Magnetic resonance imaging as a predictor of pathologic response in patients treated with neoadjuvant systemic treatment for operable breast cancer. Translational Breast Cancer Research Consortium trial 017

Breast Tumor-Bed Biopsy for Pathological Complete Response Prediction: The NRG-BR005 Nonrandomized Clinical Trial

Importance

Use of modern neoadjuvant chemotherapy (NAC) regimens has markedly increased rates of pathologic complete response (pCR) in breast cancer, raising the question of whether surgical removal of the primary tumor is required for patients with pCR. For surgery to be omitted, one must be able to accurately predict pCR before surgery.

Objective

To investigate if adding post-NAC core needle biopsy of the tumor bed to trimodality imaging in patients who have clinical complete response (cCR) will predict pCR (resolution of both invasive disease and ductal carcinoma in situ) in 90% or more cases.

Design, Setting, and Participants

This was a phase 2, prospective, nonrandomized clinical trial. Patients were enrolled from August 2017 to June 2019. This is the final analysis, which was completed in December 2023. The setting included academic and community hospital center members of NRG (ie, the National Surgical Adjuvant Breast and Bowel Project, the Radiation Therapy Oncology Group, and the Gynecologic Oncology Group) in the US and Canada. Patients with operable (T1-T3, stage I-III) invasive ductal carcinoma who completed NAC and achieved cCR and radiological complete response (rCR) or near rCR by mammography (mass ≤1 cm and no malignant microcalcifications), ultrasound (mass ≤2 cm), and magnetic resonance imaging (no mass with rapid rise or washout kinetics).

Interventions

Patients underwent marker-directed stereotactic multiple-core needle biopsy of the tumor bed with marker placement before breast-conservation surgery.

Main Outcomes and Measures

End points were negative predictive value (NPV) and sensitivity of the biopsy.

Results

A total of 105 patients were enrolled with 101 evaluable (mean [SD] age, 52.8 [10.5] years); 77 patients (76.2%) were younger than 60 years, and all breast cancer subtypes were represented with 32 (31.7%) triple-negative breast cancer, 21 (20.8%) hormone receptor-positive/epidermal growth factor receptor 2 (ERBB2; formerly HER2)-negative (ERBB2-) breast cancer, and 46 (45.5%) ERBB2-positive (ERBB2+) breast cancer. In 101 evaluable patients, 36 had residual disease at surgery (pCR = 64%). With imaging criteria, NPV of the biopsy was 78.3% (95% CI, 67.9%-86.6%), and the sensitivity of the biopsy was 50% (95% CI, 32.9%-67.1%). In an exploratory subset analysis, the NPV in patients with ERBB2+ breast cancer was 90% (95% CI, 76.3%-97.2%). On retrospective central review, 62 of 101 enrolled patients met imaging eligibility criteria. In this exploratory post hoc analysis, NPV in these patients was 86.8% (95% CI, 74.7%-94.5%).

Conclusions and Relevance

These findings do not support breast conservation treatment without surgery based on the study criteria for cCR and rCR/near rCR by trimodality imaging and negative tumor-bed biopsy. Strict adherence to imaging criteria may be required to achieve acceptable predictive values.

TRIAL Registration

ClinicalTrials.gov Identifier: NCT03188393.

Combined morphology and radiomics of intravoxel incoherent movement as a predictive model for the pathologic complete response before neoadjuvant chemotherapy in patients with breast cancer

Background

To develop a predictive model using baseline imaging of morphology and radiomics derived from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) to determine the pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) in breast cancer patients.

Methods

A total of 265 patients who underwent 3.0 T MRI scans before NACT were examined. Among them, 113 female patients with stage II-III breast cancer were included. The training data set consisted of 79 patients (31/48=pCR/Non-PCR, npCR), while the remaining 34 cases formed the validation cohort (13/21=pCR/npCR). Radiomics and conventional magnetic resonance imaging features analysis were performed. To build a nomogram model that integrates the radiomics signature and conventional imaging, a logistic regression method was employed. The performance evaluation of the nomogram involved the area under the receiver operating characteristic curve (AUC), a decision curve analysis, and the calibration slope.

Results

In an assessment for predicting pCR, the radiomics model displayed an AUC of 0.778 and 0.703 for the training and testing cohorts, respectively. Conversely, the morphology model exhibited an AUC of 0.721 and 0.795 for the training and testing cohorts, respectively. The nomogram displayed superior predictive discrimination with an AUC of 0.862 for the training cohort and 0.861 for the testing cohort. Decision curve analyses indicated that the nomogram provided the highest clinical net benefit.

Conclusion

Performing a nomogram consisting of integrated morphology and radiomics assessment using IVIM-DWI before NACT enables effective prediction of pCR in breast cancer. This predictive model therefore can facilitate medical professionals in making individualized treatment decisions.

Diffusion-weighted imaging in addition to contrast-enhanced MRI in identifying complete response in HER2-positive breast cancer

OBJECTIVES

The aim of this study is to investigate the added value of diffusion-weighted imaging (DWI) to dynamic-contrast enhanced (DCE)-MRI to identify a pathological complete response (pCR) in patients with HER2-positive breast cancer and radiological complete response (rCR).

MATERIALS AND METHODS

This is a single-center observational study of 102 patients with stage I-III HER2-positive breast cancer and real-world documented rCR on DCE-MRI. Patients were treated between 2015 and 2019. Both 1.5 T/3.0 T single-shot diffusion-weighted echo-planar sequence were used. Post neoadjuvant systemic treatment (NST) diffusion-weighted images were reviewed by two readers for visual evaluation and ADCmean. Discordant cases were resolved in a consensus meeting. pCR of the breast (ypT0/is) was used to calculate the negative predictive value (NPV). Breast pCR-percentages were tested with Fisher's exact test. ADCmean and ∆ADCmean(%) for patients with and without pCR were compared using a Mann-Whitney U-test.

RESULTS

The NPV for DWI added to DCE is 86% compared to 87% for DCE alone in hormone receptor (HR)-/HER2-positive and 67% compared to 64% in HR-positive/HER2-positive breast cancer. Twenty-seven of 39 non-rCR DWI cases were false positives. In HR-positive/HER2-positive breast cancer the NPV for DCE MRI differs between MRI field strength (1.5 T: 50% vs. 3 T: 81% [p = 0.02]). ADCmean at baseline, post-NST, and ∆ADCmean were similar between patients with and without pCR.

CONCLUSION

DWI has no clinically relevant effect on the NPV of DCE alone to identify a pCR in early HER2-positive breast cancer. The added value of DWI in HR-positive/HER2-positive breast cancer should be further investigated taken MRI field strength into account.

CLINICAL RELEVANCE STATEMENT

The residual signal on DWI after neoadjuvant systemic therapy in cases with early HER2-positive breast cancer and no residual pathologic enhancement on DCE-MRI breast should not (yet) be considered in assessing a complete radiologic response.

KEY POINTS

Radiologic complete response is associated with a pathologic complete response (pCR) in HER2+ breast cancer but further improvement is warranted. No relevant increase in negative predictive value was observed when DWI was added to DCE. Residual signal on DW-images without pathologic enhancement on DCE-MRI, does not indicate a lower chance of pCR.

Ultrafast Dynamic Contrast-Enhanced MRI of the Breast: From Theory to Practice

The development of ultrafast dynamic contrast-enhanced (UF-DCE) MRI has occurred in tandem with fast MRI scan techniques, particularly view-sharing and compressed sensing. Understanding the strengths of each technique and optimizing the relevant parameters are essential to their implementation. UF-DCE MRI has now shifted from research protocols to becoming a part of clinical scan protocols for breast cancer. UF-DCE MRI is expected to compensate for the low specificity of abbreviated MRI by adding kinetic information from the upslope of the time-intensity curve. Because kinetic information from UF-DCE MRI is obtained from the shape and timing of the initial upslope, various new kinetic parameters have been proposed. These parameters may be associated with receptor status or prognostic markers for breast cancer. In addition to the diagnosis of malignant lesions, more emphasis has been placed on predicting and evaluating treatment response because hyper-vascularity is linked to the aggressiveness of breast cancers. In clinical practice, it is important to note that breast lesion images obtained from UF-DCE MRI are slightly different from those obtained by conventional DCE MRI in terms of morphology. A major benefit of using UF-DCE MRI is avoidance of the marked or moderate background parenchymal enhancement (BPE) that can obscure the target enhancing lesions. BPE is less prominent in the earlier phases of UF-DCE MRI, which offers better lesion-to-noise contrast. The excellent contrast of early-enhancing vessels provides a key to understanding the detailed pathological structure of tumor-associated vessels. UF-DCE MRI is normally accompanied by a large volume of image data for which automated/artificial intelligence-based processing is expected to be useful. In this review, both the theoretical and practical aspects of UF-DCE MRI are summarized. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Predictive value of ultrasound doppler parameters in neoadjuvant chemotherapy response of breast cancer: Prospective comparison with magnetic resonance and mammography

BACKGROUND

Neoadjuvant chemotherapy (NACT) is a treatment option for breast cancer patients that allows for the assessment of tumor response during treatment. This information can be used to adjust treatment and improve outcomes. However, the optimal imaging modalities and parameters for assessing tumor response to NACT are not well established.

METHODS

This study included 173 breast cancer patients who underwent NACT. Patients were imaged with ultrasound (US), mammography (MMG), and magnetic resonance imaging (MRI) at baseline, after two cycles of NACT, and before breast surgery. US parameters included lesion morphology, Doppler variables, and elastography measurements. MMG and MRI were evaluated for the presence of nodules and tumor dimensions. The pathological response to NACT was determined using the residual cancer burden (RCB) classification.

RESULTS

The US parameter with the highest power for predicting pathological complete response (pCR) was shear wave elastography (SWE) maximum speed inside the tumor at baseline. For nonluminal tumors, the end diastolic velocity measured by US after two cycles of NACT showed the highest predictive value for pCR. Similarly, SWE maximum speed after two cycles of NACT had the highest discriminating power for predicting RCB-III in luminal tumors, while the same parameter measured at baseline was most predictive for nonluminal tumors.

CONCLUSIONS

This study provides evidence that mid-treatment Doppler US and other imaging modalities can be used to predict the response to NACT in breast cancer patients. Functional parameters, such as blood flow velocities and SWE measurements, demonstrated superior predictive value for pCR, while morphological parameters had limited value. These findings have implications for personalized treatment strategies and may contribute to improved outcomes in the management of breast cancer.

MRI-guided optimisation of neoadjuvant chemotherapy duration in stage II-III HER2-positive breast cancer (TRAIN-3): a multicentre, single-arm, phase 2 study

BACKGROUND

Patients with stage II-III HER2-positive breast cancer have good outcomes with the combination of neoadjuvant chemotherapy and HER2-targeted agents. Although increasing the number of chemotherapy cycles improves pathological complete response rates, early complete responses are common. We investigated whether the duration of chemotherapy could be tailored on the basis of radiological response.

METHODS

TRAIN-3 is a single-arm, phase 2 study in 43 hospitals in the Netherlands. Patients with stage II-III HER2-positive breast cancer aged 18 years or older and a WHO performance status of 0 or 1 were enrolled. Patients received neoadjuvant chemotherapy consisting of paclitaxel (80 mg/m2 of body surface area on day 1 and 8 of each 21 day cycle), trastuzumab (loading dose on day 1 of cycle 1 of 8 mg/kg bodyweight, and then 6 mg/kg on day 1 on all subsequent cycles), and carboplatin (area under the concentration time curve 6 mg/mL per min on day 1 of each 3 week cycle) and pertuzumab (loading dose on day 1 of cycle 1 of 840 mg, and then 420 mg on day 1 of each subsequent cycle), all given intravenously. The response was monitored by breast MRI every three cycles and lymph node biopsy. Patients underwent surgery when a complete radiological response was observed or after a maximum of nine cycles of treatment. The primary endpoint was event-free survival at 3 years; however, follow-up for the primary endpoint is ongoing. Here, we present the radiological and pathological response rates (secondary endpoints) of all patients who underwent surgery and the toxicity data for all patients who received at least one cycle of treatment. Analyses were done in hormone receptor-positive and hormone receptor-negative patients separately. This trial is registered with ClinicalTrials.gov, number NCT03820063, recruitment is closed, and the follow-up for the primary endpoint is ongoing.

FINDINGS

Between April 1, 2019, and May 12, 2021, 235 patients with hormone receptor-negative cancer and 232 with hormone receptor-positive cancer were enrolled. Median follow-up was 26·4 months (IQR 22·9-32·9) for patients who were hormone receptor-negative and 31·6 months (25·6-35·7) for patients who were hormone receptor-positive. Overall, the median age was 51 years (IQR 43-59). In 233 patients with hormone receptor-negative tumours, radiological complete response was seen in 84 (36%; 95% CI 30-43) patients after one to three cycles, 140 (60%; 53-66) patients after one to six cycles, and 169 (73%; 66-78) patients after one to nine cycles. In 232 patients with hormone receptor-positive tumours, radiological complete response was seen in 68 (29%; 24-36) patients after one to three cycles, 118 (51%; 44-57) patients after one to six cycles, and 138 (59%; 53-66) patients after one to nine cycles. Among patients with a radiological complete response after one to nine cycles, a pathological complete response was seen in 147 (87%; 95% CI 81-92) of 169 patients with hormone receptor-negative tumours and was seen in 73 (53%; 44-61) of 138 patients with hormone receptor-positive tumours. The most common grade 3-4 adverse events were neutropenia (175 [37%] of 467), anaemia (75 [16%]), and diarrhoea (57 [12%]). No treatment-related deaths were reported.

INTERPRETATION

In our study, a third of patients with stage II-III hormone receptor-negative and HER2-positive breast cancer had a complete pathological response after only three cycles of neoadjuvant systemic therapy. A complete response on breast MRI could help identify early complete responders in patients who had hormone receptor negative tumours. An imaging-based strategy might limit the duration of chemotherapy in these patients, reduce side-effects, and maintain quality of life if confirmed by the analysis of the 3-year event-free survival primary endpoint. Better monitoring tools are needed for patients with hormone receptor-positive and HER2-positive breast cancer.

FUNDING

Roche Netherlands.

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.

Assessment of Pathological Complete Response Using Vacuum-Assisted Biopsy in Breast Cancer Patients Who Have Clinical and Radiological Complete Response After Neo-Adjuvant Chemotherapy

Background

Any treatment protocol that leads to complete elimination of surgery may lead to a better patient acceptance of breast cancer treatments.

Objectives

We conducted this study to assess the feasibility of preoperative vacuum-assisted biopsies in identifying pathological complete response (pCR) and its accuracy in correlation to final histopathology report (HPR), in an Indian setting.

Methods

This was a prospective study conducted between October 1, 2019, and March 31, 2021. Patients with early breast cancer, estrogen and progesterone receptors negative and either Her2 positive or negative, and who were fit to undergo marker placement at the centre of the tumour and to receive third-generation chemotherapy (4 cycles of 3 weekly doxorubicin and cyclophosphamide followed by 4 cycles of 3 weekly docetaxel) were included in the study. Following the enrolment, a tissue marker was placed at the centre of the tumour and appropriate chemotherapy was started. Patients who achieved clinical complete response were subjected to ultrasound-guided vacuum-assisted biopsy (VAB) from the tumour bed before surgery. Pathology results of the VAB and resected specimen were then compared. Descriptive statistics were used in the study.

Results

Eighteen patients were enrolled in the study, with a mean age of 43.6 ± 9.8 years. However, only 10 were eligible for VAB procedure, and sensitivity and specificity were calculated based on the results of these 10 patients only. Vacuum-assisted biopsy showed sensitivity of 50% and specificity of 100% in identifying pCR. Combination of mammography, ultrasonography, and VAB showed sensitivity of 77.8% and specificity of 66.7% in identifying pCR.

Conclusion

Vacuum-assisted biopsy of tumour bed may not be sensitive enough to eliminate surgery even in patients who have had exceptional response to neo-adjuvant chemotherapy.

89Zr-Trastuzumab PET/CT Imaging of HER2-Positive Breast Cancer for Predicting Pathological Complete Response after Neoadjuvant Systemic Therapy: A Feasibility Study

BACKGROUND

Approximately 20% of invasive ductal breast malignancies are human epidermal growth factor receptor 2 (HER2)-positive. These patients receive neoadjuvant systemic therapy (NAT) including HER2-targeting therapies. Up to 65% of patients achieve a pathological complete response (pCR). These patients might not have needed surgery. However, accurate preoperative identification of a pCR remains challenging. A radiologic complete response (rCR) on MRI corresponds to a pCR in only 73% of patients. The current feasibility study investigates if HER2-targeted PET/CT-imaging using Zirconium-89 (89Zr)-radiolabeled trastuzumab can be used for more accurate NAT response evaluation.

METHODS

HER2-positive breast cancer patients scheduled to undergo NAT and subsequent surgery received a 89Zr-trastuzumab PET/CT both before (PET/CT-1) and after (PET/CT-2) NAT. Qualitative and quantitative response evaluation was performed.

RESULTS

Six patients were enrolled. All primary tumors could be identified on PET/CT-1. Four patients had a pCR and two a pathological partial response (pPR) in the primary tumor. Qualitative assessment of PET/CT resulted in an accuracy of 66.7%, compared to 83.3% of the standard-of-care MRI. Quantitative assessment showed a difference between the SUVR on PET/CT-1 and PET/CT-2 (ΔSUVR) in patients with a pPR and pCR of -48% and -90% (p = 0.133), respectively. The difference in tumor-to-blood ratio on PET/CT-1 and PET/CT-2 (ΔTBR) in patients with pPR and pCR was -79% and -94% (p = 0.133), respectively. Three patients had metastatic lymph nodes at diagnosis that were all identified on PET/CT-1. All three patients achieved a nodal pCR. Qualitative assessment of the lymph nodes with PET/CT resulted in an accuracy of 66.7%, compared to 50% of the MRI.

CONCLUSIONS

NAT response evaluation using 89Zr-trastuzumab PET/CT is feasible. In the current study, qualitative assessment of the PET/CT images is not superior to standard-of-care MRI. Our results suggest that quantitative assessment of 89Zr-trastuzumab PET/CT has potential for a more accurate response evaluation of the primary tumor after NAT in HER2-positive breast cancer.

Predictors of successful neoadjuvant treatment in HER2‑positive breast cancer

The prognosis of local or locally advanced human epidermal growth factor receptor 2 (HER2)-positive breast cancer after a complete response from neoadjuvant systemic treatment (NAT) is excellent. However, some of the patients succumb to their disease, so novel predictive factors to identify these patients at risk are needed. Retrospective data from 119 patients treated at the Helsinki University Hospital Comprehensive Cancer Centre (Helsinki, Finland) were collected. All patients had in situ hybridization-confirmed HER2-positive breast cancer and underwent NAT with a curative intention. The primary tumours were relatively large, most patients had cytologically confirmed lymph node metastases and the treatments used were current regimens. A total of 63 (52.1%) patients had a pathological complete response (pCR) to neoadjuvant therapy. Achieving pCR predicted longer disease-free survival (DFS; P=0.0083) but not overall survival (P=0.061). The patients with a pCR had an estimated DFS rate of 96.8% at 5 years, compared with only 59.7% of the patients with non-pCR. Radiological complete response (CR) was associated with pCR (P=0.00033), although imaging yielded 30.4% false-negative and 36.9% false-positive results. The association between the radiological CR and pCR was more obvious in oestrogen receptor-negative tumours. Moderate (compared with strong) immunohistochemical HER2 expression predicted a lower chance of pCR (P=0.0078) and worse breast cancer-specific survival (P=0.0015). In conclusion, pCR after NAT served as an important prognostic factor in women with high-risk HER2-positive breast cancer. The patients with only moderate immunohistochemical HER2 expression had a lower chance of reaching a pCR, as well as a shorter breast cancer-specific survival.

Triple-Negative Breast Cancer: Histopathologic Features, Genomics, and Treatment

Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive group of tumors that are defined by the absence of estrogen and progesterone receptors and lack of ERBB2 (formerly HER2 or HER2/neu) overexpression. TNBC accounts for 8%-13% of breast cancers. In addition, it accounts for a higher proportion of breast cancers in younger women compared with those in older women, and it disproportionately affects non-Hispanic Black women. TNBC has high metastatic potential, and the risk of recurrence is highest during the 5 years after it is diagnosed. TNBC exhibits benign morphologic imaging features more frequently than do other breast cancer subtypes. Mammography can be suboptimal for early detection of TNBC owing to factors that include the fast growth of this cancer, increased mammographic density in young women, and lack of the typical features of malignancy at imaging. US is superior to mammography for TNBC detection, but benign-appearing features can lead to misdiagnosis. Breast MRI is the most sensitive modality for TNBC detection. Most cases of TNBC are treated with neoadjuvant chemotherapy, followed by surgery and radiation. MRI is the modality of choice for evaluating the response to neoadjuvant chemotherapy. Survival rates for individuals with TNBC are lower than those for persons with hormone receptor-positive and human epidermal growth factor receptor 2-positive cancers. The 5-year survival rates for patients with localized, regional, and distant disease at diagnosis are 91.3%, 65.8%, and 12.0%, respectively. The early success of immunotherapy has raised hope regarding the development of personalized strategies to treat TNBC. Imaging and tumor biomarkers are likely to play a crucial role in the prediction of TNBC treatment response and TNBC patient survival in the future. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Can breast MRI predict pathologic response following neoadjuvant chemotherapy for breast cancer? A retrospective cohort study

PURPOSE

For patients treated with neoadjuvant chemotherapy (NAC) for breast cancer, it is standard of care to perform pre- and post-NAC imaging to evaluate response to therapy prior to surgery. In this study we assess outcome metrics of magnetic resonance imaging (MRI) following NAC.

METHODS

We conducted a retrospective analysis of patients with invasive breast cancer who underwent a breast MRI before and after NAC between 2016 and 2021 at a single, multisite academic institution. All breast MRI studies were characterized as either radiologic complete response (rCR) or non-rCR. Corresponding surgical pathology reports were reviewed and categorized as pathologic complete response (pCR) or non-pCR. We defined a positive test as having residual enhancement on MRI (non-rCR) and a positive outcome as having residual disease on final surgical pathology (non-pCR).

RESULTS

There were 225 patients included in the study (mean age 52 ± 12 years). Breast cancer receptor distribution was HR+/HER2- (n = 71, 32%), HR+/HER2+ (n = 51, 23%), HR-/HER2- (n = 72, 32%), and HR-/HER2+ (n = 31, 14%). In total, 78 (35%) had rCR and 77 (34%) had pCR; 43 (19%) had both rCR and pCR. The overall accuracy rate was 69% (156/225), sensitivity 76% (113/148), specificity 56% (43/77), positive predictive value 77% (113/147), and negative predictive value 55% (43/78). The PPV was significantly associated with receptor status (p = 0.004). No patient or imaging characteristics were associated with sensitivity.

CONCLUSION

Breast MRI only moderately predicts pathologic response for invasive breast cancer treated with NAC (overall accuracy 69%). PPV is significantly associated with receptor status.

ACR Appropriateness Criteria® Monitoring Response to Neoadjuvant Systemic Therapy for Breast Cancer: 2022 Update

Imaging plays a vital role in managing patients undergoing neoadjuvant chemotherapy, as treatment decisions rely heavily on accurate assessment of response to therapy. This document provides evidence-based guidelines for imaging breast cancer before, during, and after initiation of neoadjuvant chemotherapy. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Patient-Related Characteristics Associated with Treatment Modifications and Suboptimal Relative Dose Intensity of Neoadjuvant Chemotherapy in Patients with Breast Cancer-A Retrospective Study

BACKGROUND

Reduced relative dose intensity (RDI) of neoadjuvant chemotherapy (NACT) in patients with breast cancer may compromise treatment outcome and survival. We examined patient-related characteristics associated with treatment modifications and suboptimal RDI and tumour response in patients with breast cancer.

METHODS

In this observational study, electronic medical records were reviewed retrospectively for female patients with breast cancer scheduled for NACT at a university hospital in Denmark between 2017 and 2019. The RDI (ratio of delivered dose intensity in relation to standard dose intensity) was calculated. Multivariate logistic regression analyses examined associations of sociodemographics, general health and clinical cancer characteristics with dose reductions, dose delays, discontinuation of NACT and suboptimal RDI < 85%.

RESULTS

Among 122 included patients, 43%, 42% and 28% experienced dose reductions, dose delays ≥3 days and discontinuation, respectively. A total of 25% received an RDI < 85%. Comorbidity, taking long-term medications and being overweight were statistically significantly associated with treatment modifications, while age ≥ 65 years and comorbidity were associated with RDI < 85%. Around one third of all patients had radiologic (36%) or pathologic (35%) complete tumour response, with no statistically significant differences by RDI < or ≥85% irrespective of breast cancer subtype.

CONCLUSIONS

While most patients had RDI ≥85%, still one out of four patients received an RDI < 85%. Further investigations of possible supportive care initiatives to improve patients' treatment tolerability are needed, particularly among subgroups of older age or with comorbidity.

Surgical Planning after Neoadjuvant Treatment in Breast Cancer: A Multimodality Imaging-Based Approach Focused on MRI

Neoadjuvant chemotherapy (NACT) today represents a cornerstone in the treatment of locally advanced breast cancer and highly chemo-sensitive tumors at early stages, increasing the possibilities of performing more conservative treatments and improving long term outcomes. Imaging has a fundamental role in the staging and prediction of the response to NACT, thus aiding surgical planning and avoiding overtreatment. In this review, we first examine and compare the role of conventional and advanced imaging techniques in preoperative T Staging after NACT and in the evaluation of lymph node involvement. In the second part, we analyze the different surgical approaches, discussing the role of axillary surgery, as well as the possibility of non-operative management after-NACT, which has been the subject of recent trials. Finally, we focus on emerging techniques that will change the diagnostic assessment of breast cancer in the near future.

Surgical Management of the Axilla for Breast Cancer

This review discusses the contemporary surgical management of the axilla in patients with breast cancer. Surgical paradigms are highlighted by clinical nodal status at presentation and treatment approach, including upfront surgery and neoadjuvant systemic therapy settings. This review focuses on the increasing opportunities for de-escalating the extent of axillary surgery in the era of sentinel lymph node biopsy, while also reviewing the remaining indications for axillary clearance with axillary lymph node dissection.

Comparison of automated breast volume scanning with conventional ultrasonography, mammography, and MRI to assess residual breast cancer after neoadjuvant therapy by molecular type

AIM

To compare the accuracy of hand-held ultrasonography (US), mammography (MG), magnetic resonance imaging (MRI), and automated breast volume scanning (ABVS) in defining residual breast cancer tumour size after neoadjuvant therapy (NAT).

MATERIALS AND METHODS

Patients diagnosed breast cancer and who received NAT at the Breast Center, Peking University People's Hospital, were enrolled prospectively. Imaging was performed after the last cycle of NAT. The residual tumour size, intraclass correlation coefficients (ICCs), and receiver operating characteristic (ROC) to predict pathological complete response (pCR) were analysed.

RESULTS

A total of 156 patients with 159 tumours were analysed. ABVS had a moderate correlation with histopathology residual tumour size (ICC = 0.666), and showed high agreement among triple-positive tumours (ICC = 0.797). With 5 mm as the threshold, the coincidence rate reached 64.7% between ABVS and pathological size, which was significantly higher than that between US, MG, MRI, and pathological size (50%, 45.1%, 41.4%; p=0.009, p=0.001, p<0.001, respectively). For ROC analysis, ABVS demonstrated a higher area under the ROC curve, but with no statistical difference, except for MG (0.855, 0.816, 0.819, and 0.788, respectively; p=0.183 for US, p=0.044 for MG, and p=0.397 for MRI, with ABVS as the reference).

CONCLUSIONS

The longest tumour diameter on ABVS had a moderate correlation with pathological residual invasive tumour size. ABVS was shown to have good ability to predict pCR and would appear to be a potential useful tool for the assessment after NAT for breast cancer.

Patient perspectives on repeated contrast-enhanced mammography and magnetic resonance during neoadjuvant chemotherapy of breast cancer

BACKGROUND

The burden perceived by the patient of repeated imaging required for neoadjuvant chemotherapy (NAC) monitoring warrants attention due to the increased use of NAC and imaging.

PURPOSE

To evaluate and compare the experienced burden associated with repeated contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) during NAC for breast cancer from the patient perspective.

MATERIAL AND METHODS

Approval from the ethics committee and written informed consent were obtained. In this prospective study, CEM and MRI were performed on 38 patients with breast cancer before, during, and after NAC in a tertiary cancer center. The experienced burden was evaluated with a self-reported questionnaire addressing duration, comfort, anxiety, positioning, and intravenous contrast administration, each measured on a 5-point Likert scale. The participants were asked their preference between CEM or MRI. Statistical comparisons were performed and P<0.05 was considered significant.

RESULTS

Most participants (n = 29, 76%) preferred CEM over MRI (P = 0.0008). CEM was associated with a significantly shorter duration (P < 0.001), greater overall comfort (P < 0.01), more comfortable positioning (P = 0.01), and lower anxiety (P = 0.03). Intravenous contrast administration perception revealed no significant difference. Only 4 (10%) participants preferred MRI over CEM, due to the absence of breast compression.

CONCLUSION

In the hypothetical scenario of equal diagnostic accuracy, most participants preferred CEM and compared CEM favorably to MRI in all investigated features at repeated imaging required for NAC response assessment. Our results indicate that repeated examinations with CEM is well tolerated and constitutes a patient-friendly alternative for NAC imaging monitoring in breast cancer.

Deep Learning Prediction of Pathologic Complete Response in Breast Cancer Using MRI and Other Clinical Data: A Systematic Review

Breast cancer patients who have pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) are more likely to have better clinical outcomes. The ability to predict which patient will respond to NAC early in the treatment course is important because it could help to minimize unnecessary toxic NAC and to modify regimens mid-treatment to achieve better efficacy. Machine learning (ML) is increasingly being used in radiology and medicine because it can identify relationships amongst complex data elements to inform outcomes without the need to specify such relationships a priori. One of the most popular deep learning methods that applies to medical images is the Convolutional Neural Networks (CNN). In contrast to supervised ML, deep learning CNN can operate on the whole images without requiring radiologists to manually contour the tumor on images. Although there have been many review papers on supervised ML prediction of pCR, review papers on deep learning prediction of pCR are sparse. Deep learning CNN could also incorporate multiple image types, clinical data such as demographics and molecular subtypes, as well as data from multiple treatment time points to predict pCR. The goal of this study is to perform a systematic review of deep learning methods that use whole-breast MRI images without annotation or tumor segmentation to predict pCR in breast cancer.

A spatial attention guided deep learning system for prediction of pathological complete response using breast cancer histopathology images

MOTIVATION

Predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) patients accurately is direly needed for clinical decision making. pCR is also regarded as a strong predictor of overall survival. In this work, we propose a deep learning system to predict pCR to NAC based on serial pathology images stained with hematoxylin and eosin and two immunohistochemical biomarkers (Ki67 and PHH3). To support human prior domain knowledge-based guidance and enhance interpretability of the deep learning system, we introduce a human knowledge-derived spatial attention mechanism to inform deep learning models of informative tissue areas of interest. For each patient, three serial breast tumor tissue sections from biopsy blocks were sectioned, stained in three different stains and integrated. The resulting comprehensive attention information from the image triplets is used to guide our prediction system for prognostic tissue regions.

RESULTS

The experimental dataset consists of 26 419 pathology image patches of 1000×1000 pixels from 73 TNBC patients treated with NAC. Image patches from randomly selected 43 patients are used as a training dataset and images patches from the rest 30 are used as a testing dataset. By the maximum voting from patch-level results, our proposed model achieves a 93% patient-level accuracy, outperforming baselines and other state-of-the-art systems, suggesting its high potential for clinical decision making.

AVAILABILITY AND IMPLEMENTATION

The codes, the documentation and example data are available on an open source at: https://github.com/jkonglab/PCR_Prediction_Serial_WSIs_biomarkers.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A review of studies on omitting surgery after neoadjuvant chemotherapy in breast cancer

The advancement in systemic neoadjuvant therapy has significantly increased the pathological complete response (pCR) rate in breast cancer. As surgeries inevitably affect patients physically and psychologically and the accuracy of pCR prediction and diagnosis by minimal invasive biopsy is improving, the necessity of surgery in neoadjuvant chemotherapy (NAC) patients who achieve pCR is under debate. Thus, we conducted a literature review of studies on the selective omission of breast surgery after NAC for breast cancer patients. We summarized the existing predictive models and technologies to predict and diagnose pCR after NAC. Our research indicates that, for nearly half a century, the extent of surgery on both breast and axillary lymph nodes is decreasing, while more precise systematic treatments are increasing. NAC has advanced significantly and its pCR rates have improved, so surgery may be omitted in certain patients. However, accurately predicting pCR after NAC is still a challenge. We also described the design for a randomized clinical trial and the potential problems of omitting surgical treatment after NAC. In summary, the decrease in breast cancer surgery is an unavoidable trend, and more high-quality clinical trials need to be conducted.

Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

There is a need to identify biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether plasma polyamines and other metabolites may identify TNBC patients who are less likely to respond to NACT. Pre-treatment plasma levels of acetylated polyamines were elevated in TNBC patients that had moderate to extensive tumor burden (RCB-II/III) following NACT compared to those that achieved a complete pathological response (pCR/RCB-0) or had minimal residual disease (RCB-I). We further applied artificial intelligence to comprehensive metabolic profiles to identify additional metabolites associated with treatment response. Using a deep learning model (DLM), a metabolite panel consisting of two polyamines as well as nine additional metabolites was developed for improved prediction of RCB-II/III. The DLM has potential clinical value for identifying TNBC patients who are unlikely to respond to NACT and who may benefit from other treatment modalities.

Breast Magnetic Resonance Imaging for Patients With Newly Diagnosed Breast Cancer: A Review

Despite the high sensitivity and widespread use of preoperative magnetic resonance imaging (MRI), the American Cancer Society and the National Comprehensive Cancer Network guidelines do not recommend the routine use of preoperative MRI owing to the conflicting results and lack of clear benefit to the surgical outcome (reoperation and mastectomy) and long-term clinical outcomes (local recurrence and metachronous contralateral breast cancer). Preoperative MRI detects additional cancers that are occult at mammography and ultrasound but increases the rate of mastectomy. Concerns about overdiagnosis and overtreatment of preoperative MRI might be mitigated by adjusting the confounding factors when conducting studies, using the state-of-the-art image-guided biopsy technique, applying the radiologists’ cumulative experiences in interpreting MRI findings, and performing multiple lumpectomies in patients with multicentric cancer. Among the various imaging methods, dynamic contrast-enhanced MRI has the highest accuracy in predicting pathologic complete response after neoadjuvant chemotherapy. Prospective trials aimed at applying the MRI information to the de-escalation of surgical or radiation treatments are underway. In this review, current studies on the clinical outcomes of preoperative breast MRI are updated, and circumstances in which MRI may be useful for surgical planning are discussed.

Changes in kinetic heterogeneity of breast cancer via computer-aided diagnosis on MRI predict the pathological response to neoadjuvant systemic therapy

OBJECTIVE

To evaluate whether the computer-aided diagnosis (CAD)-extracted kinetic heterogeneity of breast cancer on MRI and changes therein during treatment were associated with the pathological response to neoadjuvant systemic therapy (NST).

MATERIALS AND METHODS

Consecutive patients with invasive breast cancer, who underwent NST followed by surgery between 2014 and 2020, were retrospectively evaluated. Using a commercial CAD system, kinetic features (angiovolume, peak enhancement, delayed enhancement profiles, and kinetic heterogeneity) of breast cancer were assessed with pre- and mid-treatment MRI. Multivariate logistic regression was used to identify the associations between CAD-extracted kinetic features and pathological complete response (pCR).

RESULTS

A total of 130 patients (mean age, 55 years) were included, 37 (28.5%) of whom achieved a pCR. When the pre- and mid-treatment MRI data were compared, the pCR group exhibited greater changes in kinetic heterogeneity (86.14 ± 32.05% vs. 8.50 ± 141.01%, p < 0.001) and angiovolume (95.20 ± 14.29% vs. 19.89 ± 320.16%; p < 0.001) than the non-pCR group. Multivariate regression analysis showed that a large change in kinetic heterogeneity (odds ratio (OR) = 1.030, p < 0.001), age (OR = 0.931, p = 0.005), progesterone receptor negativity (OR = 7.831, p = 0.001), and HER2 positivity (OR = 3.455, p = 0.017) were associated with pCR.

CONCLUSIONS

A greater change in the CAD-extracted kinetic heterogeneity of breast cancer between pre- and mid-treatment MRI was associated with a pCR in patients on NST.

KEY POINTS

A greater change in kinetic heterogeneity was associated with a pathological complete response. Computer-aided diagnosis-extracted kinetic heterogeneity might serve as a quantitative biomarker of therapeutic efficacy.

Preoperative Breast Magnetic Resonance Imaging as a Predictor of Response to Neoadjuvant Chemotherapy

Introduction:

The ability to accurately predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer would improve patient selection for specific treatment strategies, would provide important information for patients to aid in the treatment selection process, and could potentially avoid the need for more extensive surgery. The diagnostic performance of magnetic resonance imaging (MRI) in predicting pCR has previously been studied, with mixed results. Magnetic resonance imaging performance may also be influenced by tumour and patient factors.

Methods:

Eighty-seven breast cancer patients who underwent NAC were studied. Pre-NAC and post-NAC MRI findings were compared with pathologic findings postsurgical excision. The impact of patient and tumour characteristics on MRI accuracy was evaluated.

Results:

The mean (SD) age of participants was 48.7 (10.3) years. The rate of pCR based on post-NAC MRI was 19.5% overall (19/87). The sensitivity, specificity, positive predictive value (PPV), negative predictive value, and accuracy in predicting pCR were 52.9%, 77.1%, 36.0%, 87.1%, and 72.4%, respectively. Positive predictive value was the highest in nonluminal versus Luminal A disease (45.0% vs 25.0%, P < .001), with higher rates of false positivity in nonluminal subtypes (P = .002). Tumour grade, T category, and histological subtype were all independent predictors of MRI accuracy regarding post-NAC tumour size.

Conclusion:

Magnetic resonance imaging alone is insufficient to accurately predict pCR in breast cancer patients post-NAC. Magnetic resonance imaging predictions of pCR are more accurate in nonluminal subtypes. Tumour grade, T category, and histological subtype should be considered when evaluating post-NAC tumour sizes.

Visual Evaluation of Ultrafast MRI in the Assessment of Residual Breast Cancer after Neoadjuvant Systemic Therapy: A Preliminary Study Association with Subtype

The purpose of this study was to investigate the diagnostic performance of ultrafast DCE (UF-DCE) MRI after the completion of neoadjuvant systemic therapy (NST) in breast cancer. In this study, MR examinations of 55 post-NST breast cancers were retrospectively analyzed. Residual tumor sizes were measured in the 20th phase of UF-DCE MRI, early and delayed phases of conventional DCE MRI, and high spatial-resolution CE MRI (UF, early, delayed, and HR, respectively). The diagnostic performance for the detection of residual invasive cancer was calculated by ROC analysis. The size difference between MRI and pathological findings was analyzed using the Wilcoxon signed-rank test with the Bonferroni correction. The overall AUC was highest for UF (0.86 and 0.88 for readers 1 and 2, respectively). The difference in imaging and pathological sizes for UF (5.7 ± 8.2 mm) was significantly smaller than those for early, delayed, and HR (p < 0.01). For luminal subtype breast cancer, the size difference was significantly smaller for UF and early than for delayed (p < 0.01). UF-DCE MRI demonstrated higher AUC and specificity for the more accurate detection of residual cancer and the visualization of tumor extent than conventional DCE MRI.

Differences in sensitivity to neoadjuvant chemotherapy among invasive lobular and ductal carcinoma of the breast and implications on surgery-A systematic review and meta-analysis

Meta-analysis of >87,000 patients demonstrates that patients with invasive lobular carcinoma of the breast are far less likely to achieve pCR of the breast or axilla compared to their ductal counterparts, receive less BCS and more frequently return positive margins.

BACKGROUND

Neoadjuvant chemotherapy (NACT) facilitates tumour downstaging, increases breast conserving surgery (BCS) and assesses tumour chemosensitivity. Despite clinicopathological differences in Invasive Ductal Carcinoma (IDC) and Invasive Lobular Carcinoma (ILC), decision making surrounding the use NACT does not take account of histological differences.

AIM

To determine the impact NACT on pathological complete response (pCR), breast conserving surgery (BCS), margin status and axillary pCR in ILC and IDC.

METHODS

A systematic review was performed in accordance with the PRISMA guidelines. Studies reporting outcomes among ILC and IDCs following NACT were identified. Dichotomous variables were pooled as odds ratios (ORs) with 95% confidence intervals_(CI) using the Mantel-Haenszel method. P-values <0.05 were statistically significant.

RESULTS

40 studies including 87,303 (7596 ILC [8.7%]and 79,708 IDC [91.3%]) patients were available for analysis. Mean age at diagnosis was 54.9 vs. 50.9 years for ILC and IDC, respectively. IDCs were significantly more likely to achieve pCR (22.1% v 7.4%, OR: 3.03 [95% CI 2.5-3.68] p < 0.00001), axillary pCR (23.6% vs. 13.4%, OR: 2.01 [95% CI 1.77-2.28] p < 0.00001) and receive BCS (45.7% vs. 33.3%, OR 2.14 [95% CI 1.87-2.45] p < 0.00001) versus ILCs. ILCs were significantly more likely to have positive margins at the time of surgery (36% vs 13.5%, OR 4.84 [95% CI 2.88-8.15] p < 0.00001).

CONCLUSION

This is the largest study comparing the impact of NACT among ILC and IDC with respect to pCR and BCS. ILC has different outcomes to IDC following NACT and incorporate it into treatment decisions and future clinical guidelines.

Diagnostic performance of digital breast tomosynthesis for predicting response to neoadjuvant systemic therapy in breast cancer patients: A comparison with magnetic resonance imaging, ultrasound, and full-field digital mammography

Background

The goals of neoadjuvant systemic therapy (NST) are to reduce tumor volume and to provide a prognostic indicator in assessing treatment response. Digital breast tomosynthesis (DBT) was developed and has increased interest in clinical settings due to its higher sensitivity for breast cancer detection compared to full-field digital mammography (FFDM).

Purpose

To evaluate the accuracy of DBT in assessing response to NST compared to FFDM, ultrasound (US), and magnetic resonance imaging (MRI) in breast cancer patients.

Material and Methods

In this retrospective study, 95 stages II–III breast cancer patients undergoing NST and subsequent surgeries were enrolled. After NST, the longest diameter of residual tumor measured by DBT, FFDM, US, and MRI was compared with pathology. Agreements and correlations of tumor size were assessed, and the diagnostic performance for predicting pathologic complete response (pCR) was evaluated.

Results

Mean residual tumor size after NST was 19.9 mm for DBT, 18.7 mm for FFDM, 16.0 mm for US, and 18.4 mm for MRI, compared with 17.9 mm on pathology. DBT and MRI correlated better with pathology than that of FFDM and US. The ICC values were 0.85, 0.87, 0.74, and 0.77, respectively. Twenty-five patients (26.3%) achieved pCR after NST. For predicting pCR, area under the receiver operating characteristic (ROC) curve for DBT, FFDM, US, and MRI were 0.79, 0.66, 0.68, and 0.77, respectively.

Conclusion

DBT has good correlation with histopathology for measuring residual tumor size after NST. DBT was comparable to MRI in assessing tumor response after completion of NST.

Prediction of pathologic complete response on MRI in patients with breast cancer receiving neoadjuvant chemotherapy according to molecular subtypes

OBJECTIVES

This study aimed to investigate the predictability of breast MRI for pathologic complete response (pCR) by molecular subtype in patients with breast cancer receiving neoadjuvant chemotherapy (NAC) and investigate the MRI findings that can mimic residual malignancy.

METHODS

A total of 506 patients with breast cancer who underwent MRI after NAC and underwent surgery between January and December 2018 were included. Two breast radiologists dichotomized the post-NAC MRI findings as radiologic complete response (rCR) and no-rCR. The diagnostic performance of MRI predicting pCR was evaluated. pCR was determined based on the final pathology reports. Tumors were divided according to hormone receptor (HR) and human epidermal growth factor receptor (HER) 2. Residual lesions on post-NAC MRI were divided into overt and subtle which classified as nodularity or delayed enhancement. Pearson's χ² and Wilcoxon rank-sum tests were used for MRI findings causing false-negative pCR.

RESULTS

The overall pCR rate was 30.04%. The overall accuracy for predicting pCR using MRI was 76.68%. The accuracy was significantly different by subtypes (p < 0.001), as follows in descending order: HR - /HER2 - (85.63%), HR + /HER2 - (82.84%), HR + /HER2 + (69.37%), and HR - /HER2 + (62.38%). MRI in the HR - /HER2 + type showed the highest false-negative rate (18.81%) for predicting pCR. The subtle residual enhancement observed only in the delayed phase was associated with false-negative findings (76.2%, p = 0.016).

CONCLUSIONS

The diagnostic accuracy of MRI for predicting pCR differed by molecular subtypes. When the residual enhancement on MRI after NAC is subtle and seen only in the delayed phase, overinterpretation of residual tumors should be performed with caution.

KEY POINTS

• In patients with breast cancer after completion of neoadjuvant chemotherapy, the diagnostic accuracy of MRI for predicting pathologic complete response (pCR) differed according to molecular subtype. • When residual enhancement on MRI is subtle and seen only in the delayed phase, this finding could be associated with false-negative pCR results.

Role of MRI in predicting response to neo-adjuvant systemic therapy (NAST) in breast cancer

BACKGROUND AND OBJECTIVES

MRI is generally performed to assess response to Neo-adjuvant systemic therapy (NAST) in breast cancer.

OBJECTIVE

To assess role of MRI in determining the probability of having residual disease in patients undergoing NAST. We also evaluated synchronous cancers diagnosed following MRI.

METHODS

This is a retrospective study which included all patients who had pre-and post-NAST MRI between June 2014 and December 2019. Data on demographics, tumour characteristics and pathology were collected and analysed. Pre- and post-MRI probability were calculated and depicted on nomograms.

RESULTS

The study included 205 patients. Overall pre-MRI probability of having residual disease was 55% (OR:1.2). The post-MRI probability was 78% (95% CI 72-83%; OR:3.5) if MRI showed residual disease and 23% (95% CI 16-31%, OR:0.3) if imaging showed complete response. The absolute benefit was higher in TNBC and HR-HER2. Additional cancers were identified in 8.78% of patients.

CONCLUSION

MRI is beneficial in evaluating response to NAST specifically in TNBC and HR-HER2 cancers. Pre- and post-MRI probabilities of residual disease depicted on nomograms are a useful tool for clinicians. MRI can potentially impact the treatment decisions by identification of synchronous cancers.

Computer-aided classification of MRI for pathological complete response to neoadjuvant chemotherapy in breast cancer

Background: To determine suitable optimal classifiers and examine the general applicability of computer-aided classification to compare the differences between a computer-aided system and radiologists in predicting pathological complete response (pCR) from patients with breast cancer receiving neoadjuvant chemotherapy. Methods: We analyzed a total of 455 masses and used the U-Net network and ResNet to execute MRI segmentation and pCR classification. The diagnostic performance of radiologists, the computer-aided system and a combination of radiologists and computer-aided system were compared using receiver operating characteristic curve analysis. Results: The combination of radiologists and computer-aided system had the best performance for predicting pCR with an area under the curve (AUC) value of 0.899, significantly higher than that of radiologists alone (AUC: 0.700) and computer-aided system alone (AUC: 0.835). Conclusion: An automated classification system is feasible to predict the pCR to neoadjuvant chemotherapy in patients with breast cancer and can complement MRI.

Pre-treatment MRI tumor features and post-treatment mammographic findings: may they contribute to refining the prediction of pathologic complete response in post-neoadjuvant breast cancer patients with radiologic complete response on MRI?

PURPOSE

Radiologic complete response (rCR) in breast cancer patients after neoadjuvant chemotherapy (NAC) does not necessarily correlate with pathologic complete response (pCR), a marker traditionally associated with better outcomes. We sought to verify if data extracted from two important steps of the imaging workup (tumor features at pre-treatment MRI and post-treatment mammographic findings) might assist in refining the prediction of pCR in post-NAC patients showing rCR.

METHODS

A total of 115 post-NAC women with rCR on MRI (2010-2016) were retrospectively assessed. Pre-treatment MRI (lesion morphology, size, and distribution) and post-treatment mammographic findings (calcification, asymmetry, mass, architectural distortion) were assessed, as well as clinical and molecular variables. Bivariate and multivariate analyses evaluated correlation between such variables and pCR. Post-NAC mammographic findings and their correlation with ductal in situ carcinoma (DCIS) were evaluated using Pearson's correlation.

RESULTS

Tumor distribution at pre-treatment MRI was the only significant predictive imaging feature on multivariate analysis, with multicentric lesions having lower odds of pCR (p = 0.035). There was no significant association between tumor size and morphology with pCR. Mammographic residual calcifications were associated with DCIS (p = 0.009). The receptor subtype remained as a significant predictor, with HR-HER2 + and triple-negative status demonstrating higher odds of pCR on multivariate analyses.

CONCLUSIONS

Multicentric lesions on pre-NAC MRI were associated with a lower chance of pCR in post-NAC rCR patients. The receptor subtype remained a reliable predictor of pCR. Residual mammographic calcifications correlated with higher odds of malignancy, making the correlation between mammography and MRI essential for surgical planning. Key Points • The presence of a multicentric lesion on pre-NAC MRI, even though the patient reaches a radiologic complete response on MRI, is associated with a lower chance of pCR. • Molecular status of the tumor remained the only significant predictor of pathologic complete response in such patients in the present study. • Post-neoadjuvant residual calcifications found on mammography were related to higher odds of residual malignancy, making the correlation between mammography and MRI essential for surgical planning.

Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.

Accuracy of MRI for prediction of response to neo-adjuvant chemotherapy in triple negative breast cancer compared to other subtypes of breast cancer

Purpose:

The aim of this study was to compare the accuracy of magnetic resonance imaging (MRI) for the prediction of response to neo-adjuvant chemotherapy in triple negative (TN) breast cancer, with respect to other subtypes.

Materials and Methods:

There were a total of 1610 breast cancers diagnosed between March 2009 and August 2014, out of which 82 patients underwent MRI before and after neo-adjuvant chemotherapy but just before surgery. TN cancers were analyzed with respect to others subtypes. Accuracy of MRI for prediction of pathological complete response was compared between different subtypes by obtaining receiver operating characteristic (ROC) curves. The Statistical Package for the Social Sciences version 21 was used for all data analysis, with P value of 0.05 as statistically significant.

Results:

Out of 82 patients, 29 were luminal (HR+/HER2−), 23 were TN (HR−, HER2−), 11 were HER2 positive (HR−, HER2+), and 19 were of hybrid subtype (HR+/HER2+). TN cancers presented as masses on the pre-chemotherapy MRI scan, were grade 3 on histopathology, and showed concentric shrinkage following chemotherapy. TN cancers were more likely to have both imaging and pathological complete response following chemotherapy (P = 0.055) in contrast to luminal cancers, which show residual cancer. ROC curves were constructed for the prediction of pathological complete response with MRI. For the TN subgroup, MR had a sensitivity of 0.745 and specificity of 0.700 (P = 0.035), with an area under curve of 0.745 (95% confidence interval: 0.526–0.965), which was significantly better compared to other subtypes.

Conclusion:

TN breast cancers present as masses and show concentric shrinkage following chemotherapy. MRI is most accurate in predicting response to chemotherapy in the TN group, compared to others subtypes. MRI underestimates residual disease in luminal cancers.

Management of the Axilla and the Breast After Neoadjuvant Chemotherapy in Patients with Breast Cancer: A Systematic Review

Breast cancer is the most common cancer in women worldwide. Breast cancer is traditionally treated with surgery, plus adjuvant systemic therapy and radiotherapy as required. Neoadjuvant chemotherapy (NACT) for the treatment of breast cancer is used for locally advanced operable breast cancer to reduce the tumor size, to perform breast conserving surgery, and to perform a limited axillary approach. Adjuvant chemotherapy for the treatment of inflammatory breast cancer and even in inoperable breast cancer is used to increase overall survival time and to delay disease progression while relieving symptoms. NACT for breast cancer is a new strategy that was introduced toward the end of the 20^th century and is increasingly used in the treatment of breast cancer. At present, NACT is increasingly being used to reduce the need for axillary dissection and to convert patients with large tumors to candidates for breast conservation therapy in both locally advanced and operable breast cancers. Breast conserving procedures are currently more preferred by surgeons and axillary dissection is being replaced by sentinel lymph node biopsy after chemotherapy. One of the targets of neoadjuvant systemic therapy is to try to perform a less aggressive surgery by breast conservation, mainly for cosmetic reasons and avoiding axillary dissection mainly for arm mobility, pain, and lymphedema risk. The other target of neoadjuvant systemic therapy is to see the response of the tumor to chemotherapy and determine the treatment accordingly. Neoadjuvant systemic therapy increases the rate of complete pathological response by clearing the breast and axilla from tumor cells before surgery. In this review, we examine the key points of using the NACT in breast cancer, considering radiological imaging methods, surgical management, and reconstruction after NACT.

Diagnostic Accuracy of MRI in Evaluating Response After Neoadjuvant Systemic Therapy in Operable Breast Cancer

Background

Neoadjuvant chemotherapy (NAC) is an important step in the treatment of various types of breast cancer by downsizing the tumor to make it operable. Determining disease extent after NAC is essential for accurate surgical planning. MRI has been the gold standard for detecting tumors that are usually difficult to detect on ultrasound or mammography. However, the use of MRI after NAC is controversial. Therefore, we aimed to evaluate the diagnostic accuracy of post-NAC MRI in the detection of residual disease preoperatively and to investigate the factors associated with pathological complete response (pCR).

Methodology

This retrospective review study was approved by the institutional review board with waiving of the informed consent. A total of 90 charts between January 2016 and January 2019 were reviewed. Baseline lesion size was measured as the maximal diameter in a single dimension by pretreatment MRI. To assess the diagnostic accuracy of MRI in detecting residual disease, we used two different definitions of pCR in the breast. The first is the resolution of both invasive disease and ductal carcinoma in situ. The second is the resolution of the invasive disease only. As a secondary objective of the study, we assessed the association between different patients’ characteristics and both MRI and pathologic response using univariate and multivariate analysis.

Results

A total of 52 women (mean age: 47.4 years; range: 28-74) with 56 breast masses were eligible for the study. Complete MRI response was noted in 22 (39%) masses. pCR was achieved in 14 (25%) and 25 (44.6%) masses using the first and second pCR definitions, respectively. The negative predictive value (NPV) and overall accuracy of MRI for detecting residual disease were 50% and 75%, respectively, using the first pCR definition. With the second pCR definition, NPV and accuracy were 77.3% and 76.8%, respectively. Positive axillary lymph nodes were the only significant factor associated with incomplete MRI and pathological responses.

Conclusions

MRI NPV for residual disease was higher with the second pCR definition; however, overall accuracy was not different. MRI accuracy in detecting residual disease after NAC is not adequate to replace pathological assessment.

Is pathological complete response predictable after neoadjuvant chemotherapy in breast cancer? A single institution's retrospective experience

BACKGROUND

Pathological complete response (pCR), in breast cancers, after neoadjuvant chemotherapy is linked to improved survival. Determining complete response to chemotherapy prior to surgery has remained elusive even using a combination of pathological factors and imaging modalities, making surgery still a necessity.

METHODS

A retrospective analysis was performed from a single institution from 2013 to 2018. Breast cancer patients treated with neoadjuvant chemotherapy with pre- and post-chemotherapy magnetic resonance imaging (MRI) were included. Patients receiving other neoadjuvant modalities were excluded. Imaging characteristics, including response to chemotherapy and pathological factors, were recorded.

RESULTS

Analysis showed 134 patients were identified with 40/134 (29.9%) noted to have radiological complete response and 34/134 (25.6%) had pCR. The positive predictive value for MRI to detect pCR was greatest for oestrogen receptor (ER) negative and human epidermal growth factor receptor 2 (HER2) negative tumours at 81.8% and worst for ER+ HER2- tumours at 25%. The negative predictive value was greatest for ER+ HER2- tumours at 93.9% and worst for ER- HER2- tumours at 77.4%.

CONCLUSION

MRI after neoadjuvant chemotherapy for breast cancer even combined with tumour factors is not an accurate predictor of pCR.

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 response by MR imaging and ultrasound as predictor of pathologic complete response to 12-week neoadjuvant therapy for different early breast cancer subtypes: Combined analysis from the WSG ADAPT subtrials

We evaluated the role of early response after 3 weeks of neoadjuvant treatment (NAT) assessed by ultrasound (US), magnetic resonance imaging (MRI) and Ki-67 dynamics for prediction of pathologic complete response (pCR) in different early breast cancer subtypes. Patients with HR+/HER2+, HR-/HER2- and HR-/HER2+ tumors enrolled into three neoadjuvant WSG ADAPT subtrials underwent US, MRI and Ki-67 assessment at diagnosis and after 3 weeks of NAT. Early response was defined as complete or partial response (US, MRI) and ≥30% proliferation decrease or <500 invasive tumor cells (Ki-67). Predictive values and area under the receiver operating characteristic (AUC) curves for prediction of pCR (ypT0/is ypN0) after 12-week NAT were calculated. Two hundred twenty-six had MRI and 401 US; 107 underwent both MRI and US. All three methods yielded a similar AUC in HR+/HER2+ (0.66-0.67) and HR-/HER2- tumors (0.53-0.63), while MRI and Ki-67 performed better than US in HR-/HER2+ tumors (0.83 and 0.79 vs 0.56). Adding MRI+/-Ki-67 increased AUC of US in HR-/HER2+ tumors to 0.64 to 0.75. MRI and Ki-67 demonstrated highest sensitivity in HR-/HER2- (0.8-1) and HR-/HER2+ tumors (1, both). Negative predictive value was similar for all methods in HR+/HER2+ (0.71-0.74) and HR-/HER2- tumors (0.85-1), while it was higher for MRI and Ki-67 compared to US in HR-/HER2+ subtype (1 vs 0.5). Early response assessed by US, MRI and Ki-67 is a strong predictor for pCR after 12-week NAT. Strength of pCR prediction varies according to tumor subtype. Adding MRI+/-Ki-67 to US did not improve pCR prediction in majority of our patients.

Kinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study

This study aimed to evaluate the predictions of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for prognosis of triple-negative breast cancer (TNBC), especially with residual disease (RD) after preoperative chemotherapy. This retrospective analysis included 74 TNBC patients who received preoperative chemotherapy. DCE-MRI findings from three timepoints were examined: at diagnosis (MRI_pre), at midpoint (MRI_mid) and after chemotherapy (MRI_post). These findings included cancer lesion size, washout index (WI) as a kinetic parameter using the difference in signal intensity between early and delayed phases, and time-signal intensity curve types. Distant disease-free survival was analysed using the log-rank test to compare RD group with and without a fast-washout curve. The diagnostic performance of DCE-MRI findings, including positive predictive value (PPV) for pathological responses, was also calculated. RD without fast washout curve was a significantly better prognostic factor, both at MRI_mid and MRI_post (hazard ratio = 0.092, 0.098, p < 0.05). PPV for pathological complete remission at MRI_mid was 76.7% by the cut-off point at negative WI value or lesion size = 0, and 66.7% at lesion size = 0. WI and curve types derived from DCE-MRI at the midpoint of preoperative chemotherapy can help not only assess tumour response but also predict prognosis.

Breast MRI for Evaluation of Response to Neoadjuvant Therapy

Neoadjuvant therapy is increasingly being used to treat early-stage triple-negative and human epidermal growth factor 2-overexpressing breast cancers, as well as locally advanced and inflammatory breast cancers. The rationales for neoadjuvant therapy are to shrink tumor size and potentially decrease the extent of surgery, to serve as an in vivo test of response to therapy, and to reveal prognostic information for the patient. MRI is the most accurate modality to demonstrate response to therapy and to help ensure accurate presurgical planning. Changes in lesion diameter, volume, and enhancement are used to predict complete response, partial response, or nonresponse to therapy. However, residual disease may be overestimated or underestimated at MRI. Fibrosis, necrotic tumors, and residual benign masses may be causes of overestimation of residual disease. Nonmass lesions, invasive lobular carcinoma, hormone receptor-positive tumors, nonconcentric shrinkage patterns, the use of antiangiogenic therapy, and late-enhancing foci may be causes of underestimation of residual disease. In patients with known axillary lymph node metastasis, neoadjuvant therapy may be followed by targeted axillary dissection to avoid the potential morbidity associated with an axillary lymph node dissection. Diffusion-weighted imaging, radiomics, machine learning, and deep learning methods are under investigation to improve MRI accuracy in predicting treatment response.^©RSNA, 2021.

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.

Value of ultrafast and standard dynamic contrast-enhanced magnetic resonance imaging in the evaluation of the presence and extension of residual disease after neoadjuvant chemotherapy in breast cancer

PURPOSE

To evaluate the diagnostic performance of ultrafast and standard dynamic contrast-enhanced (DCE)-MRI in evaluating the residual disease after neoadjuvant chemotherapy (NAC) for breast cancer.

MATERIALS AND METHODS

Sixty-seven consecutive patients underwent MRI after NAC. Visual analysis of enhancement was performed on ultrafast and standard DCE-MRI, and compared between no residual disease and residual disease groups. The lesion diameters measured on the last phase of ultrafast DCE-MRI and early and delayed phases of standard DCE-MRI were compared with pathological diameter of entire residual cancer and residual invasive ductal carcinoma (IDC).

RESULTS

The visual analysis in the delayed phase of standard DCE-MRI exhibited the highest sensitivity (90%), whereas ultrafast DCE-MRI revealed the highest positive predictive value (92%). There were no significant differences between the diameters in the delayed phase of the standard DCE-MRI and the pathological entire residual cancer (p = 0.97), and the diameters in ultrafast DCE-MRI and the pathological residual IDC (p = 0.97).

CONCLUSION

The delayed phase of standard DCE-MRI may be effective for detecting the residual disease and evaluating the extension of entire residual cancer. Enhancement in ultrafast DCE-MRI may be strongly suggestive of the presence of residual disease, and effective for evaluating the extension of residual IDC.

Margin Assessment and Re-excision Rates for Patients Who Have Neoadjuvant Chemotherapy and Breast-Conserving Surgery

BACKGROUND

Neoadjuvant chemotherapy (NAC) has enabled more patients to be eligible for breast-conservation surgery (BCS). Achieving negative lumpectomy margins, however, is challenging due to changes in tissue composition and potentially scattered residual carcinoma in the tumor bed. Data regarding BCS after NAC have shown variable re-excision rates. MarginProbe (Dilon Technologies, Newport News, VA, USA) has been shown to identify positive resection margins intraoperatively and to reduce the number of re-excisions in primary BCS, but has not been studied in NAC+BCS cases. This study aimed to investigate the clinicopathologic characteristics, margin status, and re-excision rates for NAC+BCS patients with and without the use of MarginProbe.

METHODS

The Institutional Breast Cancer Database was queried for patients who received NAC and had BCS from 2010 to 2019. The variables of interest were demographics, tumor characteristics, pathologic complete response (pCR), MarginProbe use, and re-excision rates.

RESULTS

The study population consisted of 214 patients who had NAC, 61 (28.5 %) of whom had NAC+BCS. The median age of the patients was 53.5 years. A pCR was achieved for 19 of the patients (31.1 %). Of the remaining 42 patients, 9 (21 %) had close or positive margins that required re-excision. Re-excision was associated with a larger residual tumor size (p = 0.025) and estrogen receptor (ER)-positive disease before NAC (p = 0.041). MarginProbe use was associated with a lower re-excision rate for the patients who had NAC+BCS (6 % vs. 31 %, respectively).

CONCLUSION

The patients with a larger residual tumor burden and ER-positive disease had a greater risk for inadequate margins at surgery. MarginProbe use was associated with a lower re-excision rate. Techniques to reduce the need for re-excision will support the use of BCS after NAC.

Criteria for identifying residual tumours after neoadjuvant chemotherapy of breast cancers: a magnetic resonance imaging study

We investigated magnetic resonance imaging (MRI) criteria identifying residual tumours in patients with triple-negative and human epidermal growth factor receptor type 2-positive (HER2+) breast cancer following neoadjuvant chemotherapy. Retrospectively, 290 patients were included who had undergone neoadjuvant chemotherapy and definitive surgery. Clinicopathological features, as well as lesion size and lesion-to-background parenchymal signal enhancement ratio (SER) in early- and late-phase MRIs, were analysed. Receiver operating characteristic (ROC) analyses evaluated diagnostic performances. Maximal MRI values showing over 90% sensitivity and negative predictive value (NPV) were set as cut-off points. Identified MRI criteria were prospectively applied to 13 patients with hormone receptor-negative (HR-) tumours. The lesion size in HR-HER2-tumours had the highest area under the ROC curve value (0.92), whereas this parameter in HR + HER2 + tumours was generally low (≤ 0.75). For HR-tumours, both sensitivity and NPV exceeded the 90% threshold for early size > 0.2 cm (HR-HER2-) or > 0.1 cm (HR-HER2 +), late size > 0.4 cm, and early SER > 1.3. In the prospective pilot cohort, the criteria size and early SER did not find false negative cases, but one case was false negative with late SER. Distinguishing residual tumours based on MRI is feasible in selected triple-negative and HER2 + breast cancer patients.

Evaluation of Post-Neoadjuvant Chemotherapy Pathologic Complete Response and Residual Tumor Size of Breast Cancer: Analysis on Accuracy of MRI and Affecting Factors

목적

신보강화학요법을 시행한 유방암 환자에서 병리학적 관해와 잔류 암의 크기를 평가하는 데 있어 유방자기공명영상의 정확도를 분석하고 이에 영향을 미치는 인자들이 무엇인지 알아본다.

대상과 방법

2010년부터 2017년까지 본원에서 신보강화학요법 후 수술을 시행한 88명의 유방암 환자를 대상으로 하였다. 병리학적 관해는 수술 병리 결과에서 침윤성 유방암이 발견되지 않는 것으로 정의하였고 자기공명영상과 병리 조직의 잔류 암 크기 차이는 최대 직경으로 비교하였다. 병리학적 관해 및 자기공명영상과 병리 조직에서의 잔류 암 크기 차이에 영향을 미치는 인자를 알아보기 위해 통계분석을 시행하였다.

결과

전체 환자의 10%가 병리학적 관해에 도달하였다. 자기공명영상으로 관해를 예측할 때의 정확도와 곡선하부면적은 각각 90.91%, 0.8017이었다. 신보강화학요법 시행 후 유방자기공명영상과 병리 조직에서 측정한 잔류 암의 크기는 매우 강한 연관성을 보였고(r = 0.9, p < 0.001), 특히 영상에서 단일 종괴로 보였던 병변에서(p = 0.047) 그러하였다. 자기공명영상과 병리 조직 간의 잔류 암 크기는 내강형(p = 0.023), 그리고 자기공명영상에서 다초점 종괴 및 비종괴성 조영증강을 보인(p = 0.047) 환자군에서 유의미하게 큰 차이를 보였다.

결론

자기공명영상은 유방암의 병리학적 완전 관해와 잔류 암 크기의 평가에 있어서 정확도가 높은 검사이다. 유방암 아형과 병변의 영상의학적 소견이 자기공명영상의 정확도에 영향을 미친다.

The role of breast MRI in newly diagnosed breast cancer: An evidence-based review

The utility of pre-operative MRI in patients with newly diagnosed invasive breast cancer remains a topic of debate. Those who advocate for pre-treatment imaging contend that MRI may detect additional disease not otherwise appreciated on conventional imaging and may provide more accurate staging information to guide treatment. Additionally, it has been proposed that MRI can be utilized to assess extent of residual disease in patients undergoing neoadjuvant chemotherapy. Conversely, those in opposition maintain that routine pre-operative MRI subjects patients to unnecessary ipsilateral mastectomies and prophylactic contralateral mastectomies with no difference in oncologic outcome. When stratified based on tumor biology and patient characteristics, the data suggests that pre-treatment MRI may be advantageous in certain subsets when compared to the general cohort of breast cancer patients. This review recapitulates the current literature on the impact of breast MRI on the surgical management and outcomes of newly diagnosed breast cancer.

Assessing the accuracy of conventional gadolinium-enhanced breast MRI in measuring the nodal response to neoadjuvant chemotherapy (NAC) in breast cancer

Management of the axilla in the era of neoadjuvant chemotherapy for breast cancer is evolving. The aim of this study is to determine if conventional gadolinium-enhanced breast MRI can aid in evaluation of the response to neoadjuvant chemotherapy in the axilla. A retrospective review of a prospectively maintained database of patients undergoing neoadjuvant chemotherapy for breast cancer was performed. Pre and post-neoadjuvant chemotherapy MRI reports for node-positive patients were examined in conjunction with demographic data, treatment type, and final histopathology reports. One-hundred and fourteen patients with breast cancer undergoing neoadjuvant chemotherapy were included in the study. The sensitivity of magnetic resonance imaging in detecting nodal response post-neoadjuvant chemotherapy was 33.93% and the specificity was 82.76%. Magnetic resonance imaging had a positive predictive value of 65.52% and a negative predictive value of 56.47%. MRI was found to be most specific in the detection of triple-negative cancer response. Specificity was 100% in this group and sensitivity was 75%. Magnetic resonance imaging has a relatively high specificity in detecting nodal response post-neoadjuvant chemotherapy but has a low sensitivity. Alone it cannot be relied upon to identify active axillary malignancy post-neoadjuvant chemotherapy. However, given its increased specificity among certain subgroups, it may have a role in super-selecting patients suitable for sentinel lymph node biopsy post-neoadjuvant chemotherapy.