MRI accuracy in residual disease evaluation in breast cancer patients treated with neoadjuvant chemotherapy

The Role of MRI in Breast Cancer and Breast Conservation Therapy

Contrast-enhanced breast MRI has an established role in aiding in the detection, evaluation, and management of breast cancer. This article discusses MRI sequences, the clinical utility of MRI, and how MRI has been evaluated for use in breast radiotherapy treatment planning. We highlight the contribution of MRI in the decision-making regarding selecting appropriate candidates for breast conservation therapy and review the emerging role of MRI-guided breast radiotherapy.

The Role of MRI in Assessing Residual Breast Cancer After Neoadjuvant Chemotherapy

INTRODUCTION

Breast cancer is the most common malignancy among women in the world. The role of neoadjuvant chemotherapy (NAC) in the management of breast cancer is increasing. The decision about the management after NAC depends mainly on the tumor response to NAC.

OBJECTIVES

The role of the current study is to evaluate the role of the MRI scan in assessing the residual disease after NAC, which would help in decision making regarding the best treatment plan for the patient.

PATIENTS AND METHODS

We did this retrospective review for all patients who were diagnosed with breast cancer in our center and had NAC over four years. All patients in our study had a post-NAC magnetic resonance imaging (MRI) scan to assess the residual tumor size. A 2×2 table was used to calculate the diagnostic accuracy, and SPSS software version 25 was used to get the correlation coefficients between the post-NAC MRI measurements and pathological size.

RESULTS

28 female patients were included in our study. The average age was 45.25 ± 10 years. We utilized the tumor size on histology as the standard for comparison. We calculated MRI sensitivity, specificity, PPV, and NPV rates of 90.9%, 100%, 100%, and 94.4%, respectively. The correlation coefficient was strong (r = 0.859, P = 0.01).

CONCLUSION

Magnetic resonance imaging is a good test to assess the residual tumor disease after NAC in breast cancer patients. However, cases of under- and overestimation are still seen, which require more caution when making a decision regarding the management of such cases.

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.

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.

Staging Breast Cancer with MRI, the T. A Key Role in the Neoadjuvant Setting

Breast cancer (BC) is the most common cancer among women worldwide. Neoadjuvant chemotherapy (NACT) indications have expanded from inoperable locally advanced to early-stage breast cancer. Achieving a pathological complete response (pCR) has been proven to be an excellent prognostic marker leading to better disease-free survival (DFS) and overall survival (OS). Although diagnostic accuracy of MRI has been shown repeatedly to be superior to conventional methods in assessing the extent of breast disease there are still controversies regarding the indication of MRI in this setting. We intended to review the complex literature concerning the tumor size in staging, response and surgical planning in patients with early breast cancer receiving NACT, in order to clarify the role of MRI. Morphological and functional MRI techniques are making headway in the assessment of the tumor size in the staging, residual tumor assessment and prediction of response. Radiomics and radiogenomics MRI applications in the setting of the prediction of response to NACT in breast cancer are continuously increasing. Tailored therapy strategies allow considerations of treatment de-escalation in excellent responders and avoiding or at least postponing breast surgery in selected 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.

Automated breast volume scanner (ABVS) compared to handheld ultrasound (HHUS) and contrast-enhanced magnetic resonance imaging (CE-MRI) in the early assessment of breast cancer during neoadjuvant chemotherapy: an emerging role to monitoring tumor response?

OBJECTIVES

To investigate the role of automated breast volume scanner (ABVS) compared to handheld ultrasound (HHUS) and contrast-enhanced magnetic resonance imaging (CE-MRI) in the early detection of patients with locally advanced breast cancer who are more likely to reach a complete pathological response (pCR) during neoadjuvant chemotherapy (NAC).

METHODS

A single-institution prospective study was performed in patients with histological diagnosis of invasive breast cancer, eligible for NAC, and who were to undergo surgery in our Hospital. Imaging examinations with ABVS, HHUS and CE-MRI were performed at diagnosis (basal time) and after 3 months of chemotherapy (middle time). The tumor size of each lesion was measured at the basal and middle times, and the dimensional variation was reported. Based on this, patients were divided dichotomously by the median value, obtaining "good responders" (goodR) versus "poor responders" (poorR). The results were correlated with the histological assessment (pCR versus No-pCR) with the use of the intergroup comparison of categorical data (Fisher's exact test).

RESULT

A total of 21 patients were included; 5 obtained a pCR (23%). Both the ABVS and the CE-MRI found all 5 patients with pCR in the group of goodR (10 patients), while none of the poorR (11 patients) obtained a pCR [correlation was statistically significant (p 0.01)]. In the HHUS, goodR (10 patients) 1 obtained a pCR while in the poorR (11 patients) 4 obtained a pCR [correlation not statistically significant (p 0.31)].

CONCLUSIONS

ABVS could be a useful tool, appearing to be more reliable than HHUS, and as accurate as CE-MRI, in early detection of patients who could reach a pCR after NAC.

The value of MR-based radiomics in identifying residual disease in patients with carcinoma in situ after cervical conization

Carcinoma in situ (CIS) of the uterine cervix is a precursor to cervical carcinoma. However, hysterectomy can be avoided in patients who can be treated by cone biopsy. Previous studies have shown that imaging-based approaches allow for the noninvasive visualization of cervical cancer, and radiomics has high accuracy in classifying cancer and predicting treatment outcome for different cancer types. To develop a magnetic resonance (MR)-based radiomics model for identifying residual disease in patients with CIS after cervical conization. Patients who had CIS after conization and finally underwent hysterectomy were collected to comprise a database to establish an imaging model for predicting the residual status after conization. Then, patients who opted for uterine preservation were classified as high-risk or low-risk patients according to the model. The disease-free survival was compared between the different risk groups using the Kaplan–Meier curve. The model built with the Boruta features outperformed the random forest model. Further validation with patients with uterine preservation showed that the patients classified as high risk were more likely to have tumor recurrence/residual disease in the follow-up period. In conclusion, radiomics can be used to identify residual disease in patients with CIS after cervical conization and could have the potential to predict recurrence in patients who opt for uterine preservation.

Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends

Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.

Early assessment with magnetic resonance imaging for prediction of pathologic response to neoadjuvant chemotherapy in triple-negative breast cancer: Results from the phase III BrighTNess trial

INTRODUCTION

The ability of breast magnetic resonance imaging (MRI) to predict pathologic complete response (pCR) to neoadjuvant systemic therapy (NST) varies across biological subtypes. We sought to determine how well breast MRI findings following initial treatment on the phase III BrighTNess trial correlated with pCR in patients with triple negative breast cancer (TNBC).

METHODS

Baseline and mid-treatment imaging and pathologic response data were available in 519 patients with stage II-III TNBC who underwent NST as per protocol. MRI complete response (mCR) was defined as disappearance of all target lesion(s) and MRI partial response (mPR) as a ≥50% reduction in the largest tumor diameter.

RESULTS

Overall, mCR was demonstrated in 116 patients (22%), whereas 166 (32%) had mPR and 237 (46%) had stable/progressive disease (SD/PD). The positive predictive value (PPV), negative predictive value, and overall accuracy of the mid-treatment MRI for pCR were 78%, 56%, and 61%, respectively; accuracy did not differ significantly between gBRCA mutation carriers and non-carriers (52% vs. 63%, p = 0.10). When compared to patients with SD/PD, those with mPR or mCR were 3.35-fold (95% CI 2.07-5.41) more likely to have pCR at surgery. MRI response during NST was significantly associated with eligibility for breast-conserving surgery following completion of treatment (93.1% for mCR vs. 81.6% for SD/PD, p < 0.001).

CONCLUSIONS

Complete response on mid-treatment MRI in the BrighTNess trial had a PPV of 78% for demonstration of pCR after completion of NST in TNBC. However, a substantial proportion of patients with mPR or SD/PD also achieved a pCR.

CLINICAL TRIAL REGISTRATION

NCT02032277.

Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography

Strain elastography was used to monitor response to neoadjuvant chemotherapy (NAC) in 92 patients with biopsy-proven, locally advanced breast cancer. Strain elastography data were collected before, during, and after NAC. Relative changes in tumor strain ratio (SR) were calculated over time, and responder status was classified according to tumor size changes. Statistical analyses determined the significance of changes in SR over time and between response groups. Machine learning techniques, such as a naïve Bayes classifier, were used to evaluate the performance of the SR as a marker for Miller-Payne pathological endpoints. With pathological complete response (pCR) as an endpoint, a significant difference (P < .01) in the SR was observed between response groups as early as 2 weeks into NAC. Naïve Bayes classifiers predicted pCR with a sensitivity of 84%, specificity of 85%, and area under the curve of 81% at the preoperative scan. This study demonstrates that strain elastography may be predictive of NAC response in locally advanced breast cancer as early as 2 weeks into treatment, with high sensitivity and specificity, granting it the potential to be used for active monitoring of tumor response to chemotherapy.

Attributes, Performance, and Gaps in Current & Emerging Breast Cancer Screening Technologies

Background:

Early detection of breast cancer, combined with effective treatment, can reduce mortality. Millions of women are diagnosed with breast cancer and many die every year globally. Numerous early detection screening tests have been employed. A wide range of current breast cancer screening methods are reviewed based on a series of searchers focused on clinical testing and performance. </P><P> Discussion: The key factors evaluated centre around the trade-offs between accuracy (sensitivity and specificity), operator dependence of results, invasiveness, comfort, time required, and cost. All of these factors affect the quality of the screen, access/eligibility, and/or compliance to screening programs by eligible women. This survey article provides an overview of the working principles, benefits, limitations, performance, and cost of current breast cancer detection techniques. It is based on an extensive literature review focusing on published works reporting the main performance, cost, and comfort/compliance metrics considered.

Conclusion:

Due to limitations and drawbacks of existing breast cancer screening methods there is a need for better screening methods. Emerging, non-invasive methods offer promise to mitigate the issues particularly around comfort/pain and radiation dose, which would improve compliance and enable all ages to be screened regularly. However, these methods must still undergo significant validation testing to prove they can provide realistic screening alternatives to the current accepted standards.

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

BACKGROUND

Magnetic resonance imaging (MRI) or ultrasonography (US) alone is limited in the ability to predict the pathologic complete response (pCR) accurately after neoadjuvant chemotherapy (NAC). The aim of the present study was to predict the pCR using MRI combined with second-look US in primary breast cancer patients.

MATERIALS AND METHODS

A total of 1274 consecutive primary breast cancer patients who were examined by MRI and second-look US before and after NAC and had undergone breast-conserving surgery from 2004 to 2014 were included. The positive predictive value (PPV) of a clinical complete response (cCR) by MRI alone and MRI plus US was assessed. A CR was defined as no residual invasive carcinoma. The presence of a residual in situ component was also assessed (ypTis).

RESULTS

Of the 1274 patients, 333 (26.1%) had a pCR (ypT0/is), and 102 (8.0%) had a residual in situ component (ypTis). A cCR was found in 247 patients (19.4%) using MRI alone and in 182 patients (14.3%) using MRI plus US. The PPV for a cCR using MRI alone was 79.4% and the PPV for MRI plus US was 86.8%. The PPV for a cCR by MRI plus US was the greatest at 98.1% in the estrogen receptor-negative (ER^-)/human epidermal growth factor receptor-positive (HER2⁺) group (86.5% in the ER⁺/HER2⁺, 83.0% in the ER^-/HER2^-, and 64.7% in the ER⁺/HER2^- groups). The PPV for residual in situ component was as low as 72.2%.

CONCLUSION

Our results have shown that MRI combined with second-look US in predicting for a pCR was useful compared with MRI alone, especially for ER^-/HER2⁺. However, it was difficult to predict for the presence of a residual in situ component. Our ongoing prospective multi-institutional study has shown that adding vacuum-assisted biopsy to MRI plus second-look US is warranted to improve the prediction of pCR for omitting breast surgery.

Breast cancer MRI radiomics: An overview of algorithmic features and impact of inter-reader variability in annotating tumors

PURPOSE

To review features used in MRI radiomics of breast cancer and study the inter-reader stability of the features.

METHODS

We implemented 529 algorithmic features that can be extracted from tumor and fibroglandular tissue (FGT) in breast MRIs. The features were identified based on a review of the existing literature with consideration of their usage, prognostic ability, and uniqueness. The set was then extended so that it comprehensively describes breast cancer imaging characteristics. The features were classified into 10 groups based on the type of data used to extract them and the type of calculation being performed. For the assessment of inter-reader variability, four fellowship-trained readers annotated tumors on preoperative dynamic contrast-enhanced MRIs for 50 breast cancer patients. Based on the annotations, an algorithm automatically segmented the image and extracted all features resulting in one set of features for each reader. For a given feature, the inter-reader stability was defined as the intraclass correlation coefficient (ICC) computed using the feature values obtained through all readers for all cases.

RESULTS

The average inter-reader stability for all features was 0.8474 (95% CI: 0.8068-0.8858). The mean inter-reader stability was lower for tumor-based features (0.6348, 95% CI: 0.5391-0.7257) than FGT-based features (0.9984, 95% CI: 0.9970-0.9992). The feature group with the highest inter-reader stability quantifies breast and FGT volume. The feature group with the lowest inter-reader stability quantifies variations in tumor enhancement.

CONCLUSIONS

Breast MRI radiomics features widely vary in terms of their stability in the presence of inter-reader variability. Appropriate measures need to be taken for reducing this variability in tumor-based radiomics.

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

Patients with locally advanced invasive breast cancers are often treated with neoadjuvant chemotherapy prior to definitive surgical intervention. The primary aims of this approach are to: 1) reduce tumor burden thereby permitting breast conservation rather than mastectomy; 2) promptly treat possible metastatic disease, whether or not it is detectable on preoperative staging; and 3) potentially tailor future chemotherapeutic decisions by monitoring in-vivo tumor response. Accurate radiological assessment permits optimal management and planning in this population. However, assessment of tumor size and response to treatment can vary depending on the modality used, the measurement technique (such as single longest diameter, 3-D measurements, or calculated tumor volume), and varied response of different tumor subtypes to neoadjuvant chemotherapy (such as concentric shrinkage or tumor fragmentation). As discussed in further detail, digital mammography, digital breast tomosynthesis, US and MRI represent the key modalities with potential to help guide patient management. 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 include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Role of MR Imaging in Neoadjuvant Therapy Monitoring

Neoadjuvant chemotherapy (NAC) has become an important treatment approach for stage II/III breast cancers to downsize tumor and enable breast-conserving surgery for patients that may otherwise undergo mastectomy. MR imaging has the potential to identify early response or disease progression, enabling potential modification to NAC regimens. Detection of size and morphologic changes is better appreciated with MR imaging than other modalities and is different between molecular subtypes of breast cancer. The combination of DCE-MR imaging and DWI provides the highest sensitivity and specificity. Other new modalities such as FDG PET/MR imaging and molecular breast imaging are still undergoing research.

Approaches and genetic determinants in predicting response to neoadjuvant chemotherapy in locally advanced gastric cancer

Gastric cancer remains a major health burden worldwide. There is near-universal agreement that neoadjuvant chemotherapy (NAC) is a preferred management for locally advanced gastric cancer (LAGC). However, the optimal approach for an individual patient is still not clear and remains controversial, which could be at least partly explained by the lack of predictive tools. The ability to predict chemosensitivity from NAC in routine clinical practice is difficult and is an area of intense investigation, especially in the Precision-Medicine Era. Available consistent evidence suggests that a favorable tumor histopathological response to NAC may be a useful positive prognostic marker in gastric cancer. Hence, it is reasonable to speculate that making the histopathological response from NAC predictable will dramatically facility the NAC and improve patients' outcome. This review provides an overview on the current status of predictive biomarkers for histopathological response from NAC in LAGC, including clinicopathological variables, imaging and molecular testing. Furthermore, limitations and future perspectives are also discussed.

Magnetic resonance imaging tumor regression shrinkage patterns after neoadjuvant chemotherapy in patients with locally advanced breast cancer: Correlation with tumor biological subtypes and pathological response after therapy

The objective of this study is to analyze magnetic resonance imaging shrinkage pattern of tumor regression after neoadjuvant chemotherapy and to evaluate its relationship with biological subtypes and pathological response. We reviewed the magnetic resonance imaging studies of 51 patients with single mass-enhancing lesions (performed at time 0 and at the II and last cycles of neoadjuvant chemotherapy). Tumors were classified as Luminal A, Luminal B, HER2+, and Triple Negative based on biological and immunohistochemical analysis after core needle biopsy. We classified shrinkage pattern, based on tumor regression morphology on magnetic resonance imaging at the II cycle, as concentric, nodular, and mixed. We assigned a numeric score (0: none; 1: low; 2: medium; 3: high) to the enhancement intensity decrease. Pathological response on the surgical specimen was classified as complete (grade 5), partial (grades 4-3), and non-response (grades 1-2) according to Miller and Payne system. Fisher test was used to relate shrinkage pattern with biological subtypes and final pathological response. Seventeen patients achieved complete response, 25 partial response, and 9 non-response. A total of 13 lesions showed nodular pattern, 20 concentric, and 18 mixed. We found an association between concentric pattern and HER2+ (p < 0.001) and mixed pattern and Luminal A lesions (p < 0.001). We observed a statistical significant correlation between concentric pattern and complete response (p < 0.001) and between mixed pattern and non-response (p = 0.005). Enhancement intensity decrease 3 was associated with complete response (p < 0.001). Shrinkage pattern and enhancement intensity decrease may serve as early response indicators after neoadjuvant chemotherapy. Shrinkage pattern correlates with tumor biological subtypes.

Role of Magnetic Resonance Imaging in Detection of Pathologic Complete Remission in Breast Cancer Patients Treated With Neoadjuvant Chemotherapy: A Meta-analysis

Pathologic complete remission after neoadjuvant chemotherapy has a role in guiding the management of breast cancer. The present meta-analysis examined the accuracy of contrast-enhanced magnetic resonance imaging (CE-MRI) and diffusion-weighted magnetic resonance imaging (DW-MRI) in detecting the response to neoadjuvant chemotherapy and compared CE-MRI with ultrasonography, mammography, and positron emission tomography/computed tomography (PET/CT). Medical subject heading terms and related keywords were searched to generate a compilation of eligible studies. The pooled sensitivity, specificity, diagnostic odds ratio, area under summary receiver operating characteristic curve (AUC), and Youden index (Q* index) were used to estimate the diagnostic efficacy of CE-MRI, DW-MRI, ultrasonography, mammography, and PET/CT. A total of 54 studies of CE-MRI and 8 studies of DW-MRI were included. The overall AUC and the Q* index values for CE-MRI and DW-MRI were 0.88 and 0.94 and 0.80 and 0.85, respectively. According to the summary receiver operating characteristic curves, CE-MRI resulted in a higher AUC value and Q* index compared with ultrasonography and mammography but had values similar to those of DW-MRI and PET/CT. CE-MRI accurately assessed pathologic complete remission in specificity, and PET/CT and DW-MRI accurately assessed pathologic complete remission in sensitivity. The present meta-analysis indicates that CE-MRI has high specificity and DW-MRI has high sensitivity in predicting pathologic complete remission after neoadjuvant chemotherapy. CE-MRI is more accurate than ultrasonography or mammography. Additionally, PET/CT is valuable for predicting pathologic complete remission. CE-MRI, combined with PET/CT or DW-MRI, might allow for a more precise assessment of pathologic complete remission.

Ability of contrast-enhanced ultrasonography to determine clinical responses of breast cancer to neoadjuvant chemotherapy

OBJECTIVE

We aimed to determine whether contrast-enhanced ultrasonography can predict the effects of neoadjuvant chemotherapy on breast cancer.

METHODS

The clinical responses of 63 consecutive patients with breast cancer (T1-4, N0-1, M0) to neoadjuvant chemotherapy between October 2012 and May 2015 were assessed using contrast-enhanced magnetic resonance imaging, positron emission tomography/computed tomography and contrast-enhanced ultrasonography. Perfusion parameters for contrast-enhanced ultrasonography were created from time-intensity curves based on enhancement intensity and temporal changes to objectively evaluate contrast-enhanced ultrasonography findings. The sensitivity, specificity and accuracy of contrast-enhanced ultrasonography, magnetic resonance imaging and positron emission tomography/computed tomography to predict a pathological complete response were compared after confirming the pathological findings of surgical specimens.

RESULTS

Twenty-three (36.5%) of the 63 patients achieved pathological complete response. The sensitivity, specificity and accuracy of contrast-enhanced ultrasonography for predicting pathological complete response were 95.7% (82.5-99.2%), 77.5% (69.9-79.5%) and 84.1% (74.5-86.7%). The sensitivity of contrast-enhanced ultrasonography was significantly greater than that of magnetic resonance imaging (95.7 vs. 69.6%, P = 0.047). The specificity and accuracy were significantly greater and tended to be greater, respectively, for contrast-enhanced ultrasonography than positron emission tomography/computed tomography (specificity, 77.5 vs. 52.5%, P = 0.02; accuracy, 84.1 vs. 69.8%, P = 0.057).

CONCLUSIONS

Contrast-enhanced ultrasonography might serve as a new diagnostic modality when planning therapeutic strategies for patients with breast cancer after neoadjuvant chemotherapy.

Response to neoadjuvant treatment of invasive ductal breast carcinomas including outcome evaluation: MRI analysis by an automatic CAD system in comparison to visual evaluation

BACKGROUND

The aim of this study was to evaluate imaging-based response to standardized neoadjuvant chemotherapy (NACT) regimen by dynamic contrast-enhanced magnetic resonance mammography (DCE-MRM), whereas MR images were analyzed by an automatic computer-assisted diagnosis (CAD) system in comparison to visual evaluation. MRI findings were correlated with histopathologic response to NACT and also with the occurrence of metastases in a follow-up analysis.

PATIENTS AND METHODS

Fifty-four patients with invasive ductal breast carcinomas received two identical MRI examinations (before and after NACT; 1.5T, contrast medium gadoteric acid). Pre-therapeutic images were compared with post-therapeutic examinations by CAD and two blinded human observers, considering morphologic and dynamic MRI parameters as well as tumor size measurements. Imaging-assessed response to NACT was compared with histopathologically verified response. All clinical, histopathologic, and DCE-MRM parameters were correlated with the occurrence of distant metastases.

RESULTS

Initial and post-initial dynamic parameters significantly changed between pre- and post-therapeutic DCE-MRM. Visually evaluated DCE-MRM revealed sensitivity of 85.7%, specificity of 91.7%, and diagnostic accuracy of 87.0% in evaluating the response to NACT compared to histopathology. CAD analysis led to more false-negative findings (37.0%) compared to visual evaluation (11.1%), resulting in sensitivity of 52.4%, specificity of 100.0%, and diagnostic accuracy of 63.0%. The following dynamic MRI parameters showed significant associations to occurring metastases: Post-initial curve type before NACT (entire lesions, calculated by CAD) and post-initial curve type of the most enhancing tumor parts after NACT (calculated by CAD and manually).

CONCLUSIONS

In the accurate evaluation of response to neoadjuvant treatment, CAD systems can provide useful additional information due to the high specificity; however, they cannot replace visual imaging evaluation. Besides traditional prognostic factors, contrast medium-induced dynamic MRI parameters reveal significant associations to patient outcome, i.e. occurrence of distant metastases.

Effect of breast cancer phenotype on diagnostic performance of MRI in the prediction to response to neoadjuvant treatment

AIM

The estimation of response to neoadjuvant chemotherapy (NAC) is useful in the surgical decision in breast cancer. We addressed the diagnostic reliability of conventional MRI, of diffusion weighted imaging (DWI) and of a merged criterion coupling morphological MRI and DWI. Diagnostic performance was analysed separately in different tumor subtypes, including HER2+ (human epidermal growth factor receptor 2)/HR+ (hormone receptor) (hybrid phenotype).

MATERIALS AND METHODS

Two-hundred and twenty-five patients underwent MRI before and after NAC. The response to treatment was defined according to the RECIST classification and the evaluation of DWI with apparent diffusion coefficient (ADC). The complete pathological response - pCR was assessed (Mandard classification).

RESULTS

Tumor phenotypes were Luminal (63.6%), Triple Negative (16.4%), HER2+ (7.6%) or Hybrid (12.4%). After NAC, pCR was observed in 17.3% of cases. Average ADC was statistically higher after NAC (p<0.001) among patients showing pCR vs. those who had not pCR. The RECIST classification showed adequate performance in predicting the pCR in Triple Negative (area under the receiver operating characteristic curve, ROC AUC=0.9) and in the HER2+ subgroup (AUC=0.826). Lower performance was found in the Luminal and Hybrid subgroups (AUC 0.693 and 0.611, respectively), where the ADC criterion yielded an improved performance (AUC=0.787 and 0.722). The coupling of morphological and DWI criteria yielded maximally improved performance in the Luminal and Hybrid subgroups (AUC=0.797 and 0.761).

CONCLUSION

The diagnostic reliability of MRI in predicting the pCR to NAC depends on the tumor phenotype, particularly in the Luminal and Hybrid subgroups. In these cases, the coupling of morphological MRI evaluation and DWI assessment may facilitate the diagnosis.

Research and progress in magnetic resonance imaging of triple-negative breast cancer

Triple-negative breast cancer (TNBC), which characterized by distinct biological and clinical pathological features, has a worse prognosis because the lack of effective therapeutic targets. Breast MR is the most accurate imaging modality for diagnosis of breast cancer currently. MR imaging recognition could assist in diagnosis, pretreatment planning and prognosis evaluation of TNBC. MR findings of a larger solitary lesion, mass with smooth mass margin, high signal intensity on T2-weighted images and rim enhancement are typical MRI features associated with TNBC. Further work is necessary about the clinical application of dynamic contrast-enhanced MR imaging (DCE-MRI), DWI and MRS.

Meta-analysis of agreement between MRI and pathologic breast tumour size after neoadjuvant chemotherapy

BACKGROUND

Magnetic resonance imaging (MRI) has been proposed to guide breast cancer surgery by measuring residual tumour after neoadjuvant chemotherapy. This study-level meta-analysis examines MRI's agreement with pathology, compares MRI with alternative tests and investigates consistency between different measures of agreement.

METHODS

A systematic literature search was undertaken. Mean differences (MDs) in tumour size between MRI or comparator tests and pathology were pooled by assuming a fixed effect. Limits of agreement (LOA) were estimated from a pooled variance by assuming equal variance of the differences across studies.

RESULTS

Data were extracted from 19 studies (958 patients). The pooled MD between MRI and pathology from six studies was 0.1 cm (95% LOA: -4.2 to 4.4 cm). Similar overestimation for MRI (MD: 0.1 cm) and ultrasound (US) (MD: 0.1 cm) was observed, with comparable LOA (two studies). Overestimation was lower for MRI (MD: 0.1 cm) than mammography (MD: 0.4 cm; two studies). Overestimation by MRI (MD: 0.1 cm) was smaller than underestimation by clinical examination (MD: -0.3 cm). The LOA for mammography and clinical examination were wider than that for MRI. Percentage agreement between MRI and pathology was greater than that of comparator tests (six studies). The range of Pearson's/Spearman's correlations was wide (0.21-0.92; 16 studies). Inconsistencies between MDs, percentage agreement and correlations were common.

CONCLUSION

Magnetic resonance imaging appears to slightly overestimate pathologic size, but measurement errors may be large enough to be clinically significant. Comparable performance by US was observed, but agreement with pathology was poorer for mammography and clinical examination. Percentage agreement can provide supplementary information to MDs and LOA, but Pearson's/Spearman's correlation does not provide evidence of agreement and should be avoided. Further comparisons of MRI and other tests using the recommended methods are warranted.

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

BACKGROUND

Increased pathologic complete response (pCR) rates observed with neoadjuvant chemotherapy (NCT) for some subsets of patients with invasive breast cancer have prompted interest in whether patients who achieved a pCR can be identified preoperatively and potentially spared the morbidity of surgery. The objective of this multicenter, retrospective study was to estimate the accuracy of preoperative magnetic resonance imaging (MRI) in predicting a pCR in the breast.

METHODS

MRI studies at baseline and after the completion of NCT plus data regarding pathologic response were collected retrospectively from 746 women who received treatment at 8 institutions between 2002 and 2011. Tumors were characterized by immunohistochemical phenotype into 4 categories based on receptor expression: hormone (estrogen and progesterone) receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative (n = 327), HR-positive/HER2-positive, (n = 148), HR-negative/HER2-positive, (n = 101), and triple-negative (HR-negative/HER2 negative; n = 155). In all, 194 of 249 patients (78%) with HER2-positive tumors received trastuzumab. Univariate and multivariate analyses of factors associated with radiographic complete response (rCR) and pCR were performed.

RESULT

For the total group, the rCR and pCR rates were 182 of 746 patients (24%) and 179 of 746 patients (24%), respectively, and the highest pCR rate was observed for the triple-negative subtype (57 of 155 patients; 37%) and the HER2-positive subtype (38 of 101 patients; 38%). The overall accuracy of MRI for predicting pCR was 74%. The variables sensitivity, negative predictive value, positive predictive value, and accuracy differed significantly among tumor subtypes, and the greatest negative predictive value was observed in the triple-negative (60%) and HER2-positive (62%) subtypes.

CONCLUSIONS

The overall accuracy of MRI for predicting pCR in invasive breast cancer patients who were receiving NCT was 74%. The performance of MRI differed between subtypes, possibly influenced by differences in pCR rates between groups. Future studies will determine whether MRI in combination with directed core biopsy improves the predictive value of MRI for pathologic response.

Which imaging modality is superior for prediction of response to neoadjuvant chemotherapy in patients with triple negative breast cancer?

Background and Objectives. Triple negative breast cancer (TNBC) has been shown to be generally chemosensitive. We sought to investigate the utility of mammography (MMG), ultrasonography (US), and breast magnetic resonance imaging (MRI) in predicting residual disease following neoadjuvant chemotherapy for TNBC. Methods. We identified 148 patients with 151 Stage I-III TNBC treated with neoadjuvant chemotherapy. Residual tumor size was estimated by MMG, US, and/or MRI prior to surgical intervention and compared to the subsequent pathologic residual tumor size. Data were compared using chi-squared test. Results. Of 151 tumors, 44 (29%) did not have imaging performed prior to surgical treatment. Thirty-eight (25%) tumors underwent a pathologic complete response (pCR), while 113 (75%) had residual invasive disease. The imaging modality was accurate to within 1 cm of the final pathologic residual disease in 74 (69%) cases and within 2 cm in 94 (88%) cases. Groups were similar with regards to patient age, race, tumor size and grade, and clinical stage (P > 0.05). Accuracy to within 1 cm was the highest for US (83%) and the lowest for MMG (56%) (P < 0.05). Conclusions. Breast US and MRI were more accurate than MMG in predicting residual tumor size following neoadjuvant chemotherapy in patients with TNBC. None of the imaging modalities were predictive of a pCR.

The role of magnetic resonance imaging in assessing residual disease and pathologic complete response in breast cancer patients receiving neoadjuvant chemotherapy: a systematic review

OBJECTIVES

This systematic review aimed to assess the role of magnetic resonance imaging (MRI) in evaluating residual disease extent and the ability to detect pathologic complete response (pCR) after neoadjuvant chemotherapy for invasive breast cancer.

METHODS

PubMed, the Cochrane Library, MEDLINE, and Embase databases were searched for relevant studies published until 1 July 2012. After primary selection, two reviewers independently assessed the content of each eligible study using a standardised extraction form and pre-defined inclusion and exclusion criteria.

RESULTS

A total of 35 eligible studies were selected. Correlation coefficients of residual tumour size assessed by MRI and pathology were good, with a median value of 0.698. Reported sensitivity, specificity, positive predictive value and negative predictive value for predicting pCR with MRI ranged from 25 to 100 %, 50-97 %, 47-73 % and 71-100 %, respectively. Both overestimation and underestimation were observed. MRI proved more accurate in determining residual disease than physical examination, mammography and ultrasound. Diagnostic accuracy of MRI after neoadjuvant chemotherapy could be influenced by treatment regimen and breast cancer subtype.

CONCLUSIONS

Breast MRI accuracy for assessing residual disease after neoadjuvant chemotherapy is good and surpasses other diagnostic means. However, both overestimation and underestimation of residual disease extent could be observed.

MAIN MESSAGES

• Breast MRI accuracy for assessing residual disease is good and surpasses other diagnostic means. • Correlation coefficients of residual tumour size assessed by MRI and pathology were considered good. • However, both overestimation and underestimation of residual disease were observed. • Diagnostic accuracy of MRI seems to be affected by treatment regimen and breast cancer subtype.

Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after neoadjuvant therapy

BACKGROUND

It has been proposed that magnetic resonance imaging (MRI) be used to guide breast cancer surgery by differentiating residual tumor from pathologic complete response (pCR) after neoadjuvant chemotherapy. This meta-analysis examines MRI accuracy in detecting residual tumor, investigates variables potentially affecting MRI performance, and compares MRI with other tests.

METHODS

A systematic literature search was undertaken. Hierarchical summary receiver operating characteristic (HSROC) models were used to estimate (relative) diagnostic odds ratios ([R]DORs). Summary sensitivity (correct identification of residual tumor), specificity (correct identification of pCR), and areas under the SROC curves (AUCs) were derived. All statistical tests were two-sided.

RESULTS

Forty-four studies (2050 patients) were included. The overall AUC of MRI was 0.88. Accuracy was lower for "standard" pCR definitions (referent category) than "less clearly described" (RDOR = 2.41, 95% confidence interval [CI] = 1.11 to 5.23) or "near-pCR" definitions (RDOR = 2.60, 95% CI = 0.73 to 9.24; P = .03.) Corresponding AUCs were 0.83, 0.90, and 0.91. Specificity was higher when negative MRI was defined as contrast enhancement less than or equal to normal tissue (0.83, 95% CI = 0.64 to 0.93) vs no enhancement (0.54, 95% CI = 0.39 to 0.69; P = .02), with comparable sensitivity (0.83, 95% CI = 0.69 to 0.91; vs 0.87, 95% CI = 0.80 to 0.92; P = .45). MRI had higher accuracy than mammography (P = .02); there was only weak evidence that MRI had higher accuracy than clinical examination (P = .10). No difference in MRI and ultrasound accuracy was found (P = .15).

CONCLUSIONS

MRI accurately detects residual tumor after neoadjuvant chemotherapy. Accuracy was lower when pCR was more rigorously defined, and specificity was lower when test negativity thresholds were more stringent; these definitions require standardization. MRI is more accurate than mammography; however, studies comparing MRI and ultrasound are required.

Multifunctional magnetic resonance imaging probes

Magnetic resonance imaging (MRI) is a key imaging modality in cancer diagnostics and therapy monitoring. MRI-based tumor detection and characterization is commonly achieved by exploiting the compositional, metabolic, cellular, and vascular differences between malignant and healthy tissue. Contrast agents are frequently applied to enhance this contrast. The last decade has witnessed an increasing interest in novel multifunctional MRI probes. These multifunctional constructs, often of nanoparticle design, allow the incorporation of multiple imaging agents for complementary imaging modalities as well as anti-cancer drugs for therapeutic purposes. The composition, size, and surface properties of such constructs can be tailored as to improve biodistribution and ensure optimal delivery to the tumor microenvironment by passive or targeted mechanisms. Multifunctional MRI probes hold great promise to facilitate more specific tumor diagnosis, patient-specific treatment planning, the monitoring of local drug delivery, and the early evaluation of therapy. This chapter reviews the state-of-the-art and new developments in the application of multifunctional MRI probes in oncology.

Diffuse optical spectroscopy evaluation of treatment response in women with locally advanced breast cancer receiving neoadjuvant chemotherapy

The aim of this study was to investigate the potential of diffuse optical spectroscopy for monitoring of patients with locally advanced breast cancer (LABC) undergoing neoadjuvant chemotherapy. Fifteen women receiving treatment for LABC had the affected breast scanned before; 1 week, 4 weeks, and 8 weeks after treatment initiation; and before surgery. Optical properties related to tissue microstructure and biochemical composition were obtained. Clinical and pathologic tumor response was evaluated using whole-mount pathology after mastectomy. Patients who responded to treatment demonstrated an initial increase followed by a drop in optical parameters measured in the whole breast, whereas nonresponding patients demonstrated only a drop in the same parameters 1 week after treatment initiation. Responding patients demonstrated a significant increase of 17% ± 7%, 8% ± 8%, 10% ± 7%, 11% ± 11%, and 16% ± 15% in deoxygenated hemoglobin, oxygenated hemoglobin, total hemoglobin concentrations, water percentage, and tissue optical index, 1 week after treatment initiation, respectively. In contrast, nonresponding patients had a decrease of 14% ± 9%, 18% ± 7%, 17% ± 7%, 29% ± 7%, and 32% ± 9% in their corresponding optical parameters. Deoxygenated hemoglobin concentration (with 100% sensitivity, 83% specificity) and water percentage (with 75% sensitivity, 100% specificity) were found to be the best predictors of treatment response at 1 week after starting treatment. The results of this study suggest that optical parameters can be potentially used to predict and monitor patients' responses to neoadjuvant chemotherapy and can form a basis for the customization of treatments in which inefficacious treatments can be switched to more efficacious therapies.

Can diffusion-weighted MR imaging and contrast-enhanced MR imaging precisely evaluate and predict pathological response to neoadjuvant chemotherapy in patients with breast cancer?

Clinical evidence regarding the value of MRI for therapy responses assessment in breast cancer is increasing. The objective of this study is to compare the diagnostic capability of diffusion-weighted MR imaging (DW-MRI) and contrast-enhanced MR imaging (CE-MRI) to evaluate and predict pathological response in breast cancer patients receiving neoadjuvant chemotherapy (NAC). We performed a meta-analysis of all available studies of the diagnostic performance of DW-MRI or CE-MRI to evaluate and predict pathological response to NAC in patients with breast cancer. We determined sensitivities and specificities across studies, calculated positive and negative likelihood ratios (LR+ and LR-), diagnostic odds ratio (DOR) and constructed summary receiver operating characteristic curves using hierarchical regression models. Methodological quality was assessed by QUADAS tool. Thirty-four studies met the inclusion criteria and involved 1,932 pathologically confirmed patients in total. Methodological quality was relatively high. DW-MRI sensitivity was 0.93 (95 % CI 0.82-0.97) and specificity was 0.82 (95 % CI 0.70-0.90). Overall LR+ was 5.09 (95 % CI 3.09-8.38), LR- was 0.09 (95 % CI 0.04-0.22), and DOR was 55.59 (95 % CI 21.80-141.80). CE-MRI sensitivity was 0.68 (95 % CI 0.57-0.77) and specificity was 0.91 (95 % CI 0.87-0.94). Overall LR+ was 7.48 (95 % CI 5.29-10.57), LR- was 0.36 (95 % CI 0.27-0.48), and DOR was 20.98 (95 % CI 13.24-33.24). Our study confirms that DW-MRI is a high sensitive and CE-MRI is a high specific modality in predicting pathological response to NAC in breast cancer patients. The combined use of DW-MRI and CE-MRI has the potential to improve the diagnostic performance in monitoring NAC. Further large prospective studies are warranted to assess the actual value of this combination in breast cancer preoperative treatment screening.

Magnetic resonance imaging of the breast for cancer diagnosis and staging

Gadolinium-enhanced breast magnetic resonance imaging (MRI) is optimally suited for the diagnosis and assessment of breast cancer. The complete breast MRI examination, which includes select nonenhanced sequences, yields abundant information about the nature and stage of disease. In this article, we will explore cancer diagnosis by examining the main imaging features of breast malignancy as well as the assessment of surrounding structures. We will then discuss current ideas in the use of breast MRI in breast cancer, including high-risk screening, evaluation of extent of disease, role in surgical planning, and the use of MRI in the patient receiving neoadjuvant chemotherapy. Breast MRI plays an important role in the assessment of patients with breast malignancy-a role that is yet to be fully defined and used. By understanding the strengths and weakness of this imaging method in cancer evaluation, we hope to highlight the appropriate uses of the technique.

Accuracy of breast magnetic resonance imaging in predicting pathologic response in patients treated with neoadjuvant chemotherapy

BACKGROUND

Prior studies of the ability of magnetic resonance imaging (MRI) to predict pathologic response to neoadjuvant chemotherapy have shown conflicting results that vary depending on baseline molecular characteristics. This study examines the ability of MRI to predict pathologic complete response (pCR) and explores the influence of tumor molecular profiles on MRI sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

METHODS

Eighty-one patients with invasive breast cancer treated with neoadjuvantsystemic therapy between 2002 and 2009 who were imaged with breast MRI pre- and post-treatment were reviewed. Patient, tumor, and treatment characteristics were recorded. Comparisons of molecular subsets and their influence on MRI sensitivity, specificity, PPV, and NPV were made using χ(2)contingency tables.

RESULTS

The sensitivity, specificity, PPV, and NPV of MRI for predicting pCR for the total group were 92%, 50%, 74%, and 80%, respectively. Patients had the following molecular subtypes: 33/81 (41%) HR+Her2-, 23/81 (28%) HR+/-Her2 +, and 25/81(31%) triple receptor negative (TN). Molecular subtype did not demonstrate a significant correlation of radiographic and pathologic response, although MRI NPV was highest in the TN subset (100%) followed by those with HR+/-Her2+ disease (87.5%). Multivariate analysis did not show that tumor characteristics (estrogen receptor status, progesterone receptor status, HER2 status) or neoadjuvant treatment (doxorubicin, cyclophosphamide, paclitaxel versus other or trastuzumab) had any effect on MRI sensitivity or specificity.

CONCLUSIONS

In patients receiving neoadjuvant systemic therapy for invasive breast cancer, molecular subtype and systemic regimen administered did not significantly influence the sensitivity, specificity, PPV, or NPV of MRI in predicting pathologic response.

MRI in breast cancer therapy monitoring

Breast MRI has several roles in the clinical management of breast cancer, including as a screening method for high-risk women, as a diagnostic tool used as an adjunct to mammography and ultrasound, and for the staging of disease extent prior to treatment. In addition to these uses, MRI is also employed to track small changes in tumor size and microenvironment. MRI has produced several early indicators of treatment response in clinical trials over the last 10  years, including initial lesion pattern, changes in lesion size, kinetic parameters, apparent diffusion coefficient and T(2) value; the related technique of (1) H MRS has also shown that choline concentration, T(2) value and water-to-fat ratio are response indicators. In addition to measuring anatomical changes in the lesion size, as performed in traditional radiology, MRI has the ability to track vascular and cellular changes using dynamic contrast-enhanced MRI and diffusion-weighted MRI, respectively. By adding (1) H MRS to MRI examinations, metabolic changes can also be determined. These functional imaging techniques allow studies to focus on early time points relative to neoadjuvant treatment. Early treatment response predictors may allow therapy to be tailored to individual patients and thus aid in the realization of the goal of personalized medicine.

Utility of breast MRI for evaluation of residual disease following excisional biopsy

BACKGROUND

Because benign postoperative changes may overlap those of malignancy, the utility of breast MRI following an excisional biopsy is unclear. We sought to investigate the ability of MRI to predict residual disease following an excisional biopsy for breast cancer.

MATERIALS AND METHODS

We reviewed 93 patients who underwent surgical treatment for stage 0-III breast cancer at our institution from January 2005 to May 2008. All patients had previously undergone excisional biopsy with subsequent MRI. Patient, tumor, and treatment characteristics were collected. Descriptive statistics were utilized for data summary and data were compared using Fisher's exact or χ(2) tests.

RESULTS

The mean age of the 84 patients who had additional surgery following MRI was 51 ± 7 y. Thirteen (15%) patients had only postoperative changes on MRI; six had residual disease on final pathology. Of 71 patients with MRI findings suspicious for residual disease, 54 (76%) had pathologic confirmation, while 17 (24%) had only benign pathology. The sensitivity and specificity of MRI following excisional biopsy were 90% and 29%, respectively. Overall, 49 (58%) of the 84 patients underwent mastectomy, including 11 of 24 (46%) with negative final pathology. Patient age, tumor size, tumor grade, biomarker profile, nodal status, and MRI findings were not predictive of surgical treatment type (P > 0.05).

CONCLUSION

Although excisional biopsy decreases the specificity of breast MRI, its sensitivity remains high. Nearly 50% of patients with a suspicious MRI and negative final pathology underwent mastectomy, suggesting that additional biopsy of all suspicious MRI findings is necessary to avoid surgical overtreatment.

Size assessment of breast lesions by means of a computer-aided detection (CAD) system for magnetic resonance mammography

PURPOSE

The aim of this study was to investigate the efficacy of a dedicated software tool for automated volume measurement of breast lesions in contrast-enhanced (CE) magnetic resonance mammography (MRM).

MATERIAL AND METHODS

The size of 52 breast lesions with a known histopathological diagnosis (three benign, 49 malignant) was automatically evaluated using different techniques. The volume of all lesions was measured automatically (AVM) from CE 3D MRM examinations by means of a computer-aided detection (CAD) system and compared with the size estimates based on maximum diameter measurement (MDM) on MRM, ultrasonography (US), mammography and histopathology.

RESULTS

Compared with histopathology as the reference method, AVM understimated lesion size by 4% on average. This result was similar to MDM (3% understimation, not significantly different) but significantly better than US and mammographic lesion measurements (24% and 33% size underestimation, respectively).

CONCLUSIONS

AVM is as accurate as MDM but faster. Both methods are more accurate for size assessment of breast lesions compared with US and mammography.

Indications for breast MRI: self-assessment module

The educational objectives for this self-assessment module are for the participant to exercise, self-assess, and improve his or her understanding of breast MRI.

[Breast magnetic resonance imaging: state of the art and clinical applications]

Breast magnetic resonance imaging is a modality that is being progressively integrated into the breast radiologist's daily clinical practice. There is consensus on the minimal technical requirements that a breast MR exam should have in order to attain diagnostic quality. Diagnostic criteria are mainly based on the American College of Radiology's BI-RADS magnetic resonance imaging categories. Breast cancer staging is a main clinical application, but it is not universally accepted. Other applications are: response evaluation in patients treated with chemotherapy, screening in high-risk patients, cancer of unknown origin, assessment of a possible relapse and breast implant evaluation.

Magnetic resonance imaging and ultrasonography in predicting infiltrating residual disease after preoperative chemotherapy in stage II-III breast cancer

BACKGROUND

This study was designed to evaluate the accuracy of breast magnetic resonance imaging (MRI) and ultrasonography (US) in predicting the extent of breast residual disease after preoperative chemotherapy.

METHODS

Patients with stage II-III invasive breast tumors who received preoperative chemotherapy and were imaged with post-treatment MRI were included. Histopathological verification was available for all patients. The longest diameter of residual tumor measured with MRI and US has been compared with the infiltrating residual tumor size at pathologic evaluation.

RESULTS

A total of 108 patients were enrolled: 59 were imaged with both MRI and US (MRI group), and 49 were imaged with US only (non-MRI group). The non-MRI group was enrolled as an external control to avoid possible bias in the selection of patients. In the MRI group, the means of the deltas between MRI residual tumor size and pathologic size and between US and pathologic size were 0.16 cm and -0.06 cm respectively (P = not significant). Overall, a discrepancy limited in the interval from -0.5 cm to +0.5 cm compared with the pathologic size was observed in 54% and 51% of the patients with MRI and US, respectively (P = not significant). The linear correlation between the radiological measurement and pathologic tumor size was r = 0.53 for MRI and r = 0.66 for breast US. In the non-MRI group, the mean of the deltas between US residual tumor size and pathologic size was 0.06 cm, and the linear correlation was r = 0.79.

CONCLUSIONS

In this series of patients, MRI and US do not show significant differences in predicting the breast residual infiltrating tumor after preoperative chemotherapy.

Neoadjuvant chemotherapy in breast cancer-response evaluation and prediction of response to treatment using dynamic contrast-enhanced and diffusion-weighted MR imaging

Objective

To explore the predictive value of MRI parameters and tumour characteristics before neoadjuvant chemotherapy (NAC) and to compare changes in tumour size and tumour apparent diffusion coefficient (ADC) during treatment, between patients who achieved pathological complete response (pCR) and those who did not.

Methods

Approval by the Regional Ethics Committee and written informed consent were obtained. Thirty-one patients with invasive breast carcinoma scheduled for NAC were enrolled (mean age, 50.7; range, 37–72). Study design included MRI before treatment (Tp0), after four cycles of NAC (Tp1) and before surgery (Tp2). Data in pCR versus non-pCR groups were compared and cut-off values for pCR prediction were evaluated.

Results

Before NAC, HER2 overexpression was the single significant predictor of pCR (p = 0.006). At Tp1 ADC, tumour size and changes in tumour size were all significantly different in the pCR and non-pCR groups. Using 1.42 × 10⁻³ mm²/s as the cut-off value for ADC, pCR was predicted with sensitivity and specificity of 88% and 80%, respectively. Using a cut-off value of 83% for tumour volume reduction, sensitivity and specificity for pCR were 91% and 80%.

Conclusion

ADC, tumour size and tumour size reduction at Tp1 were strong independent predictors of pCR.