Noninvasive Monitoring of Murine Tumor Blood Flow During and After Photodynamic Therapy Provides Early Assessment of Therapeutic Efficacy

Department of Physics and Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
Clinical Cancer Research (Impact Factor: 8.72). 05/2005; 11(9):3543-52. DOI: 10.1158/1078-0432.CCR-04-2582
Source: PubMed


To monitor tumor blood flow noninvasively during photodynamic therapy (PDT) and to correlate flow responses with therapeutic efficacy.
Diffuse correlation spectroscopy (DCS) was used to measure blood flow continuously in radiation-induced fibrosarcoma murine tumors during Photofrin (5 mg/kg)/PDT (75 mW/cm2, 135 J/cm2). Relative blood flow (rBF; i.e., normalized to preillumination values) was compared with tumor perfusion as determined by power Doppler ultrasound and was correlated with treatment durability, defined as the time of tumor growth to a volume of 400 mm3. Broadband diffuse reflectance spectroscopy concurrently quantified tumor hemoglobin oxygen saturation (SO2).
DCS and power Doppler ultrasound measured similar flow decreases in animals treated with identical protocols. DCS measurement of rBF during PDT revealed a series of PDT-induced peaks and declines dominated by an initial steep increase (average +/- SE: 168.1 +/- 39.5%) and subsequent decrease (59.2 +/- 29.1%). The duration (interval time; range, 2.2-15.6 minutes) and slope (flow reduction rate; range, 4.4 -45.8% minute(-1)) of the decrease correlated significantly (P = 0.0001 and 0.0002, r2= 0.79 and 0.67, respectively) with treatment durability. A positive, significant (P = 0.016, r2= 0.50) association between interval time and time-to-400 mm3 was also detected in animals with depressed pre-PDT blood flow due to hydralazine administration. At 3 hours after PDT, rBF and SO2 were predictive (P < or = 0.015) of treatment durability.
These data suggest a role for DCS in real-time monitoring of PDT vascular response as an indicator of treatment efficacy.

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    • "Intuitively, the random flow model might be considered the best model with which to fit DCS data. In practice, however, it has been observed that the diffusion model fits the autocorrelation curves rather well over a broad range of tissue types [6], [7], [10], [13], [15], [16], [19]–[21], [27]–[33]. For the case of diffusive motion, <Δr 2 (τ )> = 6D B τ , where D B is the effective Brownian diffusion coefficient of scatterers. "
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