takenaka akinori

Background: In clinical practice, equivocal findings are inevitable in visual interpretation of whether amyloid positron emission tomography (PET) is positive or negative. It is therefore necessary to establish a more objective quantitative evaluation method for determining the indication for disease-modifying drugs currently under development. Aims: We aimed to determine cutoffs for positivity in quantitative analysis of 18F-flutemetamol PET in patients with cognitive impairment and suspected Alzheimer's disease (AD). We also evaluated the clinical efficacy of amyloid PET in the diagnosis of AD. This study was registered in the Japan Registry of Clinical Trials (jRCTs, 031180321). Methods: Ninety-three patients suspected of having AD underwent 18F-flutemetamol PET in seven institutions. A PET image for each patient was visually assessed and dichotomously rated as either amyloid-positive or amyloid-negative by two board-certified nuclear medicine physicians. If the two readers obtained different interpretations, the visual rating was rerun until they reached consensus. The PET images were quantitatively analyzed using the standardized uptake value ratio (SUVR) and standardized Centiloid (CL) scale with the whole cerebellum as a reference area. Results: Visual interpretation obtained 61 positive and 32 negative PET scans. Receiver operating characteristic analysis determined the best agreement of quantitative assessments and visual interpretation of PET scans to have an area under curve of 0.982 at an SUVR of 1.13 and a CL of 16. Using these cutoff values, there was high agreement between the two approaches (kappa = 0.88). Five discordant cases had SUVR and CL values ranging from 1.00 to 1.22 and from 1 to 26, respectively. In these discordant cases, either diffuse or mildly focal elevation of cortical activity confused visual interpretation. The amyloid PET outcome significantly altered the diagnosis of AD (χ2 = 51.3, p < 0.0001). PET imaging elevated the proportions of the very high likelihood category from 20.4 to 46.2% and the very low likelihood category from 0 to 22.6%. Conclusion: Quantitative analysis of amyloid PET using 18F-flutemetamol can objectively evaluate amyloid positivity using the determined cutoffs for SUVR and CL. Moreover, amyloid PET may have added value over the standard diagnostic workup in dementia patients with cognitive impairment and suspected AD.

OBJECTIVE: The objective of the present study was to develop a fully automated blood sampling system for kinetic analysis in mice positron emission tomography (PET) studies. Quantitative PET imaging requires radioactivity concentrations in arterial plasma to estimate the behavior of an administered radiopharmaceutical in target organs. Conventional manual blood sampling has several drawbacks, such as the need for troubleshooting in regard to blood collection, necessary personnel, and the radiation exposure dose. We recently developed and verified the operability of a fully automated blood sampling system (automatic blood dispensing system-ABDS). Here, we report the results of fully quantitative measurements of the cerebral metabolic rate of glucose (CMRglc) in mice using the ABDS. METHODS: Under 1% isoflurane anesthesia, a catheter was inserted into the femoral artery of nine wild-type male mice. Immediately after injection of 18F-fluorodeoxyglucose (FDG) (13.2 ± 3.93 MBq in 0.1 mL saline), arterial blood samples were drawn using the ABDS and then analyzed using CD-Well, a system we previously developed that can measure radioactivity concentration (Bq/μL) using a few microliters of blood in the plasma and whole blood separately. In total, 16 blood samplings were conducted in 60 min as follows: 10 s × 9; 70 s × 2; 120 s × 1; 250 s × 1; 10 min × 2; and 30 min × 1. Dynamic PET scans were conducted concurrently using a small-animal PET/computed tomography (CT) (PET/CT) scanner. Full kinetics modeling using a two-tissue-three-compartment model was applied to calculate CMRglc. Blood volume was also estimated. RESULTS: No significant differences were observed between the manual and ABDS measurements. A proportional error was detected only for plasma. The mean ± standard deviation CMRglc value in the mice was 5.43 ± 1.98 mg/100 g/min (30.2 ± 11 μmol/min/100 g), consistent with a previous report. CONCLUSIONS: The automated microliter-ordered blood sampling system developed in the present study appears to be useful for absolute quantification of CMRglc in mice PET studies.

Noncontrast computed tomography (NCCT) has been used for the detection of early ischemic change (EIC); however, correct interpretation of NCCT findings requires much clinical experience. This study aimed to assess the accuracy of time maximum intensity projection computed tomography technique (tMIP), which reflects the maximum value for the time phase direction from the dynamic volume data for each projected plane, for detection of EIC, against that of NCCT.Retrospective review of NCCT, cerebral blood volume in CT perfusion (CTP-CBV), and tMIP of 186 lesions from 280 regions evaluated by Alberta Stroke Program Early CT Score (ASPECTS) in 14 patients with acute middle cerebral artery stroke who had undergone whole-brain CTP using 320-row area detector CT was performed. Four radiologists reviewed EIC on NCCT, CTP-CBV, and tMIP in each ASPECTS region at onset using the continuous certainty factor method. Receiver operating characteristic analysis was performed to compare the relative performance for detection of EIC. The correlations were evaluated.tMIP-color showed the best discriminative value for detection of EIC. There were significant differences in the area under the curve for NCCT and tMIP-color, CTP-CBV (P < .05). Scatter plots of ASPECTS showed a positive significant correlation between NCCT, tMIP-gray, tMIP-color, and the follow-up study (NCCT, r = 0.32, P = .0166; tMIP-gray, r = 0.44, P = .0007; tMIP-color, r = 0.34, P = .0104).Because tMIP provides a high contrast parenchymal image with anatomical and vascular information in 1 sequential scan, it showed greater accuracy for detection of EIC and predicted the final infarct extent more accurately than NCCT based on ASPECTS.