Validation of quantitative magnetic resonance imaging techniques in head and neck healthy structures involved in the salivary and swallowing function: Accuracy and repeatability.
Phys Imaging Radiat Oncol
; 31: 100608, 2024 Jul.
Article
in En
| MEDLINE
| ID: mdl-39071157
ABSTRACT
Background and Purpose:
Radiation-induced damage to the organs at risk (OARs) in head-and-neck cancer (HNC) patient can result in long-term complications. Quantitative magnetic resonance imaging (qMRI) techniques such as diffusion-weighted imaging (DWI), DIXON for fat fraction (FF) estimation and T2 mapping could potentially provide a spatial assessment of such damage. The goal of this study is to validate these qMRI techniques in terms of accuracy in phantoms and repeatability in-vivo across a broad selection of healthy OARs in the HN region. Materials andMethods:
Scanning was performed at a 3 T diagnostic MRI scanner, including the calculation of apparent diffusion coefficient (ADC) from DWI, FF and T2 maps. Phantoms were scanned to estimate the qMRI techniques bias using Bland-Altman statistics. Twenty-six healthy subjects were scanned twice in a test-retest study to determine repeatability. Repeatability coefficients (RC) were calculated for the parotid, submandibular, sublingual and tubarial salivary glands, oral cavity, pharyngeal constrictor muscle and brainstem. Additionally, a linear mixed-effect model analysis was used to evaluate the effect of subject-specific characteristics on the qMRI values.Results:
Bias was 0.009x10-3 mm2/s for ADC, -0.7 % for FF and -7.9 ms for T2. RCs ranged 0.11-0.25x10-3 mm2/s for ADC, 1.2-6.3 % for FF and 2.5-6.3 ms for T2. A significant positive linear relationship between age and the FF and T2 for some of the OARs was found.Conclusion:
These qMRI techniques are feasible, accurate and repeatable, which is promising for treatment response monitoring and/or differentiating between healthy and unhealthy tissues due to radiation-induced damage in HNC patients.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Phys Imaging Radiat Oncol
Year:
2024
Document type:
Article
Affiliation country: