Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography.
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ABSTRACT:
SUBMITTER: Fernandes J
PROVIDER: S-EPMC6586920 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Pathological response of breast cancer to chemotherapy is a prognostic indicator for long-term disease free and overall survival. Responses of locally advanced breast cancer in the neoadjuvant chemotherapy (NAC) settings are often variable, and the prediction of response is imperfect. The purpose of this study was to detect primary tumor responses early after the start of neoadjuvant chemotherapy using quantitative ultrasound (QUS), textural analysis and molecular features in patients with locally advanced breast cancer.The study included ninety six patients treated with neoadjuvant chemotherapy. Breast tumors were scanned with a clinical ultrasound system prior to chemotherapy treatment, during the first, fourth and eighth week of treatment, and prior to surgery. Quantitative ultrasound parameters and scatterer-based features were calculated from ultrasound radio frequency (RF) data within tumor regions of interest. Additionally, texture features were extracted from QUS parametric maps. Prior to therapy, all patients underwent a core needle biopsy and histological subtypes and biomarker ER, PR, and HER2 status were determined. Patients were classified into three treatment response groups based on combination of clinical and pathological analyses: complete responders (CR), partial responders (PR), and non-responders (NR). Response classifications from QUS parameters, receptors status and pathological were compared. Discriminant analysis was performed on extracted parameters using a support vector machine classifier to categorize subjects into CR, PR, and NR groups at all scan times.Of the 96 patients, the number of CR, PR and NR patients were 21, 52, and 23, respectively. The best prediction of treatment response was achieved with the combination mean QUS values, texture and molecular features with accuracies of 78%, 86% and 83% at weeks 1, 4, and 8, after treatment respectively. Mean QUS parameters or clinical receptors status alone predicted the three response groups with accuracies less than 60% at all scan time points. Recurrence free survival (RFS) of response groups determined based on combined features followed similar trend as determined based on clinical and pathology.This work demonstrates the potential of using QUS, texture and molecular features for predicting the response of primary breast tumors to chemotherapy early, and guiding the treatment planning of refractory patients.
| S-EPMC5751990 | biostudies-literature
Project description:BackgroundNeoadjuvant chemotherapy (NAC) is used in patients with breast cancer to reduce tumor focus, metastatic risk, and patient mortality. Monitoring NAC effects is necessary to capture resistant patients and stop or change treatment. The existing methods for evaluating NAC results have some limitations. The aim of this study was to assess the tumor response at an early stage, after the first doses of the NAC, based on the variability of the backscattered ultrasound energy, and backscatter statistics. The backscatter statistics has not previously been used to monitor NAC effects.MethodsThe B-mode ultrasound images and raw radio frequency data from breast tumors were obtained using an ultrasound scanner before chemotherapy and 1 week after each NAC cycle. The study included twenty-four malignant breast cancers diagnosed in sixteen patients and qualified for neoadjuvant treatment before surgery. The shape parameter of the homodyned K distribution and integrated backscatter, along with the tumor size in the longest dimension, were determined based on ultrasound data and used as markers for NAC response. Cancer tumors were assigned to responding and non-responding groups, according to histopathological evaluation, which was a reference in assessing the utility of markers. Statistical analysis was performed to rate the ability of markers to predict the final NAC response based on data obtained after subsequent therapeutic doses.ResultsStatistically significant differences (p<0.05) between groups were obtained after 2, 3, 4, and 5 doses of NAC for quantitative ultrasound markers and after 5 doses for the assessment based on maximum tumor dimension. Statistical analysis showed that, after the second and third NAC courses the classification based on integrated backscatter marker was characterized by an AUC of 0.69 and 0.82, respectively. The introduction of the second quantitative marker describing the statistical properties of scattering increased the corresponding AUC values to 0.82 and 0.91.ConclusionsQuantitative ultrasound information can characterize the tumor's pathological response better and at an earlier stage of therapy than the assessment of the reduction of its dimensions. The introduction of statistical parameters of ultrasonic backscatter to monitor the effects of chemotherapy can increase the effectiveness of monitoring and contribute to a better personalization of NAC therapy.
| S-EPMC6417657 | biostudies-literature
Project description:Anti-cancer therapies including chemotherapy aim to induce tumour cell death. Cell death introduces alterations in cell morphology and tissue micro-structures that cause measurable changes in tissue echogenicity. This study investigated the effectiveness of quantitative ultrasound (QUS) parametric imaging to characterize intra-tumour heterogeneity and monitor the pathological response of breast cancer to chemotherapy in a large cohort of patients (n?=?100). Results demonstrated that QUS imaging can non-invasively monitor pathological response and outcome of breast cancer patients to chemotherapy early following treatment initiation. Specifically, QUS biomarkers quantifying spatial heterogeneities in size, concentration and spacing of acoustic scatterers could predict treatment responses of patients with cross-validated accuracies of 82?±?0.7%, 86?±?0.7% and 85?±?0.9% and areas under the receiver operating characteristic (ROC) curve of 0.75?±?0.1, 0.80?±?0.1 and 0.89?±?0.1 at 1, 4 and 8 weeks after the start of treatment, respectively. The patients classified as responders and non-responders using QUS biomarkers demonstrated significantly different survivals, in good agreement with clinical and pathological endpoints. The results form a basis for using early predictive information on survival-linked patient response to facilitate adapting standard anti-cancer treatments on an individual patient basis.
| S-EPMC5583340 | biostudies-literature
Project description:Quantitative ultrasound (QUS) can probe tissue structure and analyze tumour characteristics. Using a 6-MHz ultrasound system, radiofrequency data were acquired from 56 locally advanced breast cancer patients prior to their neoadjuvant chemotherapy (NAC) and QUS texture features were computed from regions of interest in tumour cores and their margins as potential predictive and prognostic indicators. Breast tumour molecular features were also collected and used for analysis. A multiparametric QUS model was constructed, which demonstrated a response prediction accuracy of 88% and ability to predict patient 5-year survival rates (p = 0.01). QUS features demonstrated superior performance in comparison to molecular markers and the combination of QUS and molecular markers did not improve response prediction. This study demonstrates, for the first time, that non-invasive QUS features in the core and margin of breast tumours can indicate breast cancer response to neoadjuvant chemotherapy (NAC) and predict five-year recurrence-free survival.
| S-EPMC5388850 | biostudies-literature
Project description:To explore guidelines on the use of MRI and PET/CT monitoring primary tumor response to neoadjuvant chemotherapy (NAC), taking breast cancer subtype into account.In this prospective cohort study, 188 women were included with stages II and III breast cancer. MRI and 18F-FDG-PET/CT were acquired before and during NAC. Baseline pathology was assessed from tumor biopsy. Tumors were stratified into HER2-positive, ER-positive/HER2-negative (ER-positive), and ER-negative/PR-negative/HER2-negative (triple-negative) subtypes, and treated according to subtype. Primary endpoint was pathological complete response (pCRmic) defined as no or only small numbers of scattered invasive tumor cells. We evaluated imaging scenarios using MRI only, PET/CT only, and combinations.pCRmic was found in 35/46 (76.1%) of HER2-positive, 11/87 (12.6%) of ER-positive, and 31/55 (56.4%) of triple-negative tumors. For HER2-positive tumors, MRI yielded the strongest predictor (AUC: 0.735; sensitivity 36.2%), outperforming PET/CT (AUC: 0.543; p = 0.04), and with comparable results to combined imaging (AUC: 0.708; p = 0.213). In ER-positive tumors, the combination of MRI and PET/CT was slightly superior (AUC: 0.818; sensitivity 55.8%) over MRI alone (AUC: 0.742; p = 0.117) and PET/CT alone (AUC: 0.791). However, even though relatively large numbers of ER-positive tumor patients were included, no significant differences were yet found. For triple-negative tumors, MRI (AUC: 0.855; sensitivity 45.4%), PET/CT (AUC: 0.844; p = 0.220) and combined imaging (AUC: 0.868; p = 0.213) yielded comparable results.For HER2-positive tumors, MRI shows significant advantage over PET/CT. For triple-negative tumors, comparable results were seen for MRI, PET/CT and combined imaging. For ER-positive tumors, combining MRI with PET/CT may result in optimal response monitoring, although not yet significantly.
| S-EPMC5439668 | biostudies-other
Project description:Breast imaging techniques are used to assess the tumor response to neoadjuvant treatment (NAT), which is increasingly one of the preferred therapeutic options and increases the rate of breast conservation for breast cancer. Herein, we report a case in which a woman was diagnosed with invasive ductal carcinoma in the left breast and received NAT before surgery. Automated breast ultrasound (AB US) was regularly performed before and during the NAT to evaluate the tumor response to NAT by measuring diameter changes and volume reductions of the tumor. Images showed that the tumor size was significantly reduced and disappeared after 7 cycles of NAT, except for macrocalcification. Postoperative histopathological examination confirmed that there were no residual tumor cells. We found that AB US overcame the limitations of handheld US, such as operator dependence, poor reproducibility and limited field of view, and can be an alternative modality to assess the tumor response of NAT in the absence of magnetic resonance imaging (MRI) instruments.
| S-EPMC9411026 | biostudies-literature
Project description:Patients with large or nonoperable breast cancers often receive neoadjuvant chemotherapy to facilitate full resection of the tumor and enable conservation of the breast. However, currently available methods for evaluation of response during therapy are limited and the actual effect of the treatment is only recognized at surgery upon completion of chemotherapy. Timely assessment of response could allow individual tailoring of the treatment and save noneffective drugs and unnecessary toxicity. Here, we suggest that tumor derived DNA methylation in the serum may reflect changes in tumor burden and allow early recognition of responders versus nonresponders. In this pilot study, we collected 7 consecutive serum samples from 52 patients with locally advanced breast cancer during neoadjuvant chemotherapy. We selected RASSF1, which was methylated in more than 80% of the tumors, for serum analysis. Using the "methylation sensitive PCR and high resolution melting," we detected RASSF1 methylation in the serum of 21 patients prior to therapy. In four patients who achieved complete pathological response, RASSF1 methylation in the serum became undetectable early during therapy. In contrast, in 17 patients that had partial or minimal pathological response, serum RASSF1 methylation persisted longer or throughout the treatment (complete versus partial response p = 0.02). These findings support further development of this assay for monitoring response during neoadjuvant therapy.
| S-EPMC3904188 | biostudies-literature
Project description:BackgroundThe primary objective was to determine whether mid-treatment ultrasound measurements of index breast tumors and index axillary nodes of different cancer subtypes associate with residual cancer burden (RCB).MethodsPatients with invasive breast cancer who underwent neoadjuvant chemotherapy and had pre-treatment and mid-treatment breast and axillary ultrasound were included in this single-institution, retrospective cohort study. Linear regression analysis assessed associations between RCB with (a) change in index breast tumor size, (b) change in index node size, and (c) absolute number of abnormal nodes at mid-treatment. Multivariate linear regression was used to calculate best-fit models for RCB.ResultsOne hundred fifty-nine patients (68 triple negative breast cancer [TNBC], 45 hormone receptor [HR]+/human epidermal growth factor receptor 2 [HER2]-, and 46 HR-/HER2+) were included. Median age at diagnosis was 50 years, range 30-76. Median tumor size was 3.4 cm, range 0.9-10.4. Pathological complete response/RCB-I rates were 36.8% (25/68) for TNBC patients, 24.4% (11/45) for HR+/HER2- patients, and 71.7% (33/46) for HR-/HER2+ patients. Linear regression analyses demonstrated associations between percent change in tumor ultrasound measurements at mid-treatment with RCB index score in TNBC and HR+/HER2- (p < .05) but not in HR-/HER2+ (p > .05) tumors and an association between axillary ultrasound assessment of number of abnormal nodes at mid-treatment with RCB index score across all subtypes (p < .05).ConclusionPerformance characteristics of breast ultrasound associated with RCB vary by cancer subtype, whereas the performance characteristics of axillary ultrasound associated with RCB are consistent across cancer subtype. Breast and axillary ultrasound may be valuable in monitoring response to neoadjuvant therapy. The Oncologist 2017;22:394-401 IMPLICATIONS FOR PRACTICE: The differential performance characteristics of breast ultrasound by molecular subtype and the consistent performance characteristics of axillary ultrasound across molecular subtypes can have clinical utility in monitoring response to neoadjuvant therapy.
| S-EPMC5388386 | biostudies-literature
Project description:ObjectiveTo develop and validate a radiomics nomogram based on pre-treatment, early treatment ultrasound (US) radiomics features combined with clinical characteristics for early prediction of response to neoadjuvant chemotherapy (NAC) in breast cancer.MethodA total of 217 patients with histological results of breast cancer receiving four to eight cycles of NAC before surgery from January 2018 to December 2020 were enrolled. Patients from the study population were randomly separated into a training set (n = 152) and a validation set (n = 65) at a ratio of 7:3. A total of 788 radiomics features were extracted from each region of interest in the US image at pre-treatment baseline (radiomic signature, RS1), early treatment (after completion of two cycles of NAC, RS2) and delta radiomics (calculated between the pre-treatment and post-treatment features, Delta RS). The Max-Relevance and Min-Redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) regression were applied for feature selection. The predictive nomogram was built based on the radiomics signature combined with clinicopathological risk factors. Discrimination, calibration, and prediction performance were further evaluated in the validation set.ResultsOf the 217 breast masses, 127 (58.5%) were responsive to NAC and 90 (41.5%) were non-responsive. Following feature selection, nine features in RS1, 11 features in RS2, and eight features in Delta RS remained. With multivariate analysis, the RS1, RS2, Delta RS, and Ki-67 expression were independently associated with breast NAC response. However, the performance of the Delta RS (AUC Delta RS = 0.743) was not higher than RS1 (AUC RS1 = 0.722, PDelta vs RS1 = 0.086) and RS2 (AUC RS2 = 0.811, PDelta vs RS2 = 0.173) with the Delong test. The nomogram incorporating RS1, RS2, and Ki-67 expression showed better predictive ability for NAC response with an area under the curve (AUC) of 0.866 in validation cohorts than either the single RS1 (AUC 0.725) or RS2 (AUC 0.793) or Ki-67 (AUC 0.643).ConclusionThe nomogram incorporating pre-treatment and early-treatment US radiomics features and Ki-67 expression showed good performance in terms of NAC response in breast cancer, thereby providing valuable information for individual treatment and timely adjustment of chemotherapy regimens.
| S-EPMC8859469 | biostudies-literature
Project description:ObjectiveEarly assessment of response to neoadjuvant chemotherapy (NAC) for breast cancer allows therapy to be individualized. The optimal assessment method has not been established. We investigated the accuracy of automated breast ultrasound (ABUS) to predict pathological outcomes after NAC.MethodsA total of 290 breast cancer patients were eligible for this study. Tumor response after 2 cycles of chemotherapy was assessed using the product change of two largest perpendicular diameters (PC) or the longest diameter change (LDC). PC and LDC were analyzed on the axial and the coronal planes respectively. Receiver operating characteristic (ROC) curves were used to evaluate overall performance of the prediction methods. Youden's indexes were calculated to select the optimal cut-off value for each method. Sensitivity, specificity, positive and negative predictive values (PPV and NPV) and the area under the ROC curve (AUC) were calculated accordingly.ResultsypT0/is was achieved in 42 patients (14.5%) while ypT0 was achieved in 30 patients (10.3%) after NAC. All four prediction methods (PC on axial planes, LDC on axial planes, PC on coronal planes and LDC on coronal planes) displayed high AUCs (all>0.82), with the highest of 0.89 [95% confidence interval (95% CI), 0.83-0.95] when mid-treatment ABUS was used to predict final pathological complete remission (pCR). High sensitivities (85.7%-88.1%) were observed across all four prediction methods while high specificities (81.5%-85.1%) were observed in two methods used PC. The optimal cut-off values defined by our data replicate the WHO and the RECIST criteria. Lower AUCs were observed when mid-treatment ABUS was used to predict poor pathological outcomes.ConclusionsABUS is a useful tool in early evaluation of pCR after NAC while less reliable when predicting poor pathological outcomes.
| S-EPMC5101221 | biostudies-literature