Response monitoring of breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound, texture, and molecular features

<div><p>Background</p><p>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.</p><p>Methods</p><p>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.</p><p>Results</p><p>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.</p><p>Conclusions</p><p>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.</p></div

Clinical and pathologic characteristics of LABC patients receiving neo-adjuvant chemotherapy.

<p>Clinical and pathologic characteristics of LABC patients receiving neo-adjuvant chemotherapy.</p

Features which exhibited significance differences between two response groups: CR <i>vs</i> PR, CR <i>vs</i> NR and PR <i>vs</i> NR.

<p>Features which exhibited significance differences between two response groups: CR <i>vs</i> PR, CR <i>vs</i> NR and PR <i>vs</i> NR.</p

Average changes in average acoustic concentration and corresponding texture parameters measured in ultimate clinical and pathological complete, partial and non-responders at times before and after the start of treatment.

<p>AAC, average acoustic concentration; CON, contrast; COR, correlation; ENE, energy; HOM, homogeneity; CR, complete responder; PR, partial responder; NR, non-responder.</p

Feature histograms obtained from week 8 data set over 10 iterations of classifications.

<p><b>In each iteration, best features were selected using sequential feature selection method and frequencies of occurrence of selected features over 10 iterations are presented.</b> MBF, mid-band fit; SS, spectral slope; SI, spectral intercept; SAS, spacing among scatterers; ASD, average scatterer diameter; ACE, attenuation co-efficient estimate; AAC, average acoustic concentration; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; CON, contrast; COR, correlation; ENE, energy; HOM, homogeneity; 0, parameter estimated prior to treatment.</p

Recurrence free survival curves for chemotherapy treatment response based on ultimate clinical-pathological assessment, and comparison to predicted recurrence free survival curves when based on quantitative ultrasound, texture parameters and molecular features acquired at weeks 1, 4, and 8 after treatment.

<p>CR, complete responder; PR, partial responder; NR, non-responder; QUS + Texture + Molecule, combination of mean QUS values, texture and molecular features.</p

PRISMA diagrams.

<p>PRISMA diagrams.</p