Voxel based comparison and texture analysis of 18F-FDG and 18F-FMISO PET of patients with head-and-neck cancer

Abstract

Background Hypoxia can induce radiation resistance and is an independent prognostic marker for outcome in head and neck cancer. As 18 F-FMISO (FMISO), a hypoxia tracer for PET, is far less common than 18 F-FDG (FDG) and two separate PET scans result in doubled cost and radiation exposure to the patient, we aimed to predict hypoxia from FDG PET with new techniques of voxel based analysis and texture analysis. Methods Thirty-eight patients with head-and-neck cancer underwent consecutive FDG and FMISO PET scans before any treatment. ROIs enclosing the primary cancer were compared in a voxel-by-voxel manner between FDG and FMISO PET. Tumour hypoxia was defined as the volume with a tumour-to-muscle ratio (TMR) > 1.25 in the FMISO PET and hypermetabolic volume was defined as >50% SUVmax in the FDG PET. The concordance rate was defined as percentage of voxels within the tumour which were both hypermetabolic and hypoxic. 38 different texture analysis (TA) parameters were computed based on the ROIs and correlated with presence of hypoxia. Results Within the hypoxic tumour regions, the FDG uptake was twice as high as in the non-hypoxic tumour regions (SUVmean 10.9 vs. 5.4; p<0.001). A moderate correlation between FDG and FMISO uptake was found by a voxel-by-voxel comparison (r = 0.664 p<0.001). The average concordance rate was 25% (± 22%). Entropy was the TA parameter showing the highest correlation with hypoxia (r = 0.524 p<0.001). Conclusion FDG uptake was higher in hypoxic tumour regions than in non-hypoxic regions as expected by tumour biology. A moderate correlation between FDG and FMISO PET was found by voxel-based analysis. TA yielded similar results in FDG and FMISO PET. However, it may not be possible to predict tumour hypoxia even with the help of texture analysis.

Spatial heterogeneity of radiolabeled choline positron emission tomography in tumors of patients with non-small cell lung cancer: first-in-patient evaluation of [18F]fluoromethyl-(1,2-2H4)-choline

“…The most widely used radiotracer for tumor imaging is [ 18 F]fluorodeoxyglucose ([ 18 F]FDG) which measures glucose utilization. [ 18 F]FDG does not overlap with hypoxia measured by [ 18 F]FMISO PET at the global or voxel level 15 .…”

Correlation between histogram-based DCE-MRI parameters and 18F-FDG PET values in oropharyngeal squamous cell carcinoma: Evaluation in primary tumors and metastatic nodes

“…Previous studies have focused on the correlation between perfusion and metabolic imaging in HNSCC, using DCE-MRI and 18 F-FDG PET or 18 F-FMISO (fluoromisonidazole) PET [19][20][21][22][23][24][25][26][27][28], as well as with simultaneous PET/MR systems [21,23,32,36]. However, most of these studies investigated perfusion and metabolic parameters in the PT [19][20][21]23,24,26], while only a few investigations have evaluated the metastatic LNs [25,27,28], reporting conflicting results.…”

“…Several investigations have already focused on the relationships between DCE-MRI and 18 F-FDG-PET/computed tomography (CT) parameters, even though these results are conflicting in HN tumors [19][20][21][22][23][24][25]. Most of the previous studies on DCE-MRI and/ or PET/CT have only evaluated primary tumors [19][20][21]23,24,26], while only a small number of investigations also included the metastatic lymph nodes (LNs) [25,[27][28]. Furthermore, limited research has addressed vascular heterogeneity within the lesion, using a histogrambased approach instead of the mean values of parameters, to better reveal the relationships between perfusion and metabolic variables [19,22].…”

Preoperative Texture Analysis Using 11C-Methionine Positron Emission Tomography Predicts Survival after Surgery for Glioma

“…Metabolic tumor volume (MTV) and total lesion methionine uptake (TLMU) were quantified as previously described [ 3 ], with MTV defined as the volume of the tumor boundary and TLMU defined as the product of the MTV and the SUVmean within the boundary. All image analyses were performed using the Metavol open source tool [ 3 , 9 ], and we resampled 64 discrete values from the lowest to the highest SUV values, which is a common method used in TA [ 10 , 11 ]. The PTexture package was used to calculate 36 texture features within the tumor boundary, as described by Orlhac et al [ 10 , 12 ].…”