Response In Axillary Nodes Research Articles

Elastography-based AI model can predict axillary status after neoadjuvant chemotherapy in breast cancer with nodal involvement: A prospective, multicenter, diagnostic study

Objective: To develop a model for accurate prediction of axillary lymph node (LN) status after neoadjuvant chemotherapy (NAC) in breast cancer patients with nodal involvement. Methods: Between October 2018 and February 2024, 671 breast cancer patients with biopsy-proven LN metastasis who received NAC followed by axillary LN dissection were enrolled in this prospective, multicenter study. Preoperative ultrasound (US) images, including B-mode ultrasound (BUS) and shear wave elastography (SWE), were obtained. The included patients were randomly divided at a ratio of 8:2 into a training set and an independent test set, with five-fold cross-validation applied to training set. We first identified clinicopathological characteristics and conventional US features significantly associated with the axillary LN response and developed corresponding prediction models. We then constructed deep learning radiomics (DLR) models based on BUS and SWE data. Models performances were compared, and a combination model was developed using significant clinicopathological data and interpreted US features with the SWE-based DLR model. Discrimination, calibration and clinical utility of this model were analyzed using receiver operating characteristic curve, calibration curve and decision curve, respectively. Results: Axillary pathologic complete response (pCR) was achieved in 52.41% of patients. In the test cohort, the clinicopathologic model had an accuracy of 71.30%, while radiologists’ diagnoses ranged from 64.26% to 71.11%, indicating limited to moderate predictive ability for the axillary response to NAC. The SWE-based DLR model, with an accuracy of 80.81%, significantly outperformed the BUS-based DLR model, which scored 59.57%. The combination DLR model boasted an accuracy of 88.70% and a false-negative rate of 8.82%. It demonstrated strong discriminatory ability (AUC, 0.95), precise calibration (p value obtained by Hosmer–Lemeshow goodness-of-fit test, 0.68), and practical clinical utility (probability threshold, 2.5-97.5%). Conclusions: The combination SWE-based DLR model can predict the axillary status after NAC in patients with node-positive breast cancer, and thus, may inform clinical decision-making to help avoid unnecessary axillary LN dissection.

Longitudinal ultrasound-based AI model predicts axillary lymph node response to neoadjuvant chemotherapy in breast cancer: a multicenter study

ObjectivesDeveloping a deep learning radiomics model from longitudinal breast ultrasound and sonographer’s axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer.MethodsBreast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model’s performance against sonographer’s diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection.ResultsIn the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer’s diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer’s diagnostic ability, increasing accuracy from 71.9% to 79.2%.ConclusionThe deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery.Clinical relevance statementOur AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer’s axillary diagnosis.Key PointsAxillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound.Our AI model outperformed sonographer’s visual diagnosis on axillary ultrasound.Our deep learning radiomics model can improve sonographers’ diagnosis and might assist in surgical decision-making.

Prognostic Importance of Axillary Lymph Node Response to Neoadjuvant Systemic Therapy on Axillary Surgery in Breast Cancer-A Single Center Experience.

Neoadjuvant systemic treatment (NST) is the standard treatment for HER2+, triple-negative (TN), and highly proliferative luminal HER2- early breast cancer. Pathologic complete response (pCR) after NST is associated with improved outcomes. We evaluated the predictive factors for axillary-pCR (AXpCR) and its impact on the extent of axillary node surgery. This retrospective study included 92 patients (median age of 50.4 years) with an initially node-positive disease. Patients were treated with molecular subtype-specific NST (4.3% were luminal A-like, 28.3% luminal HER2-, 26.1% luminal HER2+, 18.5% HER2+ non-luminal, and 22.8% TN). Axillary-, breast- and total-pCR were achieved in 52.2%, 48.9%, and 38% of patients, respectively. In a binary logistic regression model for the whole population, the only independent factor significantly associated with AXpCR was breast-pCR (OR 7.4; 95% CI 2.6-20.9; p < 0.001). In patients who achieved breast-pCR, aggressive subtypes (HER2+ and TN; OR 11.24) and clinical tumor stage (OR 0.10) had a significant impact on achieving AXpCR. Axillary lymph node dissection was avoided in 53.3% of patients. In conclusion, in node-positive patients with HER2+ and TN subtypes, who achieved breast-pCR after NST, de-escalation of axillary surgery could be considered in most cases.

Neoadjuvant chemotherapy for breast cancer: Pathologic response rates but not tumor size, has an independent prognostic impact on survival.

We investigated the pathologic complete response rates (pCR) and survival outcomes of early breast cancer patients who underwent neoadjuvant chemotherapy (NAC) over 14 years at a French comprehensive cancer center and reported pCR and survival outcomes by tumor subtypes and size. From January 2005 to December 2018, 1150 patients receiving NAC were identified. Correlations between cT stage, breast tumor response, axillary lymph node response, pCR, surgery, and outcomes were assessed. pCR was defined as (ypT0/ypTis) and (ypN0/pN0sn). A pCR was reached in 31.7% (365/1150) of patients and was strongly associated with tumor subtypes, but not with tumor size (pretreatment cT category). Luminal-B Her2-negative and triple-negative (TN) subtypes, cN1 status, older age, and no-pCR had an independent negative prognostic value. Overall survival (OS), relapse-free survival (RFS), and metastasis-free survival (MFS) were not significantly different for cT0-1 compared to cT2 stages. In Cox-model adjusted on in-breast pCR and pN status, ypN1 had a strong negative impact (OS, RFS, and MFS: HR = 3.153, 4.677, and 6.133, respectively), higher than no in-breast pCR (HR = 2.369, 2.252, and 2.323). A negative impact of no pCR on OS was observed for cN0 patients and TN tumors (HR = 4.972) or HER2-positive tumors (HR = 11.706), as well as in Luminal-B Her2-negative tumors on MFS (HR = 2.223) and for Luminal-A on RFS (HR = 4.465) and MFS (HR = 4.185). Achievement of pCR, but not tumor size (pretreatment cT category), has an independent prognostic impact on survival. These results suggest potential NAC benefits in patients with small tumors (<2 cm), even in absence of clinically suspicious lymph nodes. Residual lymph node disease after NAC is the most powerful adverse prognostic factor.

The Role of Ultrasound in Axillary Lymph Node Response to Neoadjuvant Chemotherapy in Breast Cancer Patients

The Role of Ultrasound in Axillary Lymph Node Response to Neoadjuvant Chemotherapy in Breast Cancer Patients

Development of MRI-Based Deep Learning Signature for Prediction of Axillary Response After NAC in Breast Cancer

To develop a MRI-based deep learning signature for predicting axillary response after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients. We enrolled 327 BC patients with axillary lymph node (ALN) metastases receiving axillary operations after NAC. The deep learning features were extracted by ResNet34, which was pretrained by a large, well-annotated dataset from ImageNet. Then we identified deep learning radiomics on magnetic resonance imaging with dynamic contrast enhancement (DCE-MRI) in predicting axillary response after NAC in BC patients. The extraction of 128 deep learning radiomics (DLR) features relied on the DCE-MRI for each patient. After the least absolute shrinkage and selection operator regression analysis, 13, 8, and 21 features remained from the pre-treatment, post-treatment, and combined DCE-MRI, respectively. The DLR signature established based on the combined DCE-MRI achieved good capacity in ALN response after NAC. The support vector machineachieved the best performance with an 0.99area under the curve (AUC) of (95% confidence interval (CI), 0.98-1.00) and 0.83 (95% CI, 0.73-0.92) in the training and test sets, respectively. The LR model established with clinical parameters represented the best performance with 0.73 AUC (95% CI, 0.62-0.84), 0.73 sensitivity, 0.73 specificity, 0.63 PPV, and 0.81 NPV in the test set, respectively. Finally, the integration of radiomic signature and clinical signature resulted in establishing a predictive radiomic nomogram, with an AUC of 0.99 (95%CI, 0.99-1.00). In conclusion, our current study constructed a predictive nomogram through the deep learning method, demonstrating favorable performance in the training and test cohort. The present prognostic model furnishes a precise and objective foundation for directing the surgical strategy toward ALN management in BC patients receiving NAC.

Nodal Response to Neo-Adjuvant Systemic Therapy Predicts Prognosis of cN3c Breast Cancer Patients Receiving Multidisciplinary Therapy

cN3c breast cancer with ipsilateral supraclavicular (SCV) lymph nodal (SCLN) metastasis has a dismal prognosis. We investigated the survival outcomes, patterns and risks of recurrence in those patients after multidisciplinary therapy, as well as the predictors of candidates for SCV area boosting. Consecutive cN3c breast cancer patients without distant metastases from January 2009 to December 2020 in our institution were retrospectively reviewed. Based on nodal response to neoadjuvant therapy (NAT), patients were categorized into three groups: clinical complete response (cCR) not achieved in SCLN (Group A, n = 66), SCLN cCR but axillary node (ALN) did not achieve pathological complete response (pCR, Group B, n = 34), cCR in SCLN and pCR in ALN (Group C, n = 13). The median follow-up time was 32.7 months (range, 21.9-53.3months). The 5-year overall survival (OS) and recurrence-free survival (RFS) rates were 64.6% and 43.7% respectively. Multivariate analysis showed cumulative SCV dose and ypT stage, ALN response and SCV response to NAT were significantly associated with OS and RFS respectively. The 3-year for patients receiving the cumulative SCV dose of ≥60 Gy versus <60 Gy was 81.3% versus 69.0% (P = 0.042). Compared with Group A or B, Group C showed significantly improved RFS (3y-RFS: 53.8% vs 73.6% vs 100%, p = 0.003) and a numerically longer OS (3y-OS: 73.4% vs 86.7% vs 100%, p = 0.089). Meanwhile, Group C showed the lowest rate of DM as first failure (37.9 % vs 23.5% vs 0 in group A, B and C, respectively, p = 0.010). In patients of Group A, the 3-year OS rates for patients receiving the cumulative SCV dose of ≥60 Gy versus <60 Gy was 78.0% versus 57.3% (p = 0.029). Nodal response to NAT is an independent prognostic factor for survival and pattern of failure. cN3c breast cancer patients with SCLN cCR and ALN pCR after NAT are potentially curable. A cumulative SCV dose of ≥60 Gy is positively associated with improved OS, especially in patients of SCLN without achieving cCR. Our data supports the perspective of optimizing radiotherapeutic strategy based on nodal response.

Nodal response to primary systemic therapy predicts prognosis of cN3c breast cancer patients receiving multimodality therapy.

To investigate the survival outcomes, patterns and risks of recurrence in cN3c breast cancer patients after multimodality therapy, as well as the predictors of candidates for ipsilateral supraclavicular (SCV) area boosting. Consecutive cN3c breast cancer patients from January 2009 to December 2020 were retrospectively reviewed. Based on nodal response to primary systemic therapy (PST), patients were categorized into three groups: clinical complete response (cCR) not achieved in SCV lymph nodal (SCLN, Group A), SCLN cCR but axillary node (ALN) did not achieve pathological complete response (pCR, Group B), cCR in SCLN and pCR in ALN (Group C). The median follow-up time was 32.7 months. The 5-year overall survival (OS) and recurrence-free survival (RFS) were 64.6% and 43.7% respectively. Multivariate analysis showed cumulative SCV dose and ypT stage, ALN response and SCV response to PST were significantly associated with OS and RFS respectively. Compared with Group A or B, Group C showed significantly improved 3y-RFS (53.8% vs 73.6% vs 100%, p=0.003), and the lowest rate of DM as first failure (37.9% vs 23.5% vs 0%, p=0.010). In Group A, the 3y-OS for patients receiving the cumulative SCV dose of ≥60Gy versus <60Gy was 78.0% versus 57.3% (p=0.029). Nodal response to PST is an independent prognostic factor for survival and pattern of failure. A cumulative SCV dose of ≥60Gy is positively associated with improved OS, especially in Group A. Our data supports the perspective of optimizing radiotherapeutic strategy based on nodal response.

Response in axillary lymph nodes to neoadjuvant chemotherapy for breast cancers: correlation with breast response, pathologic features, and accuracy of radioactive seed localization

ObjectivesThis study examined the accuracy of radioactive seed localization (RSL) of lymph nodes (LNs) following neoadjuvant chemotherapy (NAC) for invasive breast carcinoma, recorded pathologic features of LNs following NAC, evaluated concordance of response between breast and LNs, and identified clinicopathologic factors associated with higher risk of residual lymph node involvement.MethodsClinical records, imaging, and pathology reports and slides were retrospectively reviewed for 174 breast cancer patients who received NAC. Chi-square and Fisher’s exact tests were used to compare differences in risk of residual lymph node disease.ResultsRetrieval of biopsied pre-therapy positive LN was confirmed in 86/93 (88%) cases overall, and in 75/77 (97%) of cases utilizing RSL. Biopsy clip site was the best pathologic feature to confirm retrieval of a biopsied lymph node. Pre-therapy clinical N stage > 0, positive pre-therapy lymph node biopsy, estrogen and progesterone receptor positivity, Ki67 < 50%, HR + /HER2− tumors, and residual breast disease had higher likelihood of residual lymph node disease after NAC (p < 0.001).ConclusionsRSL-guided LN excision improves retrieval of previously biopsied LNs following NAC. The pathologist can use histologic features to confirm retrieval of targeted LNs, and tumor characteristics can be used to predict a higher risk of residual LN involvement.

Axillary response and outcome in breast cancer patients after neoadjuvant treatment: The role of radiotherapy in reducing recurrence in ypN0 patients with initially cN+ stage.

We aim to explore the clinicopathological features associated with axillary node response and recurrence in breast cancer patients undergoing neoadjuvant treatment (NAT). We retrospectively reviewed the medical records of 486 stage I to III breast cancer patients who received NAT and surgery between 2016 and 2021. A total of 486 cases were reviewed and 154 (31.7%) patients achieved breast pathological complete response (pCR) (ypT0/Tis). Of the 366 cases with initially cN+, 177 (48.4%) cases reach ypN0. Breast pCR is in high accordance to axillary pCR (81.5%). Hormone receptor (HR)-/HER2+ breast cancer patients have the highest axillary pCR rate (78.3%). Patients achieve axillary pCR have a significantly better disease-free survival (DFS) (P=0.0004). Further analysis reveals that the DFS of ypN0 and ypN1 cases are similar (P=0.9049). Moreover, DFS in patients with ypN0 (P<0.0001) and ypN1 (P<0.0001) is significantly better than that in patients with ypN2-3. For post-mastectomy ypN0 cases, radiation could only improve DFS in patients with initially cN+ stage (P=0.0499). Multivariate Cox regression analysis shows that radiation is an independent factor to improve DFS (Hazard ratio (HR): 0.288(0.098-0.841), P=0.0230). Radiation does not improve DFS in pre-cN0/ypN0 patients (P=0.1696). Axillary pCR rate is higher than breast pCR rate. HR-/HER2+ patients have the highest axillary pCR rate. Axillary pCR is associated with better DFS. Radiation could further improve DFS in ypN0 patients with initially positive nodal disease.

CT Radiomics for Predicting Pathological Complete Response of Axillary Lymph Nodes in Breast Cancer After Neoadjuvant Chemotherapy: A Prospective Study.

The diagnostic effectiveness of traditional imaging techniques is insufficient to assess the response of lymph nodes (LNs) to neoadjuvant chemotherapy (NAC), especially for pathological complete response (pCR). A radiomics model based on computed tomography (CT) could be helpful. Prospective consecutive breast cancer patients with positive axillary LNs initially were enrolled, who received NAC prior to surgery. Chest contrast-enhanced thin-slice CT scan was performed both before and after the NAC (recorded as the first and the second CT respectively), and on both of them, the target metastatic axillary LN was identified and demarcated layer by layer. Using pyradiomics-based software that was independently created, radiomics features were retrieved. A pairwise machine learning workflow based on Sklearn (https://scikit-learn.org/) and FeAture Explorer was created to increase diagnostic effectiveness. An effective pairwise auto encoder model was developed by the improvement of data normalization, dimensionality reduction, and features screening scheme as well as the comparison of the prediction effectiveness of the various classifiers. A total of 138 patients were enrolled, and 77 (58.7%) in the overall group achieved pCR of LN after NAC. Nine radiomics features were finally chosen for modeling. The AUCs of the training group, validation group, and test group were 0.944 (0.919-0.965), 0.962 (0.937-0.985), and 1.000 (1.000-1.000), respectively, and the corresponding accuracies were 0.891, 0.912, and 1.000. The pCR of axillary LNs in breast cancer following NAC can be precisely predicted using thin-sliced enhanced chest CT-based radiomics.

Prediction of Primary Tumour and Axillary Lymph Node Response to Neoadjuvant Chemo(Targeted) Therapy with Dedicated Breast [18F]FDG PET/MRI in Breast Cancer.

The aim of this study was to investigate whether sequential hybrid [18F]FDG PET/MRI can predict the final pathologic response to neoadjuvant chemo(targeted) therapy (NCT) in breast cancer. Sequential [18F]FDG PET/MRI was performed before, halfway through and after NCT, followed by surgery. Qualitative response evaluation was assessed after NCT. Quantitatively, the SUVmax obtained by [18F]FDG PET and signal enhancement ratio (SER) obtained by MRI were determined sequentially on the primary tumour. For the response of axillary lymph node metastases (ALNMs), SUVmax was determined sequentially on the most [18F]FDG-avid ALN. ROC curves were generated to determine the optimal cut-off values for the absolute and percentage change in quantitative variables in predicting response. Diagnostic performance in predicting primary tumour response was assessed with AUC. Similar analyses were performed in clinically node-positive (cN+) patients for ALNM response. Forty-one breast cancer patients with forty-two primary tumours and twenty-six cases of pathologically proven cN+ disease were prospectively included. Pathologic complete response (pCR) of the primary tumour occurred in 16 patients and pCR of the ALNMs in 14 cN+ patients. The AUC of the qualitative evaluation after NCT was 0.71 for primary tumours and 0.54 for ALNM responses. For primary tumour response, combining the percentage decrease in SUVmax and SER halfway through NCT achieved an AUC of 0.78. The AUC for ALNM response prediction increased to 0.92 by combining the absolute and the percentage decrease in SUVmax halfway through NCT. Qualitative PET/MRI after NCT can predict the final pathologic primary tumour response, but not the ALNM response. Combining quantitative variables halfway through NCT can improve the diagnostic accuracy for final pathologic ALNM response prediction.

The Oncologic Safety of Sentinel Lymph Node Biopsy in Patients with Node-Positive Breast Cancer with Complete Response to Neoadjuvant Chemotherapy: A Single-Center Experience.

To evaluate the efficiency and safety of sentinel lymph node biopsy (SLNB) in patients with breast cancer with complete response to neoadjuvant chemotherapy (NAC). Ninety-two consecutive (T1-4 and N1-2) patients with breast cancer who had pathologic and/or clinical and radiologic axillary lymph node involvement were included. All patients received NAC. Patients with a clinical and radiologic complete response in the axilla after NAC underwent SLNB. Pathologic complete response (ypCR) was defined as the absence of residual invasive and in situ cancer, and near-complete response (ypNCR) represented in situ and/or ≤ 1 mm residual tumor in the breast and/or presence of malignant cell clusters (≤0.2 mm) and/or micrometastases (≤2.0 mm) in the axillary lymph nodes (ALN) (ypTis/T1mi, ypN0i+/pN1mi). The mean age of the 92 patients was 49.6 ± 10.3 years and the mean follow-up was 34.0 ± 17.8 months. With respect to breast tumors, 23 (25.0%) patients had complete and 14 (15.2%) had a near-complete response to NAC. Complete response in ALN was obtained in 39 (42.4%) patients and near-complete in six (6.5%) patients. The overall survival of the 33 patients who achieved ypCR and ypNCR was 100% and the remaining 59 patients with partial or no response to NAC was 83.1% at a mean follow-up of 34 months (p=0.063). In this study, no event developed in cases with ypCR and ypNCR in the breast and axilla. The persistence of the same results in long-termfollow-ups may enable the use of ypNCR as a positive prognostic marker in addition to ypCR.

Accuracy of ultrasonographic changes during neoadjuvant chemotherapy to predict axillary lymph node response in clinical node-positive breast cancer patients.

PurposeTo evaluate whether changes in ultrasound features during neoadjuvant chemotherapy (NAC) could predict axillary node response in clinically node-positive breast cancer patients.MethodsPatients with biopsy-proven node-positive disease receiving NAC between February 2009 and March 2021 were included. Ultrasound (US) images were obtained using a 5-12-MHz linear array transducer before NAC, after two cycles, and at the completion of NAC. Long and short diameter, cortical thickness, vascularity, and hilum status of the metastatic node were retrospectively reviewed according to breast imaging-reporting and data system (BI-RADS). The included population was randomly divided into a training set and a validation set at a 2:1 ratio using a simple random sampling method. Factors associated with node response were identified through univariate and multivariate analyses. A nomogram combining clinical and changes in ultrasonographic (US) features was developed and validated. The receiver operating characteristic (ROC) and calibration plots were applied to evaluate nomogram performance and discrimination.ResultsA total of 296 breast cancer patients were included, 108 (36.5%) of whom achieved axillary pathologic complete response (pCR) and 188 (63.5%) had residual nodal disease. Multivariate regression indicated that independent predictors of node pCR contain ultrasound features in addition to clinical features, clinical features including neoadjuvant HER2-targeted therapy and clinical response, ultrasound features after NAC including cortical thickness, hilum status, and reduction in short diameter ≥50%. The nomogram combining clinical features and US features showed better diagnostic performance compared to clinical-only model in the training cohort (AUC: 0.799 vs. 0.699, P=0.001) and the validation cohort (AUC: 0.764 vs. 0.638, P=0.027).ConclusionsUltrasound changes during NAC could improve the accuracy to predict node response after NAC in clinically node-positive breast cancer patients.

Study of response of axillary lymph nodal metastases toneoadjuvant chemotherapy in carcinoma breast

Background and aim of the study: Our study aims to evaluate pathological response in axillary lymph nodes with neoadjuvant chemotherapy. Absence of invasive disease in breast and axilla after completion of neoadjuvant chemotherapy on histological examination was taken as pathological complete response (pCR). Absence of invasive disease in axilla after completion of chemotherapy on histological examination was taken as pathological complete response in axilla. Materials and Methods: A prospective observational study was conducted on breast cancer patients who were treated at MNJ Institute of Oncology and Regional Cancer Centre for a period of 22 months. A total of 55 with operable breast cancer and cytologically proven axillary lymph node metastases and subsequently received neoadjuvant chemotherapy were considered for this study. All these patients were registered in our hospital and were followed prospectively. Of them, 2 patients defaulted chemotherapy, 3 patients did not visit hospital after completion of chemotherapy and 1patient died due to reason other than carcinoma breast and all these patients were excluded from the study. Results:In this study, we had pathological complete response in breast and axilla in 24.5% of the study population.

Axillary lymph node response to neoadjuvant systemic therapy with dedicated axillary hybrid 18F-FDG PET/MRI in clinically node-positive breast cancer patients: a pilot study

To investigate the diagnostic performance of dedicated axillary hybrid 18F-2-[18F]-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET)/magnetic resonance imaging (MRI) in detecting axillary pathological complete response (pCR) following neoadjuvant systemic therapy (NST) in clinically node-positive breast cancer patients. Ten prospectively included clinically node-positive breast cancer patients underwent dedicated axillary hybrid 18F-FDG PET/MRI after completing NST followed by axillary surgery. PET images were reviewed by a nuclear medicine physician and coronal T1-weighted and T2-weighted MRI images by a radiologist. All axillary lymph nodes visible on PET/MRI were matched with those removed during axillary surgery. Diagnostic performance parameters were calculated based on patient-by-patient and node-by-node validation with histopathology of the axillary surgical specimen as the reference standard. Six patients achieved axillary pCR at final histopathology. A total of 84 surgically harvested axillary lymph nodes were matched with axillary lymph nodes depicted on PET/MRI. Histopathological examination of the matched axillary lymph nodes resulted in 10 lymph nodes with residual axillary disease of which eight contained macrometastases and two micrometastases. The patient-by-patient analysis yielded a sensitivity, specificity, positive predictive value, and negative predictive value of 25%, 100%, 100%, and 67%, respectively. The diagnostic performance parameters of the node-by-node analysis were 0%, 96%, 0%, and 88%, respectively. Excluding micrometastases from the node-by-node analysis increased the negative predictive value to 90%. This pilot study suggests that the negative predictive value and sensitivity of dedicated axillary 18F-FDG PET/MRI are insufficiently accurate to detect axillary pCR or exclude residual axillary disease following NST in clinically node-positive breast cancer patients.

Radiological prediction of axillary lymph node response following neoadjuvant chemotherapy - An aid to patient selection criteria for reducing axillary surgery

Introduction: Association of Breast Surgery guidelines recommend that sentinel node biopsy (SNB) can safely be considered in patients following neoadjuvant chemotherapy (NAC), with accuracy of SNB improved by combining targeted axillary dissection (TAD) with SNB (TAD-SNB) in initially node positive patients. However, patient selection criteria for TAD-SNB are still to be optimised. Local policy in NHS Tayside from July 2016 was to offer TAD-SNB to patients with complete and excellent response on MRI breast and normal axillary ultrasound (AUSS) after NAC.

Predicting pathological response of locally advanced breast cancer to neoadjuvant chemotherapy: comparing the performance of whole body 18F-FDG PETCT versus DCE-MRI of the breast

BackgroundWith the expansion of the use of the neoadjuvant chemotherapy(NAC) in locally advanced breast cancer (LABC), both dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET CT) are promising methods for assessment of the tumor response during chemotherapy. We aimed to evaluate the diagnostic accuracy of DCE-MRI of breast &18 F-FDG PETCT regarding the assessment of early response to neoadjuvant chemotherapy (NAC) in locally advanced breast cancer patients (LABC) and pathologic complete response (pCR) prediction.ResultsA total of forty LABC patients who had NAC were included in the study. Before and during NAC, PET/CT and DCE-MRI were used. Various morphological and functional criteria were compared and linked with post-operative pathology for both. The MRI sensitivity and specificity in assessing NAC response in conjunction with pathological data were 100% (p = 0.001) and 12.5% (p = 0.18) respectively. The equivalent readings for PET/CT were 94.1% (p = 0.001) and 25% (p = 0.18), respectively, although the estimated total accuracy for both MRI and PETCT was the same measuring 94.1% (p = 0.001) and 25% (p = 0.18) (72%). PETCT had a higher overall accuracy than MRI in assessing the response of axillary lymph nodes (ALN) to NAC (64% and 56%, respectively). Longest diameter of lesion, ADC value, and maximal enhancement in baseline MRI, SUVmax and SUV mean in baseline PETCT were all significant predictors of rCR.ConclusionDuring NAC in the primary breast mass and ALN, DCE-MRI demonstrated a better sensitivity in predicting pCR in LABC patients. Although both MRI and PETCT were equally accurate in detecting pCR of LABC patients to NAC, PETCT was more accurate in detecting pathological response of ALN to NAC.

Temporary Reactive Response of Axillary Lymph Nodes to COVID-19 Vaccination on 18F-rhPSMA-7.3 PET/CT in Patients with Prostate Cancer.

Vaccine-associated lymphadenopathy (VAL) is a common finding on 18F-FDG PET/CT examinations after coronavirus disease 2019 (COVID-19) vaccination. However, data regarding VAL on 18F-rhPSMA-7.3-ligand PET are currently lacking. This study assesses the prevalence, temporal response to vaccination, and characteristics of VAL. Methods: Two hundred thirty-three consecutive vaccinated and 41 unvaccinated patients with confirmed prostate cancer who underwent 18F-rhPSMA-7.3 PET/CT were retrospectively analyzed. Size and uptake of the axillary lymph nodes were measured. Ratios of SUVmax of ipsilateral to contralateral axillary lymph node (SUVratio) were determined. The characteristics of SUVratio in respect to the duration of PSMA avidity in the axillary lymph node after COVID-19 vaccination was analyzed. Results: The prevalence of VAL on 18F-rhPSMA-7.3 PET was 45%. Up to a period of 8 wk after the last COVID-19 vaccination, SUVratio was positive (2.05 ± 0.17). Thereafter, SUVratio dropped significantly (1.35 ± 0.09) and approached the value of unvaccinated group (1.1 ± 0.2). SUVratio of metastatic axillary lymph nodes was very high (>11) and can be easily detected visually or semiquantitatively. In 3 patients, we observed suspected development and consecutively confirmed involving metastasis of axillary lymph node with SUVratio between 4.0 to 6.6. Correlation between SUVratio and lymph node size (r = 0.93, P < 0.0001) and lymph node size and duration after vaccine (r = -0.88, P < 0.0008) was found. Conclusion: Increased uptake of the PSMA ligand 18F-rhPSMA-7.3 by axillary lymph nodes is common after COVID-19 vaccination and can persist for 8 wk. This finding should be considered in the interpretation of 18F-rhPSMA-7.3 PET/CT examinations.

Assessment of response of neoadjuvant chemotherapy in carcinoma breast patients by high-frequency ultrasound.

To assess the response of neoadjuvant chemotherapy in carcinoma breast patients by high-frequency ultrasound. The current single blind, observational study was conducted at rural tertiary healthcare center of Acharya Vinoba Bhave Rural Hospital from October 2018 to Sept 2020. We incorporated breast cancer patients with TNM stages IIIA and IIIB who received neoadjuvant chemotherapy with Cyclophosphamide/Adriamycin/5 FU and Paclitaxel respectively followed by standard surgical procedure modified radical mastectomy. Successive ultrasound examination of the breast malignancy and the axilla was done after 21 days of either of any neoadjuvant chemotherapy for 3 cycles. Assessment of response to neoadjuvant chemotherapy was applied in terms of reduction in the breast tumour volume on ultrasound and percentage of tumour response calculated by Response Evaluation Criteria for Solid Tumours (RECIST). Data were analysed using SPSS version 24.0. Higher frequency of patients was invasive ductal breast cancer. In our study, Paclitaxel group showed better response in terms of CR and PR than CAF group. Our study noticed a consistent decrement in tumour volume after every cycle of either CAF or Paclitaxel NACT. Axillary ultrasound was able to predict the response of axillary lymph nodes in terms of increase or decrease in number and morphological changes after 3 cycles of NACT with similarity on final histopathology. It can be concluded from the results of the present study that high-frequency ultrasound is appropriate tool for assessment of response of primary breast malignancy and lymphnode metastasis in the axilla after neoadjuvant chemotherapy.