More accurate prediction of treatment response than mean apparent diffusion coefficient value in multiple myeloma using whole body MRI histogram analysis.
Qingyan QiHuazheng DongXiaodong JiKemin ZhangDehui ZouMu HaoShuhui DengWeiwei SuiZhiyi SongZhuo YuZhiwei ShenWenyang HuangShuang XiaPublished in: Future oncology (London, England) (2023)
Aim: To assess baseline histogram parameters from apparent diffusion coefficient (ADC) images in predicting early treatment response in newly diagnosed multiple myeloma (NDMM) patients. Methods: The histogram parameters of lesions in 68 NDMM patients were obtained with the Firevoxel software. The presence of deep response after two cycles of induction was recorded. Results: Some parameters were significantly different between the two groups, for example, ADC 75% in lumbar spine (p = 0.026). No significant difference in mean ADC for any anatomic site was found (all p > 0.05). The combination of ADC 75, ADC 90 and ADC 95% in lumbar spine; ADC skewness and ADC kurtosis in rib achieved a sensitivity of 100% in predicting deep response. Conclusion: Histogram analysis of ADC images can describe NDMM heterogeneity and accurately predict treatment response.
Keyphrases
- diffusion weighted imaging
- newly diagnosed
- contrast enhanced
- magnetic resonance imaging
- diffusion weighted
- end stage renal disease
- multiple myeloma
- ejection fraction
- chronic kidney disease
- prognostic factors
- computed tomography
- deep learning
- convolutional neural network
- patient reported outcomes
- optical coherence tomography
- mass spectrometry