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

CONCLUSIONS: 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. PMID: 27908167 [PubMed - in process]
Source: Health Physics - Category: Physics Authors: Tags: Med Phys Source Type: research