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Prediction of Poor Responders to Neoadjuvant Chemotherapy in Patients with Osteosarcoma: Additive Value of Diffusion-Weighted MRI including Volumetric Analysis to Standard MRI at 3T. | LitMetric

AI Article Synopsis

  • The study aimed to assess how diffusion-weighted imaging (DWI) plus volumetric analysis enhances standard MRI in identifying poor responders to neoadjuvant chemotherapy in osteosarcoma patients treated at 3-Tesla.
  • Both standard MRI and DWI were analyzed in 17 patients, revealing notable statistical differences in various diffusion metrics between poor and good responders.
  • The incorporation of DWI significantly increased the sensitivity and specificity of response predictions, with the best models achieving a high area under the curve (AUC), demonstrating improved diagnostic accuracy.

Article Abstract

Objective: To evaluate the added value of diffusion weighted image (DWI) including volumetric analysis to standard magnetic resonance imaging (MRI) for predicting poor responders to neoadjuvant chemotherapy in patients with osteosarcoma at 3-Tesla.

Methods: 3-Tesla Standard MRI and DWI in 17 patients were reviewed by two independent readers. Standard MRI was reviewed using a five-level-confidence score. Two-dimensional (2D) apparent diffusion coefficient (ADC)mean and 2D ADCminimum were measured from a single-section region of interest. An ADC histogram derived from whole-tumor volume was generated including 3D ADCmean, 3D ADCskewness, and 3D ADCkurtosis. The Mann-Whitney-U test, receiver operating characteristic curve with area under the curve (AUC) analysis, and multivariate logistic regression analysis were performed.

Results: There were 13 poor responders and 4 good responders. Statistical differences were found in posttreatment and percent change of both 2D ADCmean and 2D ADCminimum, posttreatment 3D ADCmean, and posttreatment 3D ADCskewness between two groups. The best predictors of poor responders were posttreatment 2D ADCmean and posttreatment 3D ADCskewness. Sensitivity and specificity of the 1st model (standard MRI alone), 2nd model (standard MRI+posttreatment 2D ADCmean), and 3rd model (standard MRI+posttreatment 2D ADCmean+posttreatment 3D ADCskewness) were 85% and 25%, 85% and 75%, and 85% and 100% for reader 1 and 77% and 25%, 77% and 50%, and 85% and 100% for reader 2, respectively. The AUC of the 1st, 2nd, and 3rd models were 0.548, 0.798, and 0.923 for reader 1 and 0.510, 0.635, and 0.923 for reader 2, respectively.

Conclusion: The addition of DWI including volumetric analysis to standard MRI improves the diagnostic accuracy for predicting poor responders to neoadjuvant chemotherapy in patients with osteosarcoma at 3-Tesla.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7064235PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0229983PLOS

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