Literature DB >> 28806574

Quantitative diffusion-weighted magnetic resonance imaging assessment of chemotherapy treatment response of pediatric osteosarcoma and Ewing sarcoma malignant bone tumors.

Andrew J Degnan1, Chul Y Chung2, Amisha J Shah3.   

Abstract

OBJECTIVE: Assessment of tumor response to chemotherapy is essential in managing malignant pediatric bone tumors prior to resection. SUBJECTS AND METHODS: Pre-chemotherapy and post-chemotherapy osteosarcoma and Ewing sarcoma cases (n=18) were analyzed with apparent diffusion coefficient (ADC) values measured by two readers.
RESULTS: Treated tumors demonstrated significantly greater ADC values compared to untreated tumors (p<0.001). Intraclass correlation coefficients ranged between 0.858 and 0.935. No significant tumor volume differences were observed. Regression analysis demonstrated average ADC as the best predictor of treatment.
CONCLUSIONS: Our study suggests that ADC values may be useful for evaluating chemotherapeutic response of malignant pediatric bone tumors.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Bone tumor; Chemotherapy response; Ewing sarcoma; Magnetic resonance imaging; Osteosarcoma; Quantitative diffusion-weighted imaging

Mesh:

Year:  2017        PMID: 28806574     DOI: 10.1016/j.clinimag.2017.08.003

Source DB:  PubMed          Journal:  Clin Imaging        ISSN: 0899-7071            Impact factor:   1.605


  14 in total

1.  Conventional MR and diffusion-weighted imaging of musculoskeletal soft tissue malignancy: correlation with histologic grading.

Authors:  Avneesh Chhabra; Oganes Ashikyan; Chenelle Slepicka; Nathan Dettori; Helena Hwang; Alexandra Callan; Rohit R Sharma; Yin Xi
Journal:  Eur Radiol       Date:  2018-12-03       Impact factor: 5.315

2.  CORR Insights®: Neoadjuvant Chemotherapy Followed by Delayed Surgery: Is it Necessary for All Patients With Nonmetastatic High-Grade Pelvic Osteosarcoma?

Authors:  Benjamin J Miller
Journal:  Clin Orthop Relat Res       Date:  2018-11       Impact factor: 4.176

Review 3.  Pediatric skeletal diffusion-weighted magnetic resonance imaging, part 2: current and emerging applications.

Authors:  Apeksha Chaturvedi
Journal:  Pediatr Radiol       Date:  2021-05-21

Review 4.  Radiomics: from qualitative to quantitative imaging.

Authors:  William Rogers; Sithin Thulasi Seetha; Turkey A G Refaee; Relinde I Y Lieverse; Renée W Y Granzier; Abdalla Ibrahim; Simon A Keek; Sebastian Sanduleanu; Sergey P Primakov; Manon P L Beuque; Damiënne Marcus; Alexander M A van der Wiel; Fadila Zerka; Cary J G Oberije; Janita E van Timmeren; Henry C Woodruff; Philippe Lambin
Journal:  Br J Radiol       Date:  2020-02-26       Impact factor: 3.039

5.  Multiparametric MRI with diffusion-weighted imaging in predicting response to chemotherapy in cases of osteosarcoma and Ewing's sarcoma.

Authors:  Mahmoud Mohamed Saleh; Tamer Moustafa Abdelrahman; Youusef Madney; Ghada Mohamed; Ahmed Mohammed Shokry; Amr Farouk Moustafa
Journal:  Br J Radiol       Date:  2020-10-15       Impact factor: 3.039

6.  Naringin targets Zeb1 to suppress osteosarcoma cell proliferation and metastasis.

Authors:  He Ming; Qiu Chuang; Wang Jiashi; Li Bin; Wang Guangbin; Ji Xianglu
Journal:  Aging (Albany NY)       Date:  2018-12-22       Impact factor: 5.682

7.  The relation of radiological tumor volume response to histological response and outcome in patients with localized Ewing Sarcoma.

Authors:  Lianne M Haveman; Andreas Ranft; Henk Vd Berg; Anne Smets; Jarmila Kruseova; Ruth Ladenstein; Benedicte Brichard; Michael Paulussen; Thomas Kuehne; Heribert Juergens; Stephanie Klco-Brosius; Uta Dirksen; Johannes H M Merks
Journal:  Cancer Med       Date:  2019-02-21       Impact factor: 4.452

8.  Development and Validation of Nomograms for Malignancy Prediction in Soft Tissue Tumors Using Magnetic Resonance Imaging Measurements.

Authors:  Ji Hyun Lee; Young Cheol Yoon; Wook Jin; Jang Gyu Cha; Seonwoo Kim
Journal:  Sci Rep       Date:  2019-03-20       Impact factor: 4.379

9.  Radiomics signature extracted from diffusion-weighted magnetic resonance imaging predicts outcomes in osteosarcoma.

Authors:  Shuliang Zhao; Yi Su; Jinghao Duan; Qingtao Qiu; Xingping Ge; Aijie Wang; Yong Yin
Journal:  J Bone Oncol       Date:  2019-10-04       Impact factor: 4.072

10.  Feasibility of multi-parametric magnetic resonance imaging combined with machine learning in the assessment of necrosis of osteosarcoma after neoadjuvant chemotherapy: a preliminary study.

Authors:  Bingsheng Huang; Jifei Wang; Meili Sun; Xin Chen; Danyang Xu; Zi-Ping Li; Jinting Ma; Shi-Ting Feng; Zhenhua Gao
Journal:  BMC Cancer       Date:  2020-04-15       Impact factor: 4.430

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