More accurate prediction of treatment response than mean apparent diffusion coefficient value in multiple myeloma using whole body MRI histogram analysis

Author:

Qi Qingyan12,Dong Huazheng3ORCID,Ji Xiaodong4,Zhang Kemin5,Zou Dehui6,Hao Mu6,Deng Shuhui6,Sui Weiwei6,Song Zhiyi3,Yu Zhuo7,Shen Zhiwei8,Huang Wenyang6,Xia Shuang4ORCID

Affiliation:

1. The First Central Clinical School, Tianjin Medical University, Tianjin, China

2. Department of Radiology, Shanxi Eye Hospital, No. 100 Fu Dong Street, Taiyuan, Shanxi, China

3. Department of Radiology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, Tianjin, 300120, China

4. Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, 300192, China

5. Department of Radiology, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China

6. Department of lymphoma, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China

7. Department of Radiology, Tianjin Ninghe Hospital, Tianjin, China

8. Philips Healthcare (scientific research support), World Profit Centre, Chaoyang District, Beijing, 100020, China

Abstract

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.

Funder

National Key Technologies Research and Development Program of China

Natural Scientific Foundation of China

Publisher

Future Medicine Ltd

Subject

Cancer Research,Oncology,General Medicine

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