Apriori prediction of chemotherapy response in locally advanced breast cancer patients using CT imaging and deep learning: transformer versus transfer learning.

Objective: Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response to NAC for patients with Locally Advanced Breast Cancer (LABC) before treatment initiation could be beneficial to optimize therapy, ensuring the administration of effective treatments. The objective of the work here was to develop a predictive model to predict tumor response to NAC for LABC using deep learning networks and computed tomography (CT).

Quantitative US Delta Radiomics to Predict Radiation Response in Individuals with Head and Neck Squamous Cell Carcinoma.

Purpose To investigate the role of quantitative US (QUS) radiomics data obtained after the 1st week of radiation therapy (RT) in predicting treatment response in individuals with head and neck squamous cell carcinoma (HNSCC). Materials and Methods This prospective study included 55 participants (21 with complete response [median age, 65 years {IQR: 47-80 years}, 20 male, one female; and 34 with incomplete response [median age, 59 years {IQR: 39-79 years}, 33 male, one female) with bulky node-positive HNSCC treated with curative-intent RT from January 2015 to October 2019. All participants received 70 Gy of radiation in 33-35 fractions over 6-7 weeks.

A priori prediction of breast cancer response to neoadjuvant chemotherapy using quantitative ultrasound, texture derivative and molecular subtype.

The purpose of this study was to investigate the performances of the tumor response prediction prior to neoadjuvant chemotherapy based on quantitative ultrasound, tumour core-margin, texture derivative analyses, and molecular parameters in a large cohort of patients (n = 208) with locally advanced and earlier-stage breast cancer and combined them to best determine tumour responses with machine learning approach. Two multi-features response prediction algorithms using a k-nearest neighbour and support vector machine were developed with leave-one-out and hold-out cross-validation methods to evaluate the performance of the response prediction models. In a leave-one-out approach, the quantitative ultrasound-texture analysis based model attained good classification performance with 80% of accuracy and AUC of 0.

Noninvasive Evaluation of Breast Tumor Response to Combined Ultrasound-Stimulated Microbubbles and Hyperthermia Therapy Using Quantitative Ultrasound-Based Texture Analysis Method.

Objectives: Quantitative ultrasound (QUS) is a noninvasive imaging technique that can be used for assessing response to anticancer treatment. In the present study, tumor cell death response to the ultrasound-stimulated microbubbles (USMB) and hyperthermia (HT) treatment was monitored in vivo using QUS.

Methods: Human breast cancer cell lines (MDA-MB-231) were grown in mice and were treated with HT (10, 30, 50, and 60 minutes) alone, or in combination with USMB.

Implementation of Non-Invasive Quantitative Ultrasound in Clinical Cancer Imaging.

Quantitative ultrasound (QUS) is a non-invasive novel technique that allows treatment response monitoring. Studies have shown that QUS backscatter variables strongly correlate with changes observed microscopically. Increases in cell death result in significant alterations in ultrasound backscatter parameters.

Radiomics in predicting recurrence for patients with locally advanced breast cancer using quantitative ultrasound.

Background: The purpose of the study was to investigate the role of pre-treatment quantitative ultrasound (QUS)-radiomics in predicting recurrence for patients with locally advanced breast cancer (LABC).

Materials And Methods: A prospective study was conducted in patients with LABC ( = 83). Primary tumours were scanned using a clinical ultrasound device before starting treatment.

In vivo assessment of prostate cancer response using quantitative ultrasound characterization of ultrasonic scattering properties.

Background: The study here investigated quantitative ultrasound (QUS) parameters to assess tumour response to ultrasound-stimulated microbubbles (USMB) and hyperthermia (HT) treatment in vivo. Mice bearing prostate cancer xenografts were exposed to various treatment conditions including 1% (v/v) Definity microbubbles stimulated at ultrasound pressures 246 kPa and 570 kPa and HT duration of 0, 10, 40, and 50 min. Ultrasound radiofrequency (RF) data were collected using an ultrasound transducer with a central frequency of 25 MHz.

Quantitative ultrasound characterization of therapy response in prostate cancer in vivo.

Quantitative ultrasound (QUS) is a non-invasive imaging modality that permits the detection of tumor response following various cancer therapies. Based on ultrasound signal scattering from the biological system, scatterer size, and concentration of microscopic scatterers, QUS enables the rapid characterization of tumor cell death. In this study, tumor response to ultrasound-stimulated microbubbles (USMB) and hyperthermia (HT) in tumor-bearing mice, with prostate cancer xenografts (PC3), was examined using QUS.

Assessment of clinical radiosensitivity in patients with head-neck squamous cell carcinoma from pre-treatment quantitative ultrasound radiomics.

To investigate the role of quantitative ultrasound (QUS) radiomics to predict treatment response in patients with head and neck squamous cell carcinoma (HNSCC) treated with radical radiotherapy (RT). Five spectral parameters, 20 texture, and 80 texture-derivative features were extracted from the index lymph node before treatment. Response was assessed initially at 3 months with complete responders labelled as early responders (ER).

prediction of response in multicentre locally advanced breast cancer (LABC) patients using quantitative ultrasound and derivative texture methods.

Purpose: We develop a multi-centric response predictive model using QUS spectral parametric imaging and novel texture-derivate methods for determining tumour responses to neoadjuvant chemotherapy (NAC) prior to therapy initiation.

Materials And Methods: QUS Spectroscopy provided parametric images of mid-band-fit (MBF), spectral-slope (SS), spectral-intercept (SI), average-scatterer-diameter (ASD), and average-acoustic-concentration (AAC) in 78 patients with locally advanced breast cancer (LABC) undergoing NAC. Ultrasound radiofrequency data were collected from Sunnybrook Health Sciences Center (SHSC), University of Texas MD Anderson Cancer Center (MD-ACC), and St.

Comparison of methods for texture analysis of QUS parametric images in the characterization of breast lesions.

Purpose: Accurate and timely diagnosis of breast carcinoma is very crucial because of its high incidence and high morbidity. Screening can improve overall prognosis by detecting the disease early. Biopsy remains as the gold standard for pathological confirmation of malignancy and tumour grading.

Quantitative ultrasound radiomics using texture derivatives in prediction of treatment response to neo-adjuvant chemotherapy for locally advanced breast cancer.

Background: To investigate quantitative ultrasound (QUS) based higher-order texture derivatives in predicting the response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC).

Materials And Methods: 100 Patients with LABC were scanned before starting NAC. Five QUS parametric image-types were generated from radio-frequency data over the tumor volume.

Breast lesion characterization using Quantitative Ultrasound (QUS) and derivative texture methods.

Purpose: Accurate and timely diagnosis of breast cancer is extremely important because of its high incidence and high morbidity. Early diagnosis of breast cancer through screening can improve overall prognosis. Currently, biopsy remains as the gold standard for tumor pathological confirmation.

Intraocular Pressure-dependent Corneal Elasticity Measurement Using High-frequency Ultrasound.

Measurement of corneal biomechanical properties can aid in predicting corneal responses to diseases and surgeries. For delineation of spatially resolved distribution of corneal elasticity, high-resolution elastography system is required. In this study, we demonstrate a high-resolution elastography system using high-frequency ultrasound for ex-vivo measurement of intraocular pressure (IOP)-dependent corneal wave speed.

Shear wave arrival time estimates correlate with local speckle pattern.

We present simulation and phantom studies demonstrating a strong correlation between errors in shear wave arrival time estimates and the lateral position of the local speckle pattern in targets with fully developed speckle. We hypothesize that the observed arrival time variations are largely due to the underlying speckle pattern, and call the effect speckle bias. Arrival time estimation is a key step in quantitative shear wave elastography, performed by tracking tissue motion via cross-correlation of RF ultrasound echoes or similar methods.