Literature DB >> 25341151

Diffusion-weighted imaging for head and neck squamous cell carcinoma: quantifying repeatability to understand early treatment-induced change.

Jenny K Hoang1, Kingshuk Roy Choudhury, Jim Chang, Oana I Craciunescu, David S Yoo, David M Brizel.   

Abstract

OBJECTIVE: The purpose of this study was to define baseline variability of apparent diffusion coefficient (ADC) on diffusion-weighted MR imaging (DWI) in patients with head and neck squamous cell carcinoma (HNSCC) and to compare it with early treatment-induced ADC change. SUBJECTS AND METHODS: Patients with American Joint Committee on Cancer stages III and IV HNSCC were imaged with two baseline DWI examinations 1 week apart and a third DWI examination during the 2nd week of curative-intent chemoradiation therapy. Mean ADC was measured in the primary tumor and largest lymph node for each patient on the three DWI scans. Mean baseline percentage differences (%∆ADC) were compared with intratreatment change. The repeatability coefficient for baseline %∆ADC was calculated and compared with intratreatment %∆ADC. Repeatability was also assessed with Bland-Altman plots and the intraclass correlation coefficient (ICC).
RESULTS: Sixteen patients underwent double baseline imaging, with 14 also undergoing intratreatment imaging. Baseline nodal disease ADC could be measured in 16 patients, but ADC in primary tumors could only be measured in five patients. The nodal mean (SD) baseline %∆ADC was 8% (± 7%), which was significantly different compared with intratreatment changes of 32% (± 31%) (p = 0.01). Baseline ICC was 0.86 for nodal disease and 0.99 for primary tumor (excellent correlation). The calculated repeatability coefficient for baseline nodal ADC was 15%. No patients had decreases in intratreatment ADC of more than 15%.
CONCLUSION: Baseline ADC variability for HNSCC is less than intratreatment ADC change for nodal disease. Assessment of response should consider intrinsic baseline variability.

Entities:  

Keywords:  diffusion-weighted imaging; early treatment change; functional imaging; head and neck cancer; repeatability

Mesh:

Year:  2014        PMID: 25341151     DOI: 10.2214/AJR.14.12838

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  18 in total

Review 1.  Potential Role of PET/MRI for Imaging Metastatic Lymph Nodes in Head and Neck Cancer.

Authors:  Sungheon Gene Kim; Kent Friedman; Sohil Patel; Mari Hagiwara
Journal:  AJR Am J Roentgenol       Date:  2016-05-10       Impact factor: 3.959

2.  Heterogeneity analysis of diffusion-weighted MRI for prediction and assessment of microstructural changes early after one cycle of induction chemotherapy in nasopharyngeal cancer patients.

Authors:  Manijeh Beigi; Anahita Fathi Kazerooni; Mojtaba Safari; Marzieh Alamolhoda; Mohsen Shojaee Moghdam; Shiva Moghadam; Hamidreza SalighehRad; Ahmad Ameri
Journal:  Radiol Med       Date:  2017-09-15       Impact factor: 3.469

Review 3.  Recent advances in MRI of the head and neck, skull base and cranial nerves: new and evolving sequences, analyses and clinical applications.

Authors:  Philip Touska; Steve E J Connor
Journal:  Br J Radiol       Date:  2019-09-24       Impact factor: 3.039

4.  Quantitative diffusion magnetic resonance imaging for prediction of human papillomavirus status in head and neck squamous-cell carcinoma: A systematic review and meta-analysis.

Authors:  Seyedmehdi Payabvash; Aimee Chan; Pejman Jabehdar Maralani; Ajay Malhotra
Journal:  Neuroradiol J       Date:  2019-05-14

5.  Extracranial Soft-Tissue Tumors: Repeatability of Apparent Diffusion Coefficient Estimates from Diffusion-weighted MR Imaging.

Authors:  Jessica M Winfield; Nina Tunariu; Mihaela Rata; Keiko Miyazaki; Neil P Jerome; Michael Germuska; Matthew D Blackledge; David J Collins; Johann S de Bono; Timothy A Yap; Nandita M deSouza; Simon J Doran; Dow-Mu Koh; Martin O Leach; Christina Messiou; Matthew R Orton
Journal:  Radiology       Date:  2017-03-16       Impact factor: 11.105

6.  Intravoxel Incoherent Motion Diffusion Weighted MR Imaging for Monitoring the Instantly Therapeutic Efficacy of Radiofrequency Ablation in Rabbit VX2 Tumors without Evident Links between Conventional Perfusion Weighted Images.

Authors:  Ziyi Guo; Qiang Zhang; Xiaoguang Li; Zhengyu Jing
Journal:  PLoS One       Date:  2015-05-28       Impact factor: 3.240

7.  Prognostic value of simultaneous 18F-FDG PET/MRI using a combination of metabolo-volumetric parameters and apparent diffusion coefficient in treated head and neck cancer.

Authors:  Yong-Il Kim; Gi Jeong Cheon; Seo Young Kang; Jin Chul Paeng; Keon Wook Kang; Dong Soo Lee; June-Key Chung
Journal:  EJNMMI Res       Date:  2018-01-10       Impact factor: 3.138

Review 8.  Diffusion magnetic resonance imaging: A molecular imaging tool caught between hope, hype and the real world of "personalized oncology".

Authors:  Abhishek Mahajan; Sneha S Deshpande; Meenakshi H Thakur
Journal:  World J Radiol       Date:  2017-06-28

9.  A data-driven statistical model that estimates measurement uncertainty improves interpretation of ADC reproducibility: a multi-site study of liver metastases.

Authors:  Ryan Pathak; Hossein Ragheb; Neil A Thacker; David M Morris; Houshang Amiri; Joost Kuijer; Nandita M deSouza; Arend Heerschap; Alan Jackson
Journal:  Sci Rep       Date:  2017-10-26       Impact factor: 4.379

Review 10.  Functional MRI for Treatment Evaluation in Patients with Head and Neck Squamous Cell Carcinoma: A Review of the Literature from a Radiologist Perspective.

Authors:  Roland P Nooij; Jan J Hof; Peter Jan van Laar; Anouk van der Hoorn
Journal:  Curr Radiol Rep       Date:  2018-01-22
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