Computer aided prognosis for cell death categorization and prediction in vivo using quantitative ultrasound and machine learning techniques

Abstract

The technology developed in this study addresses a gap in the current standard of care by introducing a quality control step that generates potentially actionable metrics needed to enhance treatment decision-making. The study establishes a noninvasive framework for quantifying levels of cancer treatment response developed preclinically in tumors using QUS imaging in conjunction with machine learning techniques. The framework can potentially facilitate the detection of refractory responses in patients to a certain cancer treatment early on in the course of therapy to enable switching to more efficacious treatments.

Quantitative ultrasound radiomics for therapy response monitoring in patients with locally advanced breast cancer: Multi-institutional study results

“…QUS spectral parameters were acquired from the normalized, frequency-dependent power spectrum of the RF data. A sliding window analysis was performed on a pixel by pixel basis within the ROI with a window size of 2 x 2 mm 2 to include approximately 10 ultrasound wavelengths and overlap in both the lateral and axial direction of 92% [23,26,29,30].…”

Quantitative Ultrasound Spectroscopy for Differentiation of Hepatocellular Carcinoma from At-Risk and Normal Liver Parenchyma

“…QUS parameters have been demonstrated to be sensitive to subtle microstructural characteristics and alterations occurring in tissue due to biological responses and tissue morphology resulting from disease or treatment. These have been previously demonstrated in preclinical studies (14,27,(28)(29)(30) and in a clinical setting including patients with prostate cancer [disease detection (31), and extent of the disease (17)], as well as colorectal, gastric, and breast cancer patients to detect lymph node metastases (12,32). Furthermore, QUS can be used in clinic to evaluate cancer treatment response and help clinicians adapt cancer therapies and exchange ineffective treatment therapies at an early stage (12,25,26,33).…”

“…One of these techniques is quantitative ultrasound spectroscopy (QUS), which was first promulgated by Lizzi and colleagues in the early 1980s (13). QUS can provide quantitative information related to tissue characteristics using standard ultrasound systems (12), and allows differentiation of tissue microstructures by analyzing the radiofrequency (RF) signals backscattered from biological tissues (14). It is independent of instrument settings through a signal normalization process that uses a reference phantom with known backscatter and attenuation coefficients (12,(15)(16)(17).…”

Advances in low-frequency ultrasound combined with microbubbles in targeted tumor therapy

“…Endogenous apoptosis is a mitochondrial-activated apoptosis process regulated by the Bcl-2 protein family. It is reported that low-frequency ultrasound combined with microbubbles can promote apoptosis of prostate cancer cells, liver cancer cells, ovarian cancer cells, glioma cells, and human leukemia cells (Lagneaux et al, 2002;Bai et al, 2016;Gangeh et al, 2016), and reduce damage to normal tissues. Hou et al (2017) reported that low-frequency ultrasound combined with microbubbles can affect the hypoxic response of a tumor, inhibit tumor growth, and promote cell apoptosis.…”