Non-Invasive Quantitative Imaging Informs Early Assessment of Cancer Therapeutic Response.

Imaging Biomarker;Treatment Response;Cancer;Biomedical Engineering;Engineering;Biomedical Engineering

Hoff, Benjamin A.Noll, Douglas C. ;

University of Michigan

关键词: Imaging Biomarker;    Treatment Response;    Cancer;    Biomedical Engineering;    Engineering;    Biomedical Engineering;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/102381/bahoff_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Therapeutic response assessment of cancer has long been facilitated by non-invasive imaging methods such as magnetic resonance imaging (MRI) and x-ray computed tomography (CT) in the clinic. Standards of patient care are designed around the most common cases, which may not always be efficacious. However, through evidence-based medicine there has begun a shift toward more individualized care. Standard clinical practice for cancer response assessment utilizes only volumetric change, measured prior and following the completion of therapy, providing no opportunity to adjust the treatment. In addition, novel targeted therapies, which may not result in a substantial decrease in tumor volume, are becoming more prevalent in the treatment of tumors. There is a clear need for non-invasive biomarkers that provide near real-time information on the anatomical and physiological makeup of the tumor post-treatment initiation. Tools for assessing early treatment response may allow physicians to dynamically optimize treatments individually, enhancing patient prognoses and avoiding unnecessary patient morbidity. In the following studies, I have evaluated various non-invasive imaging tools for early detection of treatment response in rodent models of disease. Tissue apparent diffusion coefficients (ADC) are known to correlate well with cellular status in cancer, and have shown promise in the detection of early tumor treatment response. Several different numerical models of higher-order diffusion signal attenuation were evaluated to determine their sensitivity to treatment response compared to the standard diffusion model. Dynamic contrast-enhanced (DCE-) MRI has shown sensitivity to vascular changes in cancer and was evaluated as an imaging biomarker of treatment response using a novel vascular-targeted therapy. Quantitative indices generated from DCE-MRI data were compared to diffusion (ADC) and volumetric MRI readouts for response assessment. The utility of imaging readouts from concurrent MRI, CT, bioluminescence, and fluorescence imaging was also evaluated in a model of bone metastasis. Further, a new voxel-based analytical technique, the parametric response map (PRM), was applied to CT images of metastatic bone disease and osteoporosis to evaluate bone response to treatment and hormone deprivation, respectively. Use of these tools may help improve the clinical effectiveness of cancer patient therapy as well as drug development and testing in preclinical models.