Construction of a novel Chinese normal brain database using 18F-FDG PET images and MIMneuro software, the initial application in epilepsy

Characterisation of a novel [18F]FDG brain PET database and combination with a second database for optimising detection of focal abnormalities, using focal cortical dysplasia as an example

BACKGROUND

Brain [18F]FDG PET is used clinically mainly in the presurgical evaluation for epilepsy surgery and in the differential diagnosis of neurodegenerative disorders. While scans are usually interpreted visually on an individual basis, comparison against normative cohorts allows statistical assessment of abnormalities and potentially higher sensitivity for detecting abnormalities. Little work has been done on out-of-sample databases (acquired differently to the patient data). Combination of different databases would potentially allow better power and discrimination. We fully characterised an unpublished healthy control brain [18F]FDG PET database (Marseille, n = 60, ages 21-78 years) and compared it to another publicly available database (MRXFDG, n = 37, ages 23-65 years). We measured and then harmonised spatial resolution and global values. A collection of patient scans (n = 34, 13-48 years) with histologically confirmed focal cortical dysplasias (FCDs) obtained on three generations of scanners was used to estimate abnormality detection rates using standard software (statistical parametric mapping, SPM12).

RESULTS

Regional SUVs showed similar patterns, but global values and resolutions were different as expected. Detection rates for the FCDs were 50% for comparison with the Marseille database and 53% for MRXFDG. Simply combining both databases worsened the detection rate to 41%. After harmonisation of spatial resolution, using a full factorial design matrix to accommodate global differences, and leaving out controls older than 60 years, we achieved detection rates of up to 71% for both databases combined. Detection rates were similar across the three scanner types used for patients, and high for patients whose MRI had been normal (n = 10/11).

CONCLUSIONS

As expected, global and regional data characteristics are database specific. However, our work shows the value of increasing database size and suggests ways in which database differences can be overcome. This may inform analysis via traditional statistics or machine learning, and clinical implementation.

Nuclear imaging for localization and surgical outcome prediction in epilepsy: A review of latest discoveries and future perspectives

Background

Epilepsy is one of the most common neurological disorders. Approximately, one-third of patients with epilepsy have seizures refractory to antiepileptic drugs and further require surgical removal of the epileptogenic region. In the last decade, there have been many recent developments in radiopharmaceuticals, novel image analysis techniques, and new software for an epileptogenic zone (EZ) localization.

Objectives

Recently, we provided the latest discoveries, current challenges, and future perspectives in the field of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) in epilepsy.

Methods

We searched for relevant articles published in MEDLINE and CENTRAL from July 2012 to July 2022. A systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis was conducted using the keywords "Epilepsy" and "PET or SPECT." We included both prospective and retrospective studies. Studies with preclinical subjects or not focusing on EZ localization or surgical outcome prediction using recently developed PET radiopharmaceuticals, novel image analysis techniques, and new software were excluded from the review. The remaining 162 articles were reviewed.

Results

We first present recent findings and developments in PET radiopharmaceuticals. Second, we present novel image analysis techniques and new software in the last decade for EZ localization. Finally, we summarize the overall findings and discuss future perspectives in the field of PET and SPECT in epilepsy.

Conclusion

Combining new radiopharmaceutical development, new indications, new techniques, and software improves EZ localization and provides a better understanding of epilepsy. These have proven not to only predict prognosis but also to improve the outcome of epilepsy surgery.

CERMEP-IDB-MRXFDG: a database of 37 normal adult human brain [18F]FDG PET, T1 and FLAIR MRI, and CT images available for research

We present a database of cerebral PET FDG and anatomical MRI for 37 normal adult human subjects (CERMEP-IDB-MRXFDG). Thirty-nine participants underwent static [18F]FDG PET/CT and MRI, resulting in [18F]FDG PET, T1 MPRAGE MRI, FLAIR MRI, and CT images. Two participants were excluded after visual quality control. We describe the acquisition parameters, the image processing pipeline and provide participants' individual demographics (mean age 38 ± 11.5 years, range 23-65, 20 women). Volumetric analysis of the 37 T1 MRIs showed results in line with the literature. A leave-one-out assessment of the 37 FDG images using Statistical Parametric Mapping (SPM) yielded a low number of false positives after exclusion of artefacts. The database is stored in three different formats, following the BIDS common specification: (1) DICOM (data not processed), (2) NIFTI (multimodal images coregistered to PET subject space), (3) NIFTI normalized (images normalized to MNI space). Bona fide researchers can request access to the database via a short form.

18F-THK 5351 and 11C-PiB PET of the Thai normal brain template

Objectives

The aim of the study was to create a local normal database brain template of Thai individuals for ¹¹C-Pittsburgh compound B (¹¹C-PiB) and ¹⁸F-THK 5351 depositions using statistical parametric mapping (SPM) software, and to validate and optimize the established specific brain template for use in clinical practice with a highly reliability and reproducibility.

Methods

This prospective study was conducted in 24 healthy right-handed volunteers (13 men, 11 women; aged: 42-79 years) who underwent ¹⁸F-THK 5351 and ¹¹C-PiB PET/CT scans. SPM was used for the ¹⁸F-THK 5351 and ¹¹C-PiB PET/CT image analysis. All PET images were processed individually using Diffusion Tensor Image -Magnetic Resonance Imaging-weighted images (DTI-MRI images), which involved: (1) conversion of Digital Imaging and Communications in Medicine (DICOM) files into an analyzable file extension (.NIFTI) for statistical parametric mapping, (2) setting of the origin (the anterior commissure was used as the anatomical landmark), (3) re-alignment, (4) co-registration of PET with B0 (T1W) and DTI-MRI images, (5) normalization, and (6) normal verification using the Thai MRI standard. We then compared the normal PET template with the abnormal deposition area of different dementia syndromes, including Alzheimer's disease and progressive supranuclear palsy.

Results

This method was able to differentiate cognitively normal from Alzheimer's disease and progressive supranuclear palsy subjects.

Conclusions

This normal brain template was able to be integrated into clinical practice and research using PET analyses at our center.

Epileptogenic zone localization using a new automatic quantitative analysis based on normal brain glucose metabolism database

OBJECTIVES

To assess the clinical value of voxel-based automatic quantitative analysis using a normal brain glucose metabolism database in the preoperative localization of focal intractable temporal lobe epilepsy patients.

METHODS

Patients with refractory temporal lobe epilepsy who underwent 18F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) imaging were retrospectively enrolled from January to June 2017. Visual analysis was performed by two nuclear medicine radiologists, and the automatic quantitative analysis was carried out using MIMneuro software based the age- and gender-stratified normal brain glucose metabolism database. Setting postoperative outcomes as reference, the consistency between visual analysis and automatic quantitative analysis was tested by Cohen's kappa coefficient, and differences in localization of epileptic foci of the two methods were compared by Chi-square test.

RESULTS

A total of 32 patients intractable temporal lobe epilepsy were included in this study. There was a moderate agreement between the automatic quantitative analysis based on MIMneuro software and visual analysis (kappa coefficient = 0.472, p = 0.002). In terms of the efficiency of focus localization, the voxel-based automatic quantitative analysis was higher than that of visual analysis (Chi-square value = 6.969, p = 0.008).

CONCLUSIONS

The voxel-based automatic quantitative analysis combined with normal brain glucose metabolism database had a certain clinical application value for detection temporal lobe epilepsy.