Dual-Energy Computed Tomography Virtual Noncalcium Imaging of Intracranial Arteries in Acute Ischemic Stroke: Differentiation Between Acute Thrombus and Calcification.

OBJECTIVE: Hyperdense artery sign (HAS) on noncontrast brain computed tomography (CT) indicates an acute thrombus within the cerebral artery. It is a valuable imaging biomarker for diagnosing large-vessel occlusion; however, its identification may be challenging with the presence of vascular calcification. Dual-energy CT virtual noncalcium (VNCa) imaging using a 3-material decomposition algorithm is helpful for differentiating between calcification and hemorrhage. This study aimed to clarify the potential of VNCa imaging for differentiating HAS from vascular calcification. METHODS: Patients with acute ischemic stroke and large-vessel occlusion identified on MR angiography, who also underwent noncontrast dual-energy CT, were included. The 80 kV/Sn 140 kV mixed images, with a weighting factor of 0.4, were considered 120 kVp-equivalent images. Postprocessing using a 3-material decomposition algorithm to differentiate between calcium (Ca), cerebrospinal fluid, and hemorrhage was performed via a commercially available 3-dimensional workstation. A mixed image, VNCa image, color-coded Ca image, and color-coded Ca image with VNCa image overlay (color-coded Ca-overlay image) were obtained, and axial reconstruction with a 1-mm slice thickness was performed for each image type. Two experienced neuroradiologists conducted imaging evaluations in consensus. RESULTS: Thirty-four patients (mean age, 76.0 years; 21 male and 13 female patients) were included. The mixed and VNCa images revealed an HAS (indicating an acute clot) corresponding to the large-vessel occlusion site in 30 patients. Among them, the VNCa and color-coded Ca-overlay images enabled clear differentiation between the acute thrombus and adjacent vessel wall calcification in 5 patients. Among the other 4 patients, the VNCa, Ca-overlay, and Ca images identified calcified cerebral emboli in the M1 segment in 1 patient. For the other 3 patients, no high attenuation corresponding to magnetic resonance angiography findings was observed in any of the mixed, VNCa, Ca-overlay, or Ca images. CONCLUSIONS: VNCa and color-coded Ca-overlay images obtained via dual-energy brain CT enabled differentiation of acute thrombus from vessel wall calcification and calcified cerebral emboli in patients with acute ischemic stroke.

Visualization of small brain nuclei with a high-spatial resolution, clinically available whole-body PET scanner.

OBJECTIVE: To verify the visibility of physiological 18F-fluorodeoxyglucose (18F-FDG) uptake in nuclei in and around the brainstem by a whole-body (WB) silicon photomultiplier positron emission tomography (SiPM-PET) scanner with point-spread function (PSF) reconstruction using various iteration numbers. METHODS: Ten healthy subjects (5 men, 5 women; mean age, 56.0 ± 5.0 years) who underwent 18F-FDG PET/CT using a WB SiPM-PET scanner and magnetic resonance imaging (MRI) of the brain including a spin-echo three-dimensional sampling perfection with application-optimized contrasts using different flip angle evolutions fluid-attenuated inversion recovery (3D-FLAIR) and a 3D-T1 magnetization-prepared rapid gradient-echo (T1-MPRAGE) images were enrolled. Each acquired PET image was reconstructed using ordered-subset expectation maximization (OSEM) with iteration numbers of 4, 16, 64, and 256 (subset 5 fixed) + time-of-flight (TOF) + PSF. The reconstructed PET images and 3D-FLAIR images for each subject were registered to individual T1-MPRAGE volumes using normalized mutual information criteria. For each MR-coregistered individual PET image, the pattern of FDG uptake in the inferior olivary nuclei (ION), dentate nuclei (DN), midbrain raphe nuclei (MRN), inferior colliculi (IC), mammillary bodies (MB), red nuclei (RN), subthalamic nuclei (STN), lateral geniculate nuclei (LGN), medial geniculate nuclei (MGN), and superior colliculi (SC) was visually classified into the following three categories: good, clearly distinguishable FDG accumulation; fair, obscure contour of FDG accumulation; poor, FDG accumulation indistinguishable from surrounding uptake. RESULTS: Among individual 18F-FDG PET images with OSEM iterations of 4, 16, 64, and 256 + TOF + PSF, the iteration numbers that showed the best visibility in each structure were as follows: ION, MRN, LGN, MGN, and SC, iteration 64; DN, iteration 16; IC, iterations 16, 64, and 256; MB, iterations 64 and 256; and RN and STN, iterations 16 and 64, respectively. Of the four iterations, the 18F-FDG PET image of iteration 64 visualized FDG accumulation in small structures in and around the brainstem most clearly (good, 98 structures; fair, 2 structures). CONCLUSIONS: A clinically available WB SiPM-PET scanner is useful for visualizing physiological FDG uptake in small brain nuclei, using a sufficiently high number of iterations for OSEM with TOF and PSF reconstructions.

Non-contrast dual-energy CT using X-map for acute ischemic stroke: region-specific comparison with simulated 120-kVp CT and diffusion-weighted MR images.

PURPOSE: X-map is a non-contrast dual-energy CT (DECT) application to identify acute ischemic stroke (AIS). Our aim was to verify region-specific characteristics of early ischemic changes (EIC) on X-map compared with simulated 120-kVp mixed-CT image and DWI. METHODS: Fifty AIS patients who underwent DECT and DWI were enrolled (mean age, 76 years; 34 men, 16 women). All datasets including mixed-CT image, X-map, and DWI were transformed into a standard brain atlas with 11 × 2 ROIs based on the ASPECTS + W system. ROIs with EIC on DWI, mixed-CT image, and X-map were defined as DWI-positive, mixed-CT-positive, and X-map-positive, and those with normal finding were DWI-negative, mixed-CT-negative, and X-map-negative respectively, in visual assessment by two neuroradiologists in consensus. RESULTS: EIC on X-maps were visually relevant to those on the other images: of 221 ROIs with mixed-CT-positive and X-map-positive, 198 (89.6%) were DWI-positive. X-map revealed moderate diagnostic accuracy for AIS compared with DWI in ROC curve analysis (AUC = 0.732). X-map identified EIC in deep white matter more sensitively than mixed-CT image: of 15 ROIs with mixed-CT-negative and X-map-positive in W segments, 14 (93.3%) were DWI-positive. X-map often showed EIC in cortical regions that were not detected on the other images: of 67 ROIs with mixed-CT-negative and X-map-positive in I and M1-M6 segments, 47 (70.1%) were DWI-negative. CONCLUSIONS: X-map is useful to detect EIC, especially in deep white matter, and may also provide additional information in acute ischemic lesions where DWI cannot be detected.

[Evaluation of Low-dose Whole-body FDG PET with SiPM-based PET/CT Scanner: Visual and Semi-quantitative Analyses Using Random Sampling from Full-dose Scan Data].

PURPOSE: Sensitivity and count rate performance of the latest PET/CT scanners with a silicon photomultiplier (SiPM) have been substantially improved compared to scanners with a photomultiplier tube (PMT), thereby promising a low-dose whole-body PET scan with maintaining image quality. However, it is ethically difficult to verify the low-dose protocol in actual clinical settings. In this study, we investigated the effect of dose reduction on reconstructed images by using a low-dose simulation technique, i.e., reducing the number of events from the acquired data. METHOD: For 21 subjects who underwent whole-body 18F-FDG PET examination with an SiPM-based PET/CT scanner, Biograph Vision (Siemens Healthineers, Erlangen, Germany), at a dosage of 3.5 MBq/kg and a continuous bed motion speed of 1.1 mm/sec (the standard protocol in our hospital), the number of events in acquired list data (100%; "full-dose") was reduced to 50%, 25%, 12.5%, and 6.25% ("low-dose"). The low-dose reconstructed images were evaluated visually and physically with reference to the full-dose images. The physical evaluation was performed by calculating differences in SUVmax at abnormal uptake (n=54) between the full-dose and low-dose images. RESULT: The 25% data images were visually acceptable, and the difference in SUVmax between the 100% and 25% data images was 9.8±13.5%. CONCLUSION: Our results suggest that Biograph Vision is a feasible method to reduce conventional dose with the potential use of 25% data images.

DeepPVC: prediction of a partial volume-corrected map for brain positron emission tomography studies via a deep convolutional neural network.

BACKGROUND: Partial volume correction with anatomical magnetic resonance (MR) images (MR-PVC) is useful for accurately quantifying tracer uptake on brain positron emission tomography (PET) images. However, MR segmentation processes for MR-PVC are time-consuming and prevent the widespread clinical use of MR-PVC. Here, we aimed to develop a deep learning model to directly predict PV-corrected maps from PET and MR images, ultimately improving the MR-PVC throughput. METHODS: We used MR T1-weighted and [11C]PiB PET images as input data from 192 participants from the Alzheimer's Disease Neuroimaging Initiative database. We calculated PV-corrected maps as the training target using the region-based voxel-wise PVC method. Two-dimensional U-Net model was trained and validated by sixfold cross-validation with the dataset from the 156 participants, and then tested using MR T1-weighted and [11C]PiB PET images from 36 participants acquired at sites other than the training dataset. We calculated the structural similarity index (SSIM) of the PV-corrected maps and intraclass correlation (ICC) of the PV-corrected standardized uptake value between the region-based voxel-wise (RBV) PVC and deepPVC as indicators for validation and testing. RESULTS: A high SSIM (0.884 ± 0.021) and ICC (0.921 ± 0.042) were observed in the validation and test data (SSIM, 0.876 ± 0.028; ICC, 0.894 ± 0.051). The computation time required to predict a PV-corrected map for a participant (48 s without a graphics processing unit) was much shorter than that for the RBV PVC and MR segmentation processes. CONCLUSION: These results suggest that the deepPVC model directly predicts PV-corrected maps from MR and PET images and improves the throughput of MR-PVC by skipping the MR segmentation processes.

Brain partial volume correction with point spreading function reconstruction in high-resolution digital PET: comparison with an MR-based method in FDG imaging.

OBJECTIVE: In quantitative positron emission tomography (PET) of the brain, partial volume effect due mainly to the finite spatial resolution of the PET scanner (> 3 mm full width at half maximum [FWHM]) is a primary source of error in the measurement of tracer uptake, especially in small structures such as the cerebral cortex (typically < 3 mm thickness). The aim of this study was to evaluate the partial volume correction (PVC) performance of point spread function-incorporated reconstruction (PSF reconstruction) in combination with the latest digital PET scanner. This evaluation was performed through direct comparisons with magnetic resonance imaging (MR)-based PVC (used as a reference method) in a human brain study. METHODS: Ten healthy subjects underwent brain 18F-FDG PET (30-min acquisition) on a digital PET/CT system (Siemens Biograph Vision, 3.5-mm FWHM scanner resolution at the center of the field of view) and anatomical T1-weighted MR imaging for MR-based PVC. PSF reconstruction was applied with a wide range of iterations (4 to 256; 5 subsets). FDG uptake in the cerebral cortex was evaluated using the standardized uptake value ratio (SUVR) and compared between PSF reconstruction and MR-based PVC. RESULTS: Cortical structures were visualized by PSF reconstruction with several tens of iterations and were anatomically well matched with the MR-derived cortical segments. Higher numbers of iterations resulted in higher cortical SUVRs, which approached those of MR-based PVC (1.76), although even with the maximum number of iterations they were still smaller by 16% (1.47), corresponding to approximately 1.5-mm FWHM of the effective spatial resolution. CONCLUSION: With the latest digital PET scanner, PSF reconstruction can be used as a PVC technique in brain PET, albeit with suboptimal resolution recovery. A relative advantage of PSF reconstruction is that it can be applied not only to cerebral cortical regions, but also to various small structures such as small brain nuclei that are hardly visualized on anatomical T1-weighted imaging, and thus hardly recovered by MR-based PVC.

Role of magnetic resonance vessel wall imaging in detecting and managing ruptured aneurysms among multiple intracranial aneurysms.

BACKGROUND: Wall enhancement of intracranial saccular aneurysms in high-resolution magnetic resonance vessel wall imaging (MR-VWI) might indicate a ruptured aneurysm. Therefore, this study aimed to determine the diagnostic ability of wall enhancement to detect the ruptured aneurysms among multiple aneurysms. METHODS: Patients with subarachnoid hemorrhage (SAH) and multiple intracranial aneurysms who underwent MR-VWI before craniotomy and clipping were included in the study. Three-dimensional T1-weighted fast spin-echo sequences were obtained before and after gadolinium injection. Aneurysm rupture was estimated based on the subarachnoid clot distribution, aneurysmal contours, and MR-VWI findings. We selectively performed surgical clipping and confirmed the rupture site intraoperatively. RESULTS: Thirteen patients with SAH with 13 ruptured and 17 unruptured aneurysms were treated at out facility. The accuracy rate of rupture site diagnosis using MR-VWI was 69.2% (9/13 cases). Each unruptured aneurysm was equally or more strongly enhanced in the other four cases than the ruptured aneurysms. In three of the four unruptured aneurysms with positive MR-VWI findings, atherosclerosis of the aneurysmal wall was observed during simultaneous or elective clipping surgery. Further, clipping surgery was performed without intraoperative rupture in two cases with the help of MR-VWI findings. CONCLUSION: Correct diagnosis of the rupture site using MR-VWI alone was unreliable due to false positives caused by the wall enhancement of unruptured aneurysms with atherosclerosis. Therefore, ruptured aneurysms should be detected using more information in addition to MR-VWI images. MR-VWI may be advantageous to determine surgical strategies when managing patients with SAH and multiple aneurysms.

Effect of hematocrit on cerebral blood flow measured by pseudo-continuous arterial spin labeling MRI: A comparative study with 15O-water positron emission tomography.

INTRODUCTION: In cerebral blood flow (CBF) quantification with pseudo-continuous arterial spin labeling (pCASL) MRI, arterial blood T1 (T1a) is usually fixed to a typical value (e.g., 1650 ms). However, individual T1a depends strongly on hematocrit (Hct) level. To investigate the utility of Hct-based T1a as an alternative to the fixed T1a method, we performed a comparative study with 15O-water positron emission tomography (PET). METHODS: For patients with unilateral occlusion or stenosis of major arteries, hemispheric CBF on the healthy side was measured using pCASL and 15O-water PET. The pCASL CBFs were calculated with both (a) fixed T1a (1650 ms) and (b) individual T1a estimated from blood-sampled Hct (Hct-based T1a). Correlation coefficients of Hct-CBF were calculated and compared between pCASL and PET. RESULTS: In pCASL, CBF with fixed T1a showed a strong negative correlation with Hct (r = -0.568), which was reduced with individual Hct-based T1a (r = -0.341 to -0.190), consistent with the Hct-CBF relation measured with PET (r = -0.349). DISCUSSION AND CONCLUSION: We demonstrated that Hct-based T1a resulted in smaller inter-individual variations in pCASL CBF and an inverse Hct-CBF relationship more similar to that of PET. Care must be taken in the interpretation of pCASL CBF imaging in relation to Hct level even in subjects without anemia. Further comparative studies are needed to investigate whether advanced techniques improve pCASL CBF quantification at the individual level.

Appropriate iMAR presets for metal artifact reduction from surgical clips and titanium burr hole covers on postoperative non-contrast brain CT.

PURPOSE: To evaluate suitable iterative metal artifact reduction (iMAR) presets for titanium neurosurgical clips and burr hole covers (BHCs) on postoperative non-contrast computed tomography (NCCT). METHOD: Twenty-two patients who underwent NCCT after intracranial aneurysmal clipping were included. NCCT images were postprocessed using eight currently available iMAR presets. In each image, a circular region of interest (ROI) was placed around clip, BHC, and on parietal lobe as reference. Standard deviation (SD) and attenuation value (HU) were measured in each ROI to obtain artifact index (AI) and contrast-to-noise ratio (CNR). For each iMAR preset, SD, AI, HU, and CNR were compared with those without iMAR for clips and BHCs. Visual assessment around each clip and BHC was performed by two neuroradiologists using three-point visual score (VS) (1 = no apparent, 2 = minor, and 3 = severe artifacts). RESULTS: Among the presets, the neuro-coils preset (iMAR-NC) showed the lowest SD, AI, and VS for clips (P < 0.001). For BHCs, HU, CNR, and VS with iMAR-NC were significantly higher than those without iMAR (P < 0.001). SD, AI, and VS with the shoulder implants preset (iMAR-ShI) were significantly lower than those without iMAR for clips (P = 0.002, 0.002, and P <  0.001, respectively). For BHCs, VS with iMAR-ShI was lowest among the presets (P = 0.004). CONCLUSIONS: Although iMAR-NC reduces metal artifacts from clips, it strengthens artifacts from BHCs. For postoperative NCCT, iMAR-ShI most effectively reduces metal artifacts from both clips and BHCs in a single preset.

Prediction of an oxygen extraction fraction map by convolutional neural network: validation of input data among MR and PET images.

PURPOSE: Oxygen extraction fraction (OEF) is a biomarker for the viability of brain tissue in ischemic stroke. However, acquisition of the OEF map using positron emission tomography (PET) with oxygen-15 gas is uncomfortable for patients because of the long fixation time, invasive arterial sampling, and radiation exposure. We aimed to predict the OEF map from magnetic resonance (MR) and PET images using a deep convolutional neural network (CNN) and to demonstrate which PET and MR images are optimal as inputs for the prediction of OEF maps. METHODS: Cerebral blood flow at rest (CBF) and during stress (sCBF), cerebral blood volume (CBV) maps acquired from oxygen-15 PET, and routine MR images (T1-, T2-, and T2*-weighted images) for 113 patients with steno-occlusive disease were learned with U-Net. MR and PET images acquired from the other 25 patients were used as test data. We compared the predicted OEF maps and intraclass correlation (ICC) with the real OEF values among combinations of MRI, CBF, CBV, and sCBF. RESULTS: Among the combinations of input images, OEF maps predicted by the model learned with MRI, CBF, CBV, and sCBF maps were the most similar to the real OEF maps (ICC: 0.597 ± 0.082). However, the contrast of predicted OEF maps was lower than that of real OEF maps. CONCLUSION: These results suggest that the deep CNN learned useful features from CBF, sCBF, CBV, and MR images and predict qualitatively realistic OEF maps. These findings suggest that the deep CNN model can shorten the fixation time for 15O PET by skipping 15O2 scans. Further training with a larger data set is required to predict accurate OEF maps quantitatively.

Iterative framework for image registration and partial volume correction in brain positron emission tomography.

Imprecise registration between positron emission tomography (PET) and anatomical magnetic resonance (MR) images is a critical source of error in MR imaging-guided partial volume correction (MR-PVC). Here, we propose a novel framework for image registration and partial volume correction, which we term PVC-optimized registration (PoR), to address imprecise registration. The PoR framework iterates PVC and registration between uncorrected PET and smoothed PV-corrected images to obtain precise registration. We applied PoR to the [11C]PiB PET data of 92 participants obtained from the Alzheimer's Disease Neuroimaging Initiative database and compared the registration results, PV-corrected standardized uptake value (SUV) and its ratio to the cerebellum (SUVR), and intra-region coefficient of variation (CoV) between PoR and conventional registration. Significant differences in registration of as much as 2.74 mm and 3.02° were observed between the two methods (effect size < - 0.8 or > 0.8), which resulted in considerable SUVR differences throughout the brain, reaching a maximal difference of 62.3% in the sensory motor cortex. Intra-region CoV was significantly reduced using the PoR throughout the brain. These results suggest that PoR reduces error as a result of imprecise registration in PVC and is a useful method for accurately quantifying the amyloid burden in PET.

Usefulness of deep learning-assisted identification of hyperdense MCA sign in acute ischemic stroke: comparison with readers' performance.

PURPOSE: To evaluate the usefulness of deep learning-assisted diagnosis for identifying hyperdense middle cerebral artery sign (HMCAS) on non-contrast computed tomography in comparison with the diagnostic performance of neuroradiologists. MATERIALS AND METHODS: We obtained 46 HMCAS-positive and 52 HMCAS-negative test samples extracted using 50-pixel-diameter circular regions of interest. Five neuroradiologists undertook an initial diagnostic performance test by describing the HMCAS-positive prediction rate in each sample. Their diagnostic performance was compared with that of a deep convolutional neural network (DCNN) model that had been trained using another dataset in our previous study. In the second test, readers could reference the prediction rate of the DCNN model in each sample. RESULTS: The diagnostic performance of the DCNN for HMCAS showed an accuracy of 81.6% and area under the receiver-operating characteristic curve (AUC) of 0.869, whereas the initial diagnostic performance of neuroradiologists showed an accuracy of 78.8% and AUC of 0.882. The second diagnostic test of neuroradiologists with reference to the results of the DCNN model showed an accuracy of 84.7% and AUC of 0.932. In all readers, AUC values were higher in the second test than the initial test. CONCLUSION: The ability of DCNN to identify HMCAS is comparable with the diagnostic performance of neuroradiologists.

[Evaluating Eye Lens Dose of Neurovascular and Cardiac Electrophysiology Interventional Physician].

PURPOSE: The International Commission on Radiological Protection recommended that interventional radiologies (IRs) have high radiation doses and that staff may also be exposed to high doses. In the present study, we measured the radiation exposure dose [3 mm dose equivalent, Hp (3) ] in the eye using an appropriate dosimeter placed next to the physician' s eye during neurovascular intervention procedure (Neuro-IR) and interventional cardiac electrophysiology procedure (EP-IR). METHOD: Physicians wore a direct eye dosemeter just lateral to the left eye and an additional direct eye dosemeter outside the radiation protective glasses close to their left eye. Additionally, a neck badge [0.07 mm dose equivalent, Hp (0.07) ] was worn outside the protective apron to the left of the neck, to compare the direct eye dosimeter estimated doses. The occupational eye lens dose was evaluated over a period of 6-month. RESULTS: The maximum Hp (3) of the Neuro-IR physician was estimated 5.1 mSv without the radiation protective glasses and 1.6 mSv with the radiation protective glasses. On the other hand, the maximum Hp (3) of the EP-IR physician was estimated 29 mSv without the radiation protective glasses and 15 mSv with the radiation protective glasses. CONCLUSION: Physicians eye lens dose [Hp (3) ] tended to be overestimated by the neck badge measurements [Hp (0.07)]. A correct evaluation of the lens dose [Hp (3) ] using the direct eye dosimeter is recommended. Although we found a positive correlation between Hp (0.07) and Hp (3), the value of R2 in the regression equation is low, we recommended that the eye lens dose estimated carefully from Hp (0.07).

Evaluation of lumbar intervertebral disc degeneration using dual energy CT virtual non-calcium imaging.

PURPOSE: To clarify the utility of dual energy CT (DECT) virtual non-calcium (VNCa) imaging for investigating lumbar intervertebral disc degeneration. METHOD: Fifty-three patients who underwent both DECT and MR imaging were retrospectively reviewed. Midsagittal T2-weighted imaging findings of all discs were classified based on modified Pfirrmann grade (mPG). Quantitative evaluation of VNCa maps was achieved by setting volumes of interest on each disc. We compared VNCa CT values with mPG using Spearman's rank correlation and one-way ANOVA. VNCa imaging findings of each disc were classified by two neuroradiologists into one of three categories based on the attenuation of nucleus pulposus (NP) compared to that of annulus fibrosus (AF) or muscle. The relationship between the visual categories for each rater and mPGs was analyzed by chi-square test. Statistical significance was established at P < 0.05. RESULTS: Among the included 171 lumbar discs, significant positive correlation was found between VNCa CT values for NP and mPGs (R2 = 0.574, P < 0.05), whereas no significant correlation was found between those for AF and mPGs (R2= -0.015, P = 0.846). Mean VNCa CT values for NP were significantly different among each mPG (P < 0.05 for each), except between grades 3 and 4 (P = 0.111). Mean VNCa CT values for AF were not significantly different among each mPG (P = 0.160-1.000). Statistically significant difference was observed among the visual categories for VNCa maps and mPGs in each rater (P < 0.05 for both). CONCLUSIONS: VNCa imaging acquired by a single DECT scan and post-processing has potential as an imaging biomarker of lumbar intervertebral disc degeneration.

Development of a deep learning model to identify hyperdense MCA sign in patients with acute ischemic stroke.

PURPOSE: The aim of this study was to develop an interactive deep learning-assisted identification of the hyperdense middle cerebral artery (MCA) sign (HMCAS) on non-contrast computed tomography (CT) among patients with acute ischemic stroke. MATERIALS AND METHODS: 35 HMCAS-positive and 39 HMCAS-negative samples extracted by 50-pixel-diameter circular regions of interest were obtained as training and validation datasets according to the consensus decisions of two experienced neuroradiologists. Data augmentation was performed to increase the number of training samples. A deep convolutional neural network (DCNN) (Xception) was used to classify input images as HMCAS-positive or -negative. Leave-one-case-out cross-validation was achieved to estimate sensitivity, specificity, and accuracy of the deep learning-based training model for identifying HMCAS. RESULTS: In terms of diagnostic performance, DCNN for HMCAS offered 82.9% sensitivity, 89.7% specificity, and 86.5% accuracy in leave-one-case-out cross-validation. Area under the receiver operating characteristic curve for HMCAS was 0.947 (95% confidence interval 0.895-0.998; P < 0.05). CONCLUSION: The deep learning method appears potentially beneficial for identifying HMCAS on non-contrast CT in patients with acute ischemic stroke.

OCCUPATIONAL RADIATION EXPOSURE DOSE OF THE EYE IN DEPARTMENT OF CARDIAC ARRHYTHMIA PHYSICIAN.

Interventional radiology (IR) procedures tend to be complex, which delivers high radiation exposure to patient. In the present study, we measured the radiation exposure dose [Hp(3)] in the eye using a direct eye dosemeter placed next to the physician's eye during procedures. Physicians wore a direct eye dosemeter just lateral to eyes and an additional direct eye dosemeter outside the radiation protective eyeglasses close to their eyes. Additionally, a neck glass badge was worn at the neck. Although we found a positive correlation between the left neck glass badge dose [Hp(0.07)] and the left eye lens dose [Hp(3)], the value of R2 of the regression equation were 0.62 and 0.71 (outside and inside). We thought that the exact eye lens dose might not be estimated from the neck glass badge. In conclusion, a correct evaluation of the lens dose [Hp(3)] using the direct eye dosemeter is recommended for tachyarrhythmia physicians.

Radiosynthesis of 18F-labeled d-allose.

Rare sugars are defined as monosaccharides that exist in nature but are only present in limited quantities. d-Allose is a rare sugar that has been reported to have some unique physiological effects. The present study describes suitable synthetic procedures for novel rare sugars of d-allose that are 18F-labeled at the C-3 and C-6 positions and the preparation of the appropriate labeling precursors. The goal is to facilitate in vivo, noninvasive positron emission tomography (PET) investigation of the behavior of rare sugar analogs of d-allose in organs. We found five precursors that were practical for labeling, three for 3-deoxy-3-[18F]fluoro-d-allose ([18F]3FDA) and two for 6-deoxy-6-[18F]fluoro-d-allose ([18F]6FDA). With manual operation synthesis, the highest radiochemical conversion rates were 75% for [18F]3FDA with a precursor of 1,2,4,6-tetra-O-acetyl-3-O-trifluoromethanesulfonyl-ß-d-glucopyranose and 69% for [18F]6FDA with a precursor of 1,2,3,4-tetra-O-acetyl-6-O-trifluoromethanesulfonyl-ß-d-allopyranose. Furthermore, the practical yields of [18F]3FDA and [18F]6FDA using an automated synthesizer were also investigated. Radiochemical yields of 67% and 49% were obtained for [18F]3FDA and [18F]6FDA, respectively, in an automated synthesizer. As basic assessment of stability for use in PET scanning, high performance liquid chromatography analysis showed no decomposition of [18F]3FDA and [18F]6FDA after up to 6 h in rabbit blood plasma.

OCCUPATIONAL RADIATION EXPOSURE OF THE EYE IN NEUROVASCULAR INTERVENTIONAL PHYSICIAN.

Neurovascular interventional radiology (neuro-IR) procedures tend to require an extended fluoroscopic exposure time and repeated digital subtraction angiography. To evaluate the actual measurement of eye lens dose using a direct eye dosemeter in neuro-IR physicians is important. Direct dosimetry using the DOSIRIS™ (IRSN, France) [3 mm dose equivalent, Hp(3)] was performed on 86 cases. Additionally, a neck personal dosemeter (glass badge) [0.07 mm dose equivalent, Hp(0.07)] was worn outside the protective apron to the left of the neck. The average doses per case of neuro-IR physicians were 0.04 mSv/case and 0.02 mSv/case, outside and inside the radiation protection glasses, respectively. The protective effect of radiation protection glasses was approximately 60%. The physician eye lens dose tended to be overestimated by the neck glass badge measurements. A correct evaluation of the lens dose [Hp(3)] using an eye dosemeter such as DOSIRIS™ is needed for neuro-IR physicians.