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Monitoring Response to Neoadjuvant Chemotherapy of Primary Osteosarcoma Using Diffusion Kurtosis Magnetic Resonance Imaging: Initial Findings

  • Chenglei Liu (Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital) ;
  • Yan Xi (Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital) ;
  • Mei Li (Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital) ;
  • Qiong Jiao (Department of Pathology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital) ;
  • Huizhen Zhang (Department of Pathology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital) ;
  • Qingcheng Yang (Department of Orthopedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital) ;
  • Weiwu Yao (Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital)
  • Received : 2018.07.17
  • Accepted : 2018.11.11
  • Published : 2019.05.01

Abstract

Objective: To determine whether diffusion kurtosis imaging (DKI) is effective in monitoring tumor response to neoadjuvant chemotherapy in patients with osteosarcoma. Materials and Methods: Twenty-nine osteosarcoma patients (20 men and 9 women; mean age, 17.6 ± 7.8 years) who had undergone magnetic resonance imaging (MRI) and DKI before and after neoadjuvant chemotherapy were included. Tumor volume, apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), and change ratio (ΔX) between pre-and post-treatment were calculated. Based on histologic response, the patients were divided into those with good response (≥ 90% necrosis, n = 12) and those with poor response (< 90% necrosis, n = 17). Several MRI parameters between the groups were compared using Student's t test. The correlation between image indexes and tumor necrosis was determined using Pearson's correlation, and diagnostic performance was compared using receiver operating characteristic curves. Results: In good responders, MDpost, ADCpost, and MKpost values were significantly higher than in poor responders (p < 0.001, p < 0.001, and p = 0.042, respectively). The ΔMD and ΔADC were also significantly higher in good responders than in poor responders (p < 0.001 and p = 0.01, respectively). However, no significant difference was observed in ΔMK (p = 0.092). MDpost and ΔMD showed high correlations with tumor necrosis rate (r = 0.669 and r = 0.622, respectively), and MDpost had higher diagnostic performance than ADCpost (p = 0.037) and MKpost (p = 0.011). Similarly, ΔMD also showed higher diagnostic performance than ΔADC (p = 0.033) and ΔMK (p = 0.037). Conclusion: MD is a promising biomarker for monitoring tumor response to preoperative chemotherapy in patients with osteosarcoma.

Keywords

Acknowledgement

The manuscript had been edited by American Journal Experts.

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