Share：
Share this content in WeChat
X
[Chinese][PDF]3512
• Clinical Article •
Evaluation of magnetic resonance DWI-ADC value in assessing the early efficacy of neoadjuvant chemotherapy for conventional osteosarcoma
LI Yuzeng  MAIERHABA·Nuermaimaiti   XU Hui  ZHANG Shifeng 

Cite this article as: Li YZ, Maierhaba·NEMMT, Xu H, et al. Evaluation of magnetic resonance DWI-ADC value in assessing the early efficacy of neoadjuvant chemotherapy for conventional osteosarcoma[J]. Chin J Magn Reson Imaging, 2022, 13(11): 88-92, 136. DOI:10.12015/issn.1674-8034.2022.11.016.


[Abstract] Objective To investigate the value of different apparent diffusion coefficient (ADC) value of magnetic resonance diffusion-weighted imaging (DWI) and their rates of change in assessing the early efficacy of neoadjuvant chemotherapy for osteosarcoma.Materials and Methods Cases of twenty-three patients with osteosarcoma undergoing neoadjuvant chemotherapy (NAC) at the Affiliated Tumour Hospital of Xinjiang Medical University between January 2019 and March 2022 were collected, and conventional MRI and DWI were performed before NAC and after 4 cycles of chemotherapy to obtain different ADC value and its rate of change were obtained. Patients were divided into good histological response group and poor histological response group according to the pathological histological Huvos grading method of chemotherapy, and the statistical differences of different ADC value and their change rates between the two groups were compared.Results The differences in ADCmean, ADCmin, ADCmean/volume, ADCmin/volume before and after chemotherapy in the good histological response group were statistically significant, all P＜0.05 (P values were 0.024, <0.001, 0.018, 0.046, respectively). The differences in ADCmean, ADCmin, ADCmin/volume before and after chemotherapy were statistically significant in the poor histological response group, all P＜0.05 (P values were 0.005, <0.001, 0.020, respectively), while the differences in ADCmean/volume were not statistically significant (P=0.071, P＞0.05). The differences in the rates of change of ADCmean, ADCmin, ADCmean/volume, and ADCmin/volume between the two groups were statistically significant (P=0.047, 0.006, 0.039, 0.015, all P＜0.05). The area under the curve (AUC) of ADCmin rate of change by receiver operating characteristic (ROC) curve analysis was 0.938, which was higher than the rates of change of ADCmean, ADCmin/volume, and ADCmean/volume (0.783, 0.767, and 0.813, respectively).Conclusions Different ADC value and their rates of change are of great value in the early assessment of the efficacy of osteosarcoma, and the ADCmin rate of change has significant advantages in predicting the efficacy of osteosarcoma.
[Keywords] osteosarcoma；efficacy evaluation；neoadjuvant chemotherapy；area under the curve；apparent diffusion coefficient；diffusion weighted imaging；magnetic resonance imaging

LI Yuzeng   MAIERHABA·Nuermaimaiti    XU Hui*   ZHANG Shifeng  

Medical Imaging Center of Tumour Hospital Affiliated to Xinjiang Medical University, Urumqi 830011, China

Xu H, E-mail: simplehui2004@163.com

Conflicts of interest   None.

Received  2022-07-08
Accepted  2022-10-15
DOI: 10.12015/issn.1674-8034.2022.11.016
Cite this article as: Li YZ, Maierhaba·NEMMT, Xu H, et al. Evaluation of magnetic resonance DWI-ADC value in assessing the early efficacy of neoadjuvant chemotherapy for conventional osteosarcoma[J]. Chin J Magn Reson Imaging, 2022, 13(11): 88-92, 136. DOI:10.12015/issn.1674-8034.2022.11.016.

[1]
Zhao X, Wu Q, Gong X, et al. Osteosarcoma: a review of current and future therapeutic approaches[J/OL]. Biomedical engineering online, 2021, 20(1) [2022-06-16]. https://sci-hub.se/10.1186/s12938-021-00860-0. DOI: 10.1186/s12939-021-01451-0.
[2]
Zarkavelis G, Petrakis D, Fotopoulos G, et al. Bone and soft tissue sarcomas during pregnancy: a narrative review of the literature[J]. J Adv Res, 2016, 7(4): 581-587. DOI: 10.1016/j.jare.2016.01.003.
[3]
Belayneh R, Fourman M, Bhogai S, et al. Update on Osteosarcoma[J/OL]. Current oncology reports, 2021, 23(6) [2022-06-16]. https://sci-hub.se/10.1007/s11912-021-01053-7. DOI: 10.1007/s11912-021-01053-7.
[4]
Brookes MJ, Chan CD, Baljer B, et al. Surgical Advances in Osteosarcoma[J/OL]. Cancers, 2021, 13(3) [2022-06-16]. https://sci-hub.se/10.1007/s11912-021-01053-7. DOI: 10.3390/cancers13030388.
[5]
Amit P, Malhotra A, Kumar R, et al. Evaluation of static and dynamic MRI for assessing response of bone sarcomas to preoperative chemotherapy: correlation with histological necrosis[J]. Indian J Radiol Imaging, 2015, 25(3): 269-275. DOI: 10.4103/0971-3026.161452.
[6]
Zhang SP, Li X, Li H, et al. Significance of neoadjuvant chemotherapy (NACT) in limb salvage treatment of osteosarcoma and its effect on GLS1 expression[J]. Eur Rev Med Pharmacol Sci, 2018, 22(19): 6538-6544. DOI: 10.26355/eurrev_201810_16068.
[7]
Alsharief AN, Martinez-Rios C, Hopyan S, et al. Usefulness of diffusion-weighted MRI in the initial assessment of osseous sarcomas in children and adolescents[J]. Pediatr Radiol, 2019, 49(9): 1201-1208. DOI: 10.1007/s00247-019-04436-y.
[8]
Liang YS, Xu H, Guan YN. Analysis of the correlation between ADC value of diffusion weighted imaging and Ki-67 expression in non-Hodgkin lymphoma of head and neck[J]. J China Clin Med Imaging, 2020, 31(1): 6-10. DOI: 10.12117/jccmi.2020.01.002.
[9]
Song MN, Dong L, He H, et al. Value of syMRI and DWI quantitative parameters measured using different regions of interest method in differentiating benign and malignant breast lesions[J]. Chin J Magn Reson Imaging, 2022, 13(6): 17-22, 27. DOI: 10.12015/issn.1674-8034.2022.06.004.
[10]
Liu TF, Zang X, Li M, et al. Application of magnetic resonance diffusion-weighted imaging in prognostic evaluation of microwave ablation of hepatocellular carcinoma[J]. Chin J Magn Reson Imaging, 2022, 13(6): 112-116. DOI: 10.12015/issn.1674-8034.2022.06.022.
[11]
Chen K, She HL, Wu T, et al. Comparison of percentage changes in quantitative diffusion parameters for assessing pathological complete response to neoadjuvant therapy in locally advanced rectal cancer: a meta-analysis[J]. Abdom Radiol (NY), 2021, 46(3): 894-908. DOI: 10.1007/s00261-020-02770-6.
[12]
Yan B, Liang XF, Zhao TT, et al. Is the standard deviation of the apparent diffusion coefficient a potential tool for the preoperative prediction of tumor grade in endometrial cancer?[J]. Acta Radiol, 2020, 61(12): 1724-1732. DOI: 10.1177/0284185120915596.
[13]
Huvos AG, Rosen G, Marcove RC. Primary osteogenic sarcoma: pathologic aspects in 20 patients after treatment with chemotherapy en bloc resection, and prosthetic bone replacement[J]. Arch Pathol Lab Med, 1977, 101(1): 14-18.
[14]
Yu B, Zhang FF, Liu L, et al. The novel prognostic risk factor STC2 can regulate the occurrence and progression of osteosarcoma via the glycolytic pathway[J]. Biochem Biophys Res Commun, 2021, 554: 25-32. DOI: 10.1016/j.bbrc.2021.03.067.
[15]
Guenther L, Rowe R, Acharya P, et al. Response Evaluation Criteria in Solid Tumors (RECIST) following neoadjuvant chemotherapy in osteosarcoma[J/OL]. Pediatric blood & cancer, 2018, 65(4) [2022-06-18]. https://sci-hub.se/10.1002/pbc.26896. DOI: 10.1002/pbc.26896.
[16]
Blackledge M, Winfield J, Miah A, et al. Supervised Machine-Learning Enables Segmentation and Evaluation of Heterogeneous Post-treatment Changes in Multi-Parametric MRI of Soft-Tissue Sarcoma[J/OL]. Frontiers in oncology, 2019, 9(941) [2022-06-18]. https://sci-hub.se/10.3389/fonc.2019.00941. DOI: 10.3389/fonc.2019.00941.
[17]
Wang JF, Sun ML, Liu DW, et al. Correlation between apparent diffusion coefficient and histopathology subtypes of osteosarcoma after neoadjuvant chemotherapy[J]. Acta Radiol, 2017, 58(8): 971-976. DOI: 10.1177/0284185116678276.
[18]
Uhl M, Saueressig U, van Buiren M, et al. Osteosarcoma: preliminary results of in vivo assessment of tumor necrosis after chemotherapy with diffusion- and perfusion-weighted magnetic resonance imaging[J]. Invest Radiol, 2006, 41(8): 618-623. DOI: 10.1097/01.rli.0000225398.17315.68.
[19]
Li L, Chen WC, Yan ZX, et al. Comparative analysis of amide proton transfer MRI and diffusion-weighted imaging in assessing p53 and ki-67 expression of rectal adenocarcinoma[J]. J Magn Reson Imaging, 2020, 52(5): 1487-1496. DOI: 10.1002/jmri.27212.
[20]
Wan Q, Lei Q, Wang P, et al. Intravoxel incoherent motion diffusion-weighted imaging of lung cancer: comparison between turbo spin-echo and echo-planar imaging[J]. J Comput Assist Tomogr, 2020, 44(3): 334-340. DOI: 10.1097/RCT.0000000000001004.
[21]
Degnan A, Chung C, Shan A. Quantitative diffusion-weighted magnetic resonance imaging assessment of chemotherapy treatment response of pediatric osteosarcoma and Ewing sarcoma malignant bone tumors[J]. Clinical imaging, 2018, 47: 9-13. DOI: 10.1016/j.clinimag.2017.08.003.
[22]
Khoo MM, Tyler PA, Saifuddin A, et al. Diffusion-weighted imaging (DWI) in musculoskeletal MRI: a critical review[J]. Skeletal Radiol, 2011, 40(6): 665-681. DOI: 10.1007/s00256-011-1106-6.
[23]
Nishie A, Kakihara D, Asayama Y, et al. Apparent diffusion coefficient: an associative factor for recurrence after nephrectomy in localized renal cell carcinoma[J]. J Magn Reson Imaging, 2016, 43(1): 166-172. DOI: 10.1002/jmri.24984.
[24]
de Piano F, Buscarino V, Maresca D, et al. Do DWI and quantitative DCE perfusion MR have a prognostic value in high-grade serous ovarian cancer?[J]. Radiol Med, 2019, 124(12): 1315-1323. DOI: 10.1007/s11547-019-01075-z.
[25]
Ren H, Qiu JF, Huang LX, et al. Application value of diffusion weighted imaging in early evaluation of neoadjuvant chemotherapy for Osteosarcoma[J]. Radiol Pract, 2021, 36(1): 42-46. DOI: 10.13609/j.cnki.1000-0313.2021.01.009.
[26]
Oka K, Yakushiji T, Sato H, et al. The value of diffusion-weighted imaging for monitoring the chemotherapeutic response of osteosarcoma: a comparison between average apparent diffusion coefficient and minimum apparent diffusion coefficient[J]. Skeletal Radiol, 2010, 39(2): 141-146. DOI: 10.1007/s00256-009-0830-7.
[27]
Ma H, Li K, Li ZH, et al. Value of diffusion-weighted imaging for assessment of response to neoadjuvant chemotherapy in osteosarcoma[J]. Chin J Cancer Prev Treat, 2016, 23(16): 1095-1098. DOI: 10.16073/j.cnki.cjcpt.2016.16.012.
[28]
Wang Z, Liu L, Song YX, et al. Application of apparent diffusion coefficient combined with serum tumor markers detection in evaluating neoadjuvant chemotherapy for osteosarcoma[J]. Natl Med J China, 2020, 100(13): 1012-1016. DOI: 10.3760/cma.j.cn112137-20190722-01625.
[29]
Bajpai J, Gamnagatti S, Kumar R, et al. Role of MRI in osteosarcoma for evaluation and prediction of chemotherapy response: correlation with histological necrosis[J]. Pediatr Radiol, 2011, 41(4): 441-450. DOI: 10.1007/s00247-010-1876-3.
[30]
Delli Pizzi A, Cianci R, Genovesi D, et al. Performance of diffusion-weighted magnetic resonance imaging at 3.0 T for early assessment of tumor response in locally advanced rectal cancer treated with preoperative chemoradiation therapy[J]. Abdom Radiol (NY), 2018, 43(9): 2221-2230. DOI: 10.1007/s00261-018-1457-8.

PREV MRI radiomics models in rectal cancer to predict pathological complete response of nCRT: Evaluation of different approaches
NEXT Immediate brain effect of pushing Qiaogong point intervention on stage Ⅰ essential hypertension based on rs-fMRI
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn