mean diagnostic tumour size, grade and oestrogen receptor status. More Group A patients had a ductal phenotype. In the breast, 34 (31%) Group A patients and 8 (23%) Group B patients achieved a pathological complete response (PCR). In the axilla, 41 (37%) and 13 (37%) Groups A and B patients, respectively, had LN PCR. The systemic relapse rate was not statistically different (5% and 16% for Groups A and B, respectively).

CONCLUSIONS

Enhanced assessment with CEUS before NACT identifies patients with axillary metastases missed by conventional B-mode ultrasound. Without CEUS, 22 (63%) of cases in Group B (negative B-mode ultrasound) may have been erroneously classed as progressive disease by surgical SLN excision after NACT.

Risk Factors for Ipsilateral Breast Tumor Recurrence in Triple-Negative or HER2-Positive Breast Cancer Patients Who Achieve a Pathologic Complete Response After Neoadjuvant Chemotherapy

BACKGROUND

Attention has been focused on attempts to eliminate breast surgery for breast cancer patients who achieve a pathologic complete response after neoadjuvant chemotherapy (NAC). However, there are few data on ipsilateral breast tumor recurrence (IBTR) among patients with triple-negative or epidermal growth factor receptor 2-positive (HER2+) tumors who achieve a pathologic complete response after NAC and breast-conserving treatment.

METHODS

Using a multi-institutional retrospective database, this study evaluated the risk factors for IBTR among patients with newly diagnosed stages 1 to 3 breast cancer involving triple-negative or HER2+ tumors who achieved ypT0 after NAC and breast-conserving treatment.

RESULTS

During a median follow-up period of 4.8 years (range, 0.1-15.5 years), the 5-year IBTR-free survival rate was 95.5%. The breast cancer subtype was not associated with IBTR-free survival. Patients younger than 40 years at diagnosis had significantly worse IBTR-free survival than those who were 40 years of age or older (5-year IBTR-free survival, 87.7 vs 96.9%; p = 0.002).

CONCLUSIONS

This retrospective study demonstrated that age at diagnosis was independently associated with IBTR-free survival. Special caution is needed when clinical trials analyzing omission of breast surgery after NAC are enrolling younger patients (UMIN-CTR No. UMIN000037067).

Response and Prognosis of Docetaxel and Cyclophosphamide as Neoadjuvant Chemotherapy in ER+ HER2- Breast Cancer: A Prospective Phase II Study

BACKGROUND

Although a docetaxel and cyclophosphomide (TC) regimen without anthracycline as adjuvant therapy became one of the standard regimens especially for ER-positive (ER⁺)/human epidermal growth factor receptor 2-negative (HER2^-) primary breast cancer, the efficacy of TC as neoadjuvant chemotherapy (NAC) is not known. We conducted the prospective trial to assess the efficacy of a TC regimen in the neoadjuvant setting for stage II to III ER⁺/HER2^- primary breast cancer.

PATIENTS AND METHODS

A TC regimen that included 75 mg/m² of docetaxel and 600 mg/m² of cyclophosphamide for 4 cycles every 3 weeks was administered as NAC. Primary endpoints are the rate of clinical response (clinical partial response and clinical complete response) and pathologic complete response; secondary endpoints are the disease-free survival and overall survival rates.

RESULTS

Thirty (71.4%) of 42 tumors had clinical response. No patient achieved pathologic complete response. At the median follow-up period of 105.2 months (range, 12.1-119.7 months), the disease-free survival rate was 81.6%, and the distant disease-free survival rate was 86.8%. In terms of survival, only 1 patient died during the study period. The overall survival rate was 97.4% during the study period. Patients who developed distant recurrence had a trend to have progesterone receptor-negative or weakly positive compared with those who did not develop any recurrence (85.7% vs. 45.2%; P = .05).

CONCLUSIONS

Our prospective study showed that a TC regimen as NAC achieved a high clinical response rate in stage II to III ER⁺/HER2^- breast cancer. A TC regimen without anthracycline as NAC might be one of the options for patients with ER⁺/HER2^- breast cancer without high-risk factors including progesterone receptor negativity.

MR Elastography of the Breast: Evolution of Technique, Case Examples, and Future Directions

Recognizing that breast cancers present as firm, stiff lesions, the foundation of breast magnetic resonance elastography (MRE) is to combine tissue stiffness parameters with sensitive breast MR contrast-enhanced imaging. Breast MRE is a non-ionizing, cross-sectional MR imaging technique that provides for quantitative viscoelastic properties, including tissue stiffness, elasticity, and viscosity, of breast tissues. Currently, the technique continues to evolve as research surrounding the use of MRE in breast tissue is still developing. In the setting of a newly diagnosed cancer, associated desmoplasia, stiffening of the surrounding stroma, and necrosis are known to be prognostic factors that can add diagnostic information to patient treatment algorithms. In fact, mechanical properties of the tissue might also influence breast cancer risk. For these reasons, exploration of breast MRE has great clinical value. In this review, we will: (1) address the evolution of the various MRE techniques; (2) provide a brief overview of the current clinical studies in breast MRE with interspersed case examples; and (3) suggest directions for future research.

Prediction of Pathologic Complete Response by Ultrasonography and Magnetic Resonance Imaging After Neoadjuvant Chemotherapy in Patients with Breast Cancer

Purpose

To compare the diagnostic performance for pathologic complete response (pCR) in breast cancer after neoadjuvant chemotherapy (NAC) between ultrasound (US) and magnetic resonance imaging (MRI).

Patients and Methods

A total of 1,219 breast cancer patients with 1,232 tumors who accepted US and/or MRI examination after NAC and before breast surgery were included. The diagnostic performance of US, MRI, and US plus MRI in predicting pCR was compared.

Results

The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of US for pCR were 36.2%, 90.2%, 71.0%, 67.3%, and 71.9%, respectively, while for MRI they were 44.4%, 92.9%, 75.6%, 77.7%, and 75.0%, respectively. The combination of US and MRI had increased specificity (98.0%) and PPV (86.8%), decreased sensitivity (22.5%) and NPV (68.8%), but similar accuracy (70.5%) in comparison with US or MRI alone. The prediction of pCR by imaging differed in different histological, molecular subtypes and primary tumor size.

Conclusion

Neither US nor MRI could predict a pCR with sufficient accuracy. The combination of US and MRI could not predict a pCR reliably either. The explanation of imaging for pCR should take into account histological, molecular subtypes, and primary tumor size.