Journal of Biomedical Optics
Thayer School of Engineering
Common methods to characterize treatment efficacy based on morphological imaging may misrepresent outcomes and exclude effective therapies. Using a three-dimensional model of ovarian cancer, two functional treatment response metrics are used to evaluate photodynamic therapy (PDT) efficacy: total volume, calculated from viable and nonviable cells, and live volume, calculated from viable cells. The utility of these volume-based metrics is corroborated using independent reporters of photodynamic activity: viability, a common fluorescence-based ratiometric analysis, and photosensitizer photobleaching, which is characterized by a loss of fluorescence due in part to the production of reactive species during PDT. Live volume correlated with both photobleaching and viability, suggesting that it was a better reporter of PDT efficacy than total volume, which did not correlate with either metric. Based on these findings, live volume and viability are used to probe the susceptibilities of tumor populations to a range of PDT dose parameters administered using 0.25, 1, and 10 μM benzoporphyrin derivative (BPD). PDT with 0.25 μM BPD produces the most significant reduction in live volume and viability and mediates a substantial shift toward small nodules. Increasingly sophisticated bioengineered models may complement current treatment planning approaches and provide unique opportunities to critically evaluate key parameters including metrics of therapeutic response.
Anbil S, Rizvi I, Celli JP, Alagic N, Pogue BW, Hasan T. Impact of treatment response metrics on photodynamic therapy planning and outcomes in a three-dimensional model of ovarian cancer. J Biomed Opt. 2013 Sep;18(9):098004. doi: 10.1117/1.JBO.18.9.098004. PMID: 24802230; PMCID: PMC3783041.
Dartmouth Digital Commons Citation
Anbil, Sriram; Rizvi, Imran; Celli, Jonathan P.; Alagic, Nermina; Pogue, Brian W.; and Tayyaba Hasan, "Impact of Treatment Response Metrics on Photodynamic Therapy Planning and Outcomes in a Three-Dimensional Model of Ovarian Cancer" (2013). Dartmouth Scholarship. 3736.