Monitoring tumor response to neoadjuvant chemotherapy using MRI and 18F-FDG PET/CT in breast cancer subtypes

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.

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.

Clinical utility of MRI in the neoadjuvant management of early-stage breast cancer

BACKGROUND

With the increasing use of neoadjuvant treatment (NAT) for patients with early-stage breast cancer (ESBC), adequate clinical staging is essential to inform treatment. While the use of MRI with NAT has been proposed to help with accuracy of pre-treatment clinical staging, its impact in clinical practice remains controversial.

METHODS

A prospective institutional database of patients with ESBC treated with NAT between May 2012 and December 2020 was analyzed in order to compare the management of patients who received an MRI prior to NAT to those who did not. The indications for MRI and correlation of MRI findings to conventional breast imaging were evaluated. The impact of MRI on management was compared between the MRI and non-MRI groups.

RESULTS

A total of 530 patients met inclusion criteria. Of these, 186 (35.1%) had an MRI and 344 (64.9%) did not. The most frequent indication for MRI was the determination of disease extent (54.5%). Patients who had an MRI prior to neoadjuvant treatment were significantly more likely to be younger (47 years versus 57 years; p < 0.001) and have multifocal disease (32.3% versus 22.1%; p < 0.05). When compared to conventional imaging, MRI reported a greater extent of disease in the breast (37.6%), more nodal involvement (18.8%), and multifocal disease (15.1%). Additional diagnostic interventions were advised in 52.2% of patients who underwent MRI. Rates of mastectomies were greater in the MRI group (80.0% versus 58.9%; p < 0.05) in addition to more axillary dissections (28.0% versus 17.4%; p < 0.01). Rates of locoregional recurrences were low in both groups, with similar disease-free survival outcomes at 5 years.

CONCLUSION

MRI identified significantly more disease in contrast to conventional imaging and lead to more aggressive surgical management. Prospective studies evaluating the role of MRI before NAT and its impact on long-term outcomes are needed.

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.

3T DCE-MRI Radiomics Improves Predictive Models of Complete Response to Neoadjuvant Chemotherapy in Breast Cancer

OBJECTIVES

To test whether 3T MRI radiomics of breast malignant lesions improves the performance of predictive models of complete response to neoadjuvant chemotherapy when added to other clinical, histological and radiological information.

METHODS

Women who consecutively had pre-neoadjuvant chemotherapy (NAC) 3T DCE-MRI between January 2016 and October 2019 were retrospectively included in the study. 18F-FDG PET-CT and histological information obtained through lesion biopsy were also available. All patients underwent surgery and specimens were analyzed. Subjects were divided between complete responders (Pinder class 1i or 1ii) and non-complete responders to NAC. Geometric, first order or textural (higher order) radiomic features were extracted from pre-NAC MRI and feature reduction was performed. Five radiomic features were added to other available information to build predictive models of complete response to NAC using three different classifiers (logistic regression, support vector machines regression and random forest) and exploring the whole set of possible feature selections.

RESULTS

The study population consisted of 20 complete responders and 40 non-complete responders. Models including MRI radiomic features consistently showed better performance compared to combinations of other clinical, histological and radiological information. The AUC (ROC analysis) of predictors that did not include radiomic features reached up to 0.89, while all three classifiers gave AUC higher than 0.90 with the inclusion of radiomic information (range: 0.91-0.98).

CONCLUSIONS

Radiomic features extracted from 3T DCE-MRI consistently improved predictive models of complete response to neo-adjuvant chemotherapy. However, further investigation is necessary before this information can be used for clinical decision making.

Evaluation of Early Response to Preoperative Accelerated Partial Breast Irradiation (PAPBI) by Histopathology, Magnetic Resonance Imaging, and 18F-fluorodexoyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT)

PURPOSE

This study aimed to find indicators for early response to radiation therapy in breast cancer. These would be of help in tailoring treatment for individual patients.

METHODS AND MATERIALS

We analyzed 66 patients with low-risk breast cancer (≥60 years; cT1-2pN0) treated within the Preoperative Accelerated Partial Breast Irradiation (PAPBI) trial. Patients received radiation therapy (RT; 10 x 4 Gray or 5 x 6 Gray), followed by a wide local excision after 6 weeks. Patients underwent magnetic resonance imaging (MRI) and 18F-fluorodexoyglucose (FDG) positron emission tomography/computed tomography (PET/CT) before RT and 5 weeks after RT, before surgery. We assessed the response to PAPBI using a histopathologic assessment and correlated this with responses on MRI and FDG PET/CT. We calculated the positive predictive values (PPVs) of MRI and PET/CT as the number of true positives (complete response on MRI/normalized at visual evaluation on PET/CT and pathologic complete response) divided by the number of patients with a complete response on MRI/normalized at visual evaluation on PET/CT. Similarly, the negative predictive values (NPVs) of MRI and PET/CT were calculated.

RESULTS

The pathologic response was (nearly) complete in 15 (23%) of the 66 patients and partially complete in 28 (42%). The remaining 23 patients (35%) were nonresponders. The PPV of MRI (Response evaluation criteria in solid tumors [RECIST]) was 87.5% and the NPV was 85%. The PPV and NPV of PET/CT were 25% and 92%, respectively.

CONCLUSIONS

The most accurate method to predict a response and residual disease after preoperative RT in low-risk breast cancer was MRI, using RECIST.

Quantitative ultrasound radiomics for therapy response monitoring in patients with locally advanced breast cancer: Multi-institutional study results

BACKGROUND

Neoadjuvant chemotherapy (NAC) is the standard of care for patients with locally advanced breast cancer (LABC). The study was conducted to investigate the utility of quantitative ultrasound (QUS) carried out during NAC to predict the final tumour response in a multi-institutional setting.

METHODS

Fifty-nine patients with LABC were enrolled from three institutions in North America (Sunnybrook Health Sciences Centre (Toronto, Canada), MD Anderson Cancer Centre (Texas, USA), and Princess Margaret Cancer Centre (Toronto, Canada)). QUS data were collected before starting NAC and subsequently at weeks 1 and 4 during chemotherapy. Spectral tumour parametric maps were generated, and textural features determined using grey-level co-occurrence matrices. Patients were divided into two groups based on their pathological outcomes following surgery: responders and non-responders. Machine learning algorithms using Fisher's linear discriminant (FLD), K-nearest neighbour (K-NN), and support vector machine (SVM-RBF) were used to generate response classification models.

RESULTS

Thirty-six patients were classified as responders and twenty-three as non-responders. Among all the models, SVM-RBF had the highest accuracy of 81% at both weeks 1 and week 4 with area under curve (AUC) values of 0.87 each. The inclusion of week 1 and 4 features led to an improvement of the classifier models, with the accuracy and AUC from baseline features only being 76% and 0.68, respectively.

CONCLUSION

QUS data obtained during NAC reflect the ongoing treatment-related changes during chemotherapy and can lead to better classifier performances in predicting the ultimate pathologic response to treatment compared to baseline features alone.

18F-FDG PET/CT radiomic predictors of pathologic complete response (pCR) to neoadjuvant chemotherapy in breast cancer patients

PURPOSE

Pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) is commonly accepted as the gold standard to assess outcome after NAC in breast cancer patients. ¹⁸F-Fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) has unique value in tumor staging, predicting prognosis, and evaluating treatment response. Our aim was to determine if we could identify radiomic predictors from PET/CT in breast cancer patient therapeutic efficacy prior to NAC.

METHODS

This retrospective study included 100 breast cancer patients who received NAC; there were 2210 PET/CT radiomic features extracted. Unsupervised and supervised machine learning models were used to identify the prognostic radiomic predictors through the following: (1) selection of the significant (p < 0.05) imaging features from consensus clustering and the Wilcoxon signed-rank test; (2) selection of the most discriminative features via univariate random forest (Uni-RF) and the Pearson correlation matrix (PCM); and (3) determination of the most predictive features from a traversal feature selection (TFS) based on a multivariate random forest (RF). The prediction model was constructed with RF and then validated with 10-fold cross-validation for 30 times and then independently validated. The performance of the radiomic predictors was measured in terms of area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

The PET/CT radiomic predictors achieved a prediction accuracy of 0.857 (AUC = 0.844) on the training split set and 0.767 (AUC = 0.722) on the independent validation set. When age was incorporated, the accuracy for the split set increased to 0.857 (AUC = 0.958) and 0.8 (AUC = 0.73) for the independent validation set and both outperformed the clinical prediction model. We also found a close association between the radiomic features, receptor expression, and tumor T stage.

CONCLUSION

Radiomic predictors from pre-treatment PET/CT scans when combined with patient age were able to predict pCR after NAC. We suggest that these data will be valuable for patient management.

MRI Performance in Detecting pCR After Neoadjuvant Chemotherapy by Molecular Subtype of Breast Cancer

BACKGROUND

MRI performance in detecting pathologic complete response (pCR) post-neoadjuvant chemotherapy (NAC) in breast cancer has been previously explored. However, since tumor response varies by molecular subtype, it is plausible that imaging performance also varies. Therefore, we performed a literature review on subtype-specific MRI performance in detecting pCR post-NAC.

METHODS

Two reviewers searched Cochrane, PubMed, and EMBASE for articles published between 2013 and 2018 that examined MRI performance in detecting pCR post-NAC. After filtering, ten primary research articles were included. Statistical metrics, such as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were extracted per study for triple negative, HR+/HER2-, and HER2+ patients.

RESULTS

Ten studies involving 2310 patients were included. In triple negative breast cancer, MRI showed NPV (58-100%) and PPV (72.7-94.7%) across 446 patients and sensitivity (45.5-100%) and specificity (49-94.4%) in 375 patients. In HR+/HER2- breast cancer patients, MRI showed NPV (29.4-100%) and PPV (21.4-95.1%) across 851 patients and sensitivity (43-100%) and specificity (45-93%) across 780 patients. In HER2+-enriched subtype, MRI showed NPV (62-94.6%) and PPV (34.9-72%) in 243 patients and sensitivity (36.2-83%) and specificity (47-90%) in 255 patients.

CONCLUSION

MRI accuracy in detecting pCR post-NAC by subtype is not as consistent, nor as high, as individual studies suggest. Larger studies using standardized pCR definition with appropriate timing of surgery and MRI need to be conducted. This study has shown that MRI is in fact not an accurate prediction of pCR, and thus, clinicians may need to rely on other approaches such as biopsies of the tumor bed.

Understanding indications and defining guidelines for breast magnetic resonance imaging

Magnetic resonance imaging (MRI) of the breast is the most sensitive imaging modality for detecting cancer. With improved scan resolution and correctly applied clinical indications, the specificity of breast MRI has markedly improved in recent years. Current literature indicates an overall sensitivity for breast MRI of 98% - 100% and specificity of 88%. By comparison, the sensitivity and specificity for mammography is in the region of 71% and 98%, respectively. In particular, the very high negative predictive value (NPV) of breast MRI, which approaches 100%, is hugely useful in establishing absence of disease. Furthermore, the ability to accurately delineate viable cancer by way of combining both morphological and functional (contrast enhancement) capabilities means that MRI is the best tool we have in terms of local cancer staging and identifying residual or recurrent disease. The high NPV also means that breast MRI is uniquely capable of ruling out cancer or high-grade ductal carcinoma in situ in appropriate circumstances. I hope that the following guidelines that are based on those of the American College of Radiology and the European Society of Breast Imaging in addition to multiple review articles will provide some assistance to radiologists in terms of the correct indications for breast MRI. There are few formal guidelines in South Africa for the usage of breast MRI. In fact, there is a general paucity of guidelines in the international radiology world. The role of breast MRI in high-risk screening and identification of the primary in occult breast cancer is universally accepted. Thereafter, there is little consensus. By using some general guidelines, and bringing MRI into the discussion of multidisciplinary breast cancer management, good clinical practice and consistent decision-making can be established.

Breast conserving therapy after neoadjuvant chemotherapy; data from the Dutch Breast Cancer Audit

INTRODUCTION

NAC has led to an increase in breast conserving surgery (BCS) worldwide. This study aims to analyse trends in the use of neoadjuvant chemotherapy (NAC) and the impact on surgical outcomes.

METHODS

We reviewed all records of cT1-4N0-3M0 breast cancer patients diagnosed between July 2011 and June 2016 who have been registered in the Dutch National Breast Cancer Audit (NBCA) (N = 57.177). The surgical outcomes of 'BCS after NAC' were compared with 'primary BCS', using a multivariable logistic regression model.

RESULTS

Between 2011 and 2016, the use of NAC increased from 9% to 18% and 'BCS after NAC' (N = 4170) increased from 43% to 57%. We observed an involved invasive margin rate (IMR) of 6,7% and a re-excision rate of 6,6%. As compared to 'primary BCS', the IMR of 'BCS after NAC' is higher for cT1 (12,3% versus 8,3%; p < 0.005), equal for cT2 (14% versus 14%; p = 0.046) and lower for cT3 breast cancer (28,3% versus 31%; p < 0.005). Prognostic factors associated with IMR for both 'primary BCS' as for 'BCS after NAC' are: lobular invasive breast cancer and a hormone receptor positive receptor status (all p < 0,005).

CONCLUSION

The use of NAC and the incidence of 'BCS after NAC' increased exponentially in time for all stages of invasive breast cancer in the Netherlands. This nationwide data confirms that 'BCS after NAC' compared to 'primary BCS' leads to equal surgical outcomes for cT2 and improved surgical outcomes for cT3 breast cancer. These promising results encourage current developments towards de-escalation of surgical treatment.

Image Registration for Microwave Tomography of the Breast Using Priors From Nonsimultaneous Previous Magnetic Resonance Images

Microwave imaging is a low-cost imaging method that has shown promise for breast imaging and, in particular, neoadjuvant chemotherapy monitoring. The early studies of microwave imaging in the therapy monitoring setting are encouraging. For the neoadjuvant therapy application, it would be desirable to achieve the most accurate possible characterization of the tissue properties. One method to achieve increased resolution and specificity in microwave imaging reconstruction is the use of a soft prior regularization. The objective of this study is to develop a method to use magnetic resonance (MR) images, taken in a different imaging configuration, as this soft prior. To enable the use of the MR images as a soft prior, it is necessary to register the MR images to the microwave imaging space. Registration fiducials were placed around the breast that are visible in both the MRI and with an optical scanner integrated into the microwave system. Utilizing these common registration locations, numerical algorithms have been developed to warp the original breast MR images into a geometry closely resembling that in which the breast is pendant in the microwave system.