Head-to-Head Comparison among Semi-Quantification Tools of Brain FDG-PET to Aid the Diagnosis of Prodromal Alzheimer's Disease

BACKGROUND

Several automatic tools have been implemented for semi-quantitative assessment of brain [18]F-FDG-PET.

OBJECTIVE

We aimed to head-to-head compare the diagnostic performance among three statistical parametric mapping (SPM)-based approaches, another voxel-based tool (i.e., PALZ), and a volumetric region of interest (VROI-SVM)-based approach, in distinguishing patients with prodromal Alzheimer's disease (pAD) from controls.

METHODS

Sixty-two pAD patients (MMSE score = 27.0±1.6) and one hundred-nine healthy subjects (CTR) (MMSE score = 29.2±1.2) were enrolled in five centers of the European Alzheimer's Disease Consortium. The three SPM-based methods, based on different rationales, included 1) a cluster identified through the correlation analysis between [18]F-FDG-PET and a verbal memory test (VROI-1), 2) a VROI derived from the comparison between pAD and CTR (VROI-2), and 3) visual analysis of individual maps obtained by the comparison between each subject and CTR (SPM-Maps). The VROI-SVM approach was based on 6 VROI plus 6 VROI asymmetry values derived from the pAD versus CTR comparison thanks to support vector machine (SVM).

RESULTS

The areas under the ROC curves between pAD and CTR were 0.84 for VROI-1, 0.83 for VROI-2, 0.79 for SPM maps, 0.87 for PALZ, and 0.95 for VROI-SVM. Pairwise comparisons of Youden index did not show statistically significant differences in diagnostic performance between VROI-1, VROI-2, SPM-Maps, and PALZ score whereas VROI-SVM performed significantly (p < 0.005) better than any of the other methods.

CONCLUSION

The study confirms the good accuracy of [18]F-FDG-PET in discriminating healthy subjects from pAD and highlights that a non-linear, automatic VROI classifier based on SVM performs better than the voxel-based methods.

Positron emission tomography study on pancreatic somatostatin receptors in normal and diabetic rats with 68Ga-DOTA-octreotide: a potential PET tracer for beta cell mass measurement. Biochem Biophys Res Commun. 2013;442:79-84. [PMID: 24220338 DOI: 10.1016/j.bbrc.2013.11.001]

Diabetes mellitus (DM) is a metabolic disorder characterized by hyperglycemia, and the loss or dysfunction of pancreatic beta cells has been reported before the appearance of clinical symptoms and hyperglycemia. To evaluate beta cell mass (BCM) for improving the detection and treatment of DM at earlier stages, we focused on somatostatin receptors that are highly expressed in the pancreatic beta cells, and developed a positron emission tomography (PET) probe derived from octreotide, a metabolically stable somatostatin analog. Octreotide was conjugated with 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA), a chelating agent, and labeled with (68)Gallium ((68)Ga). After intravenous injection of (68)Ga-DOTA-octreotide, a 90-min emission scan of the abdomen was performed in normal and DM model rats. The PET studies showed that (68)Ga-DOTA-octreotide radioactivity was highly accumulated in the pancreas of normal rats and that the pancreatic accumulation was significantly reduced in the rats administered with an excess amount of unlabeled octreotide or after treatment with streptozotocin, which was used for the chemical induction of DM in rats. These results were in good agreement with the ex vivo biodistribution data. These results indicated that the pancreatic accumulation of (68)Ga-DOTA-octreotide represented specific binding to the somatostatin receptors and reflected BCM. Therefore, PET imaging with (68)Ga-DOTA-octreotide could be a potential tool for evaluating BCM.