PET/MRI for Oncologic Brain Imaging: A Comparison of Standard MR-Based Attenuation Corrections with a Model-Based Approach for the Siemens mMR PET/MR System

• Published in: Journal of Nuclear Medicine Vol. 58; no. 9; pp. 1519 - 1525
• Main Authors: Rausch, Ivo, Rischka, Lucas, Ladefoged, Claes N., Furtner, Julia, Fenchel, Matthias, Hahn, Andreas, Lanzenberger, Rupert, Mayerhoefer, Marius E., Traub-Weidinger, Tatjana, Beyer, Thomas
• Format: Journal Article
• Language: English
• Published: United States 01.09.2017
• Subjects: Brain - diagnostic imaging; Brain Neoplasms - diagnostic imaging; Humans; Image Processing, Computer-Assisted - methods; Image Processing, Computer-Assisted - standards; Magnetic Resonance Imaging; Multimodal Imaging; Organometallic Compounds; Positron-Emission Tomography; Retrospective Studies; Tyrosine - analogs & derivatives; PET/MRI; brain tumor imaging; quantification; attenuation correction
• ISSN: 0161-5505; 2159-662X; 1535-5667
• DOI: 10.2967/jnumed.116.186148

The aim of this study was to compare attenuation-correction (AC) approaches for PET/MRI in clinical neurooncology. Forty-nine PET/MRI brain scans were included: brain tumor studies using F-fluoro-ethyl-tyrosine ( F-FET) ( = 31) and Ga-DOTANOC ( = 7) and studies of healthy subjects using F-FDG ( = 11). For each subject, MR-based AC maps (MR-AC) were acquired using the standard DIXON- and ultrashort echo time (UTE)-based approaches. A third MR-AC was calculated using a model-based, postprocessing approach to account for bone attenuation values (BD, noncommercial prototype software by Siemens Healthcare). As a reference, AC maps were derived from patient-specific CT images (CTref). PET data were reconstructed using standard settings after AC with all 4 AC methods. We report changes in diagnosis for all brain tumor patients and the following relative differences values (RDs [%]), with regards to AC-CTref: for F-FET (A)-SUVs as well as volumes of interest (VOIs) defined by a 70% threshold of all segmented lesions and lesion-to-background ratios; for Ga-DOTANOC (B)-SUVs as well as VOIs defined by a 50% threshold for all lesions and the pituitary gland; and for F-FDG (C)-RD of SUVs of the whole brain and 10 anatomic regions segmented on MR images. For brain tumor imaging (A and B), the standard PET-based diagnosis was not affected by any of the 3 MR-AC methods. For A, the average RDs of SUV were -10%, -4%, and -3% and of the VOIs 1%, 2%, and 7% for DIXON, UTE, and BD, respectively. Lesion-to-background ratios for all MR-AC methods were similar to that of CTref. For B, average RDs of SUV were -11%, -11%, and -3% and of the VOIs 1%, -4%, and -3%, respectively. In the case of F-FDG PET/MRI (C), RDs for the whole brain were -11%, -8%, and -5% for DIXON, UTE, and BD, respectively. The diagnostic reading of PET/MR patients with brain tumors did not change with the chosen AC method. Quantitative accuracy of SUVs was clinically acceptable for UTE- and BD-AC for group A, whereas for group B BD was in accordance with CTref. Nevertheless, for the quantification of individual lesions large deviations to CTref can be observed independent of the MR-AC method used.