AI Article Synopsis

  • - The study aimed to develop a better method for predicting pubic arch interference (PAI) in prostate cancer patients undergoing permanent brachytherapy by analyzing MRI results from 40 patients.
  • - Researchers measured different parameters, including prostate volume and specific angles and heights related to PAI, using receiver operating characteristic (ROC) curve analysis to determine predictive accuracy.
  • - The results indicated that certain parameters, particularly the angle and height of PAI, were effective in predicting PAI, with the angle of PAI at the pubic symphysis level being highlighted as a reliable predictor.

Article Abstract

Purpose: The aim of this study was to establish a more reliable method to predict pubic arch interference (PAI) before permanent prostate brachytherapy.

Material And Methods: We retrospectively analyzed the nuclear magnetic resonance imaging (MRI) results of forty patients with prostate cancer, who were treated with permanent implantation of I seeds (permanent brachytherapy). We measured and calculated six parameters based on the MRI results: 1. The prostate volume (PV); 2. The angle of the pubic arch (AoPA); 3. The angle of PAI (AoPAI, pubic symphysis level); 4. The height of PAI (hPAI, pubic symphysis level); 5. The maximum angle of PAI (AoPAI); 6. The maximum height of PAI (hPAI). We then tested which parameters could accurately predict PAI through receiver operating characteristic (ROC) curve analysis.

Results: The results of this study demonstrated that AoPAI, hPAI, hPAI, and AoPAI could predict PAI. Out of forty cases in our research, 10 cases were with PAI and 30 cases without PAI during the operation. The areas under the ROC curve for PV, AoPA, AoPAI (pubic symphysis level), hPAI (pubic symphysis level), AoPAI, and hPAI were 0.592, 0.567, 0.957, 0.940, 0.927, and 0.877, respectively. The AoPAI (pubic symphysis level), hPAI (pubic symphysis level), AoPAI, and hPAI were statistically correlated with PAI. The boundary values were 26.32°, 1.13 cm, 28.37°, and 1.51 cm, respectively.

Conclusions: This new method derived from MRI has predictive value, as AoPAI, hPAI, hPAI, and AoPAI could predict PAI. Taking other factors into consideration, we suggest the use of AoPAI as a novel and very reliable predictor of PAI.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6251442PMC
http://dx.doi.org/10.5114/jcb.2018.79247DOI Listing

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