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Background: Pre-treatment magnetic resonance imaging (MRI) can give patient-specific evaluation of suspected pathologically involved volumes in the seminal vesicles (SV) in prostate cancer patients. By targeting this suspicious volume we hypothesize that radiotherapy is more efficient without introducing more toxicity. In this study we evaluate the concept of using MRI-defined target volumes in terms of tumor control probability (TCP) and rectal normal tissue complication probability (NTCP).
Material And Methods: Twenty-one high-risk prostate cancer patients were included. Pre-treatment CT images, T2 weighted (T2w) MRI and two multi-parametric MRI were acquired. Overlap between a suspicious volume in the SV observed on T2w images and a suspicious volume observed on either multi-parametric MRI was assumed to reflect a true malignant region (named 'MRI positive'). In addition the entire SV on the CT-scan was delineated. Three treatment plans of 2 Gy ×39 fractions were generated per patient: one covering the MRI positive volume in SV and prostate with margin of 11 mm to the MRI positive in the SV and two plans covering prostate and SV using 11 and 7 mm SV margin, respectively. All plans were prescribed the same PTV mean dose. Rectal NTCP grade ≥2 was evaluated with the Lyman-Kutcher-Burman model and TCP was estimated by a logistic model using the combined MRI positive volume in SV and prostate as region-of-interest.
Results: Fourteen of twenty-one patients were classified as MRI positive, six of which had suspicious volumes in all three MRI modalities. On average TCP for the plan covering prostate and the MRI positive volume was 3% higher (up to 11%) than the two other plans which was statistically significant. The increased TCP was obtained without increasing rectal NTCP grade ≥2.
Conclusions: Using functional MRI for individualized target delineation in the SV may improve the treatment outcome in radiotherapy of prostate cancer without increasing the rectal toxicity.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5425627 | PMC |
http://dx.doi.org/10.1080/0284186X.2017.1300684 | DOI Listing |
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