Diffusion-weighted MRI for monitoring tumor response to photodynamic therapy

Hesheng Wang, Baowei Fei

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Purpose: To examine diffusion-weighted MRI (DW-MRI) for assessing the early tumor response to photodynamic therapy (PDT). Materials and Methods: Subcutaneous tumor xenografts of human prostate cancer cells (CWR22) were initiated in athymic nude mice. A second-generation photosensitizer, Pc 4, was delivered to each animal by a tail vein injection 48 h before laser illumination. A dedicated high-field (9.4 Tesla) small animal MR scanner was used to acquire diffusion-weighted MR images pre-PDT and 24 h after the treatment. DW-MRI and apparent diffusion coefficients (ADC) were analyzed for 24 treated and 5 control mice with photosensitizer only or laser light only. Tumor size, prostate specific antigen (PSA) level, and tumor histology were obtained at different time points to examine the treatment effect. Results: Treated mice showed significant tumor size shrinkage and decrease of PSA level within 7 days after the treatment. The average ADC of the 24 treated tumors increased 24 h after PDT (P < 0.001) comparing with pre-PDT. The average ADC was 0.511 ± 0.119 X 10 -3 mm 2/s pre-PDT and 0.754 ± 0.181 x 10 -3 mm 2/s 24 h after the PDT. There is no significant difference in ADC values pre-PDT and 24 h after PDT in the control tumors (P = 0.20). Conclusion: The change of tumor ADC values measured by DW-MRI may provide a noninvasive imaging marker for monitoring tumor response to Pc 4-PDT as early as 24 h.

Original languageEnglish (US)
Pages (from-to)409-417
Number of pages9
JournalJournal of Magnetic Resonance Imaging
Volume32
Issue number2
DOIs
StatePublished - Aug 2010
Externally publishedYes

Keywords

  • Apparent diffusion coefficients (ADC)
  • Diffusion-weighted MRI
  • Efficacy assessment
  • Photodynamic therapy
  • Prostate cancer
  • Treatment monitoring

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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