Early and delayed prediction of axillary lymph node neoadjuvant response by 18F-FDG PET/CT in patients with locally advanced breast cancer

A nomogram model for predicting the risk of axillary lymph node metastasis in patients with early breast cancer and cN0 status

Axillary staging is commonly performed via sentinel lymph node biopsy for patients with early breast cancer (EBC) presenting with clinically negative axillary lymph nodes (cN0). The present study aimed to investigate the association between axillary lymph node metastasis (ALNM), clinicopathological characteristics of tumors and results from axillary ultrasound (US) scanning. Moreover, a nomogram model was developed to predict the risk for ALNM based on relevant factors. Data from 998 patients who met the inclusion criteria were retrospectively reviewed. These patients were then randomly divided into a training and validation group in a 7:3 ratio. In the training group, receiver operating characteristic curve analysis was used to identify the cutoff values for continuous measurement data. R software was used to identify independent ALNM risk variables in the training group using univariate and multivariate logistic regression analysis. The selected independent risk factors were incorporated into a nomogram. The model differentiation was assessed using the area under the curve (AUC), while calibration was evaluated through calibration charts and the Hosmer-Lemeshow test. To assess clinical applicability, a decision curve analysis (DCA) was conducted. Internal verification was performed via 1000 rounds of bootstrap resampling. Among the 998 patients with EBC, 228 (22.84%) developed ALNM. Multivariate logistic analysis identified lymphovascular invasion, axillary US findings, maximum diameter and molecular subtype as independent risk factors for ALNM. The Akaike Information Criterion served as the basis for both nomogram development and model selection. Robust differentiation was shown by the AUC values of 0.855 (95% CI, 0.817-0.892) and 0.793 (95% CI, 0.725-0.857) for the training and validation groups, respectively. The Hosmer-Lemeshow test yielded P-values of 0.869 and 0.847 for the training and validation groups, respectively, and the calibration chart aligned closely with the ideal curve, affirming excellent calibration. DCA showed that the net benefit from the nomogram significantly outweighed both the 'no intervention' and the 'full intervention' approaches, falling within the threshold probability interval of 12-97% for the training group and 17-82% for the validation group. This underscores the robust clinical utility of the model. A nomogram model was successfully constructed and validated to predict the risk of ALNM in patients with EBC and cN0 status. The model demonstrated favorable differentiation, calibration and clinical applicability, offering valuable guidance for assessing axillary lymph node status in this population.

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.

Nomograms for Predicting Axillary Lymph Node Status Reconciled With Preoperative Breast Ultrasound Images

Introduction

The axillary lymph node (ALN) status of breast cancer patients is an important prognostic indicator. The use of primary breast mass features for the prediction of ALN status is rare. Two nomograms based on preoperative ultrasound (US) images of breast tumors and ALNs were developed for the prediction of ALN status.

Methods

A total of 743 breast cancer cases collected from 2016 to 2019 at the Second Affiliated Hospital of Harbin Medical University were randomly divided into a training set (n = 523) and a test set (n = 220). A primary tumor feature model (PTFM) and ALN feature model (ALNFM) were separately generated based on tumor features alone, and a combination of features was used for the prediction of ALN status. Logistic regression analysis was used to construct the nomograms. A receiver operating characteristic curve was plotted to obtain the area under the curve (AUC) to evaluate accuracy, and bias-corrected AUC values and calibration curves were obtained by bootstrap resampling for internal and external verification. Decision curve analysis was applied to assess the clinical utility of the models.

Results

The AUCs of the PTFM were 0.69 and 0.67 for the training and test sets, respectively, and the bias-corrected AUCs of the PTFM were 0.67 and 0.67, respectively. Moreover, the AUCs of the ALNFM were 0.86 and 0.84, respectively, and the bias-corrected AUCs were 0.85 and 0.81, respectively. Compared with the PTFM, the ALNFM showed significantly improved prediction accuracy (p < 0.001). Both the calibration and decision curves of the ALNFM nomogram indicated greater accuracy and clinical practicality. When the US tumor size was ≤21.5 mm, the Spe was 0.96 and 0.92 in the training and test sets, respectively. When the US tumor size was greater than 21.5 mm, the Sen was 0.85 in the training set and 0.87 in the test set. Our further research showed that when the US tumor size was larger than 35 mm, the Sen was 0.90 in the training set and 0.93 in the test set.

Conclusion

The ALNFM could effectively predict ALN status based on US images especially for different US tumor size.

The Evolving Role of FDG-PET/CT in the Diagnosis, Staging, and Treatment of Breast Cancer

The applications of 2-deoxy-2-[¹⁸F]fluoro-D-glucose positron emission tomography/X-ray computed tomography (PET/CT) in the management of patients with breast cancer have been extensively studied. According to these studies, PET/CT is not routinely performed for the diagnosis of primary breast cancer, although PET/CT in specific subtypes of breast cancer correlates with histopathologic features of the primary tumor. PET/CT can detect metastases to mediastinal, axial, and internal mammary nodes, but it cannot replace the sentinel node biopsy. In detection of distant metastases, this imaging tool may have a better accuracy in detecting lytic bone metastases compared to bone scintigraphy. Thus, PET/CT is recommended when advanced-stage disease is suspected, and conventional modalities are inconclusive. Also, PET/CT has a high sensitivity and specificity to detect loco-regional recurrence and is recommended in asymptomatic patients with rising tumor markers. Numerous studies support the future role of PET/CT in prediction of response to neoadjuvant chemotherapy (NAC). PET/CT has a higher diagnostic value for prognostic risk stratification in comparison with conventional modalities. With the continuing research on the treatment planning and evaluation of patients with breast cancer, the role of PET/CT can be further extended.

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.

Predictive and prognostic potential of volume-based metabolic variables obtained by a baseline 18F-FDG PET/CT in breast cancer with neoadjuvant chemotherapy indication

AIM

To investigate the usefulness of metabolic variables using ¹⁸F-FDG PET/CT in the prediction of neoadjuvant chemotherapy (NC) response and the prognosis in locally advanced breast cancer (LABC).

MATERIAL AND METHODS

Prospective study including 67 patients with LABC, NC indication and a baseline ¹⁸F-FDG PET/CT. After breast tumor segmentation, SUV variables (SUVmax, SUVmean and SUVpeak) and volume-based variables, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG), were obtained. Tumors were grouped into molecular phenotypes, and classified as responders or non-responders after completion of NC. Disease-free status (DFs), disease-free survival (DFS), and overall survival (OS) were assessed. A univariate and multivariate analysis was performed to study the potential of all variables to predict DFs, DFS, and OS.

RESULTS

Fourteen patients were classified as responders. Median±SD of DFS and OS was 43±15 and 46±13 months, respectively. SUV and TLG showed a significant correlation (p<0.005) with the histological response, with higher values in responders compared to non-responders. MTV and TLG showed a significant association with DFs (p=0.015 and p=0.038 respectively). Median, mean and SD of MTV and TLG for patients with DFs were: 8.90, 13.73, 15.10 and 33.78, and 90.54 and 144.64, respectively. Median, mean and SD of MTV and TLG for patients with non-DFs were: 16.72, 29.70 and 31.09 and 90.89, 210.98 and 382.80, respectively. No significant relationships were observed with SUV variables and DFs. Volume-based variables were significantly associated with OS and DFS, although in multivariate analysis only MTV was related to OS. No SUV variables showed an association with the prognosis.

CONCLUSION

Volume-based metabolic variables obtained with ¹⁸F-FDG PET/CT, unlike SUV based variables, were good predictors of both neoadjuvant chemotherapy response and prognosis.

Additional value of 18F-FDG PET/CT response evaluation in axillary nodes during neoadjuvant therapy for triple-negative and HER2-positive breast cancer

Background

¹⁸F-FDG PET/CT can monitor metabolic activity in early breast cancer during neoadjuvant systemic therapy (NST), but it is unknown if the metabolic breast and axillary response differ. We evaluated the correlation between metabolic breast and axillary response at various time points during NST. Furthermore, we analysed if the combined metabolic response improves pathologic complete response (pCR) prediction compared to using the metabolic breast response alone.

Methods

¹⁸F-FDG PET/CT was performed at baseline (PET1), 2–3 weeks (PET2), and 6–8 weeks (PET3) of NST in patients with triple-negative (TN) and HER2-positive node-positive breast cancer. SUVmax and ∆SUVmax were determined separately for breast and axilla. Spearman’s correlation coefficients (r) between both localisations were calculated. The accuracy of pCR total (ypT0/is,ypN0) prediction using the metabolic response in breast, axilla or both was examined using logistic regression analysis.

Results

Hundred-five patients were included: 45 TN and 60 HER2-positive tumours. The metabolic response in breast and axilla correlated moderately in TN tumours (r = 0.57) using ∆SUVmax between PET1-PET3 and poorly in HER2-positive tumours (r = 0.49) using SUVmax at PET2. In TN tumours, metabolic breast response predicted pCR well without improvement after adding axillary response (c-index 0.82 versus 0.85, p = 0.63). In HER2-positive tumours, metabolic breast response predicted pCR poorly with improvement after adding axillary response (c-index 0.64 versus 0.72, p = 0.06).

Conclusions

¹⁸F-FDG PET/CT response during NST differs between breast and axilla. In TN tumours, pCR total prediction can be made independent of metabolic axillary response. In HER2-positive tumours, axillary response may improve pCR total prediction. These findings may help guide PET/CT-response-based changes during NST.

Trial registration

NTR NTR1797. Registered 29 May 2009, retrospectively registered.

Electronic supplementary material

The online version of this article (doi:10.1186/s40644-017-0117-5) contains supplementary material, which is available to authorized users.

The diagnostic performance of sentinel lymph node biopsy in pathologically confirmed node positive breast cancer patients after neoadjuvant systemic therapy: A systematic review and meta-analysis

PURPOSE

To provide a systematic review and meta-analysis of studies investigating sentinel lymph node biopsy after neoadjuvant systemic therapy in pathologically confirmed node positive breast cancer patients.

METHODS

Pubmed and Embase databases were searched until June 19th, 2015. All abstracts were read and data extraction was performed by two independent readers. A random-effects model was used to pool the proportion for identification rate, false-negative rate (FNR) and axillary pCR with 95% confidence intervals. Subgroup analyses affirmed potential confounders for identification rate and FNR.

RESULTS

A total of 997 abstracts were identified and eventually eight studies were included. Pooled estimates were 92.3% (90.8-93.7%) for identification rate, 15.1% (12.7-17.6%) for FNR and 36.8% (34.2-39.5%) for axillary pCR. After subgroup analysis, FNR is significantly worse if one sentinel node was removed compared to two or more sentinel nodes (23.9% versus 10.4%, p = 0.026) and if studies contained clinically nodal stage 1-3, compared to studies with clinically nodal stage 1-2 patients (21.4 versus 13.1%, p = 0.049). Other factors, including single tracer mapping and the definition of axillary pCR, were not significantly different.

CONCLUSION

Based on current evidence it seems not justified to omit further axillary treatment in every clinically node positive breast cancer patients with a negative sentinel lymph node biopsy after neoadjuvant systemic therapy.