Enhanced parameter estimation in multiparametric arterial spin labeling using artificial neural networks.

PURPOSE: Multiparametric arterial spin labeling (MP-ASL) can quantify cerebral blood flow (CBF) and arterial cerebral blood volume (CBVa). However, its accuracy is compromised owing to its intrinsically low SNR, necessitating complex and time-consuming parameter estimation. Deep neural networks (DNNs) offer a solution to these limitations. Therefore, we aimed to develop simulation-based DNNs for MP-ASL and compared the performance of a supervised DNN (DNNSup), physics-informed unsupervised DNN (DNNUns), and the conventional lookup table method (LUT) using simulation and in vivo data. METHODS: MP-ASL was performed twice during resting state and once during the breath-holding task. First, the accuracy and noise immunity were evaluated in the first resting state. Second, CBF and CBVa values were statistically compared between the first resting state and the breath-holding task using the Wilcoxon signed-rank test and Cliff's delta. Finally, reproducibility of the two resting states was assessed. RESULTS: Simulation and first resting-state analyses demonstrated that DNNSup had higher accuracy, noise immunity, and a six-fold faster computation time than LUT. Furthermore, all methods detected task-induced CBF and CBVa elevations, with the effect size being larger with the DNNSup (CBF, p = 0.055, Δ = 0.286; CBVa, p = 0.008, Δ = 0.964) and DNNUns (CBF, p = 0.039, Δ = 0.286; CBVa, p = 0.008, Δ = 1.000) than that with LUT (CBF, p = 0.109, Δ = 0.214; CBVa, p = 0.008, Δ = 0.929). Moreover, all the methods exhibited comparable and satisfactory reproducibility. CONCLUSION: DNNSup outperforms DNNUns and LUT with respect to estimation performance and computation time.

Comparison between supervised and physics-informed unsupervised deep neural networks for estimating cerebral perfusion using multi-delay arterial spin labeling MRI.

This study aimed to implement a physics-informed unsupervised deep neural network (DNN) to estimate cerebral blood flow (CBF) and arterial transit time (ATT) from multi-delay arterial spin labeling (ASL), and compare its performance with that of a supervised DNN and the conventional method. Supervised and unsupervised DNNs were trained using simulation data. The accuracy and noise immunity of the three methods were compared using simulations and in vivo data. The simulation study investigated the differences between the predicted and ground-truth values and their variations with the noise level. The in vivo study evaluated the predicted values from the original images and noise-induced variations in the predicted values from the synthesized noisy images by adding Rician noise to the original images. The simulation study showed that CBF estimated using the supervised DNN was not biased by noise, whereas that estimated using other methods had a positive bias. Although the ATT with all methods exhibited a similar behavior with noise increase, the ATT with the supervised DNN was less biased. The in vivo study showed that CBF and ATT with the supervised DNN were the most accurate and that the supervised and unsupervised DNNs had the highest noise immunity in CBF and ATT estimations, respectively. Physics-informed unsupervised learning can estimate CBF and ATT from multi-delay ASL signals, and its performance is superior to that of the conventional method. Although noise immunity in ATT estimation was superior with unsupervised learning, other performances were superior with supervised learning.

18F-Fluorodeoxyglucose Positron Emission Tomography/Magnetic Resonance Imaging-Defined Extramural Venous Invasion Predicts Distant Metastasis and Reflects Strong Tumor Invasiveness in Rectal Cancer.

INTRODUCTION: Extramural vascular invasion in patients with rectal cancer is a poor prognostic factor associated with distant metastasis; thus, accurate preoperative diagnosis is important. However, the accurate detection of extramural vascular invasion using magnetic resonance imaging (MRI) is difficult, and an improved diagnostic modality is required. In addition, the factors involved in the formation of extramural venous invasion (EMVI) remain unclear. In this study, we aimed to examine the ability of 18F-fluorodeoxyglucose positron emission tomography/MRI ([18F] FDG PET/MRI) to detect EMVI and elucidate the factors involved in EMVI. METHODS: Thirty-one patients with rectal cancer were enrolled in this study between 2017 and 2021. We preoperatively evaluated the pelvic [18F] FDG PET/MRI to detect extramural vascular invasion ([18F] FDG PET/MRI-defined EMVI: pmrEMVI). To investigate the factors related to pmrEMVI, we confirmed the desmoplastic reaction (DR) and TWIST expression in the primary lesions of rectal cancer and examined its relationship with pmrEMVI. RESULTS: Six of the 31 patients were pmrEMVI positive. Four pmrEMVI-positive patients had distant metastases. The levels of immature DR and TWIST1 expression were significantly higher in cases with pmrEMVI positivity. CONCLUSION: pmrEMVI is a useful biomarker for predicting distant metastasis. In addition, pmrEMVI was significantly correlated with factors related to tumor invasiveness.

Effects of the Training Data Condition on Arterial Spin Labeling Parameter Estimation Using a Simulation-Based Supervised Deep Neural Network.

OBJECTIVE: A simulation-based supervised deep neural network (DNN) can accurately estimate cerebral blood flow (CBF) and arterial transit time (ATT) from multidelay arterial spin labeling signals. However, the performance of deep learning depends on the characteristics of the training data set. We aimed to investigate the effects of the ground truth (GT) ranges of CBF and ATT on the performance of the DNN when training data were prepared using arterial spin labeling signal simulation. METHODS: Deep neural networks were individually trained using 36 patterns of the training data sets. Simulation test data (1,000,000 points), 17 healthy volunteers, and 1 patient with moyamoya disease were included. The simulation test data were used to evaluate accuracy, precision, and noise immunity of the DNN. The best-performing DNN was determined by the normalized mean absolute error (NMAE), normalized root mean squared error (NRMSE), and normalized coefficient of variation over repeated training (CV Net ). Cerebral blood flow and ATT values and their histograms were compared between the GT and predicted values. For the in vivo data, the dependency of the predicted values on the GT ranges was visually evaluated by comparing CBF and ATT maps between the best-performing DNN and the other DNNs. Moreover, using the synthesized noisy images, noise immunity was compared between the best-performing DNN based on the simulation study and a conventional method. RESULTS: The simulation study showed that a network trained by the GT of CBF and ATT in the ranges of 0 to 120 mL/100 g/min and 0 to 4500 milliseconds, respectively, had the highest performance (NMAE CBF , 0.150; NRMSE CBF , 0.231; CV NET CBF , 0.028; NMAE ATT , 0.158; NRMSE ATT , 0.257; and CV NET ATT , 0.028). Although the predicted CBF and ATT varied with the GT range of the training data sets, the appropriate settings preserved the accuracy, precision, and noise immunity of the DNN. In addition, the same results were observed in in vivo studies. CONCLUSIONS: The GT ranges to prepare the training data affected the performance of the simulation-based supervised DNNs. The predicted CBF and ATT values depended on the GT range; inappropriate settings degraded the accuracy, whereas appropriate settings of the GT range provided accurate and precise estimates.

Estimation of Cerebral Blood Flow and Arterial Transit Time From Multi-Delay Arterial Spin Labeling MRI Using a Simulation-Based Supervised Deep Neural Network.

BACKGROUND: An inherently poor signal-to-noise ratio (SNR) causes inaccuracy and less precision in cerebral blood flow (CBF) and arterial transit time (ATT) when using arterial spin labeling (ASL). Deep neural network (DNN)-based parameter estimation can solve these problems. PURPOSE: To reduce the effects of Rician noise on ASL parameter estimation and compute unbiased CBF and ATT using simulation-based supervised DNNs. STUDY TYPE: Retrospective. POPULATION: One million simulation test data points, 17 healthy volunteers (five women and 12 men, 33.2 ± 14.6 years of age), and one patient with moyamoya disease. FIELD STRENGTH/SEQUENCE: 3.0 T/Hadamard-encoded pseudo-continuous ASL with a three-dimensional fast spin-echo stack of spirals. ASSESSMENT: Performances of DNN and conventional methods were compared. For test data, the normalized mean absolute error (NMAE) and normalized root mean squared error (NRMSE) between the ground truth and predicted values were evaluated. For in vivo data, baseline CBF and ATT and their relative changes with respect to SNR using artificial noise-added images were assessed. STATISTICAL TESTS: One-way analysis of variance with post-hoc Tukey's multiple comparison test, paired t-test, and the Bland-Altman graphical analysis. Statistical significance was defined as P < 0.05. RESULTS: For both CBF and ATT, NMAE and NRMSE were lower with DNN than with the conventional method. The baseline values were significantly smaller with DNN than with the conventional method (CBF in gray matter, 66 ± 10 vs. 71 ± 12 mL/100 g/min; white matter, 45 ± 6 vs. 46 ± 7 mL/100 g/min; ATT in gray matter, 1424 ± 201 vs. 1471 ± 154 msec). CBF and ATT increased with decreasing SNR; however, their change rates were smaller with DNN than were those with the conventional method. Higher CBF in the prolonged ATT region and clearer contrast in ATT were identified by DNN in a clinical case. DATA CONCLUSION: DNN outperformed the conventional method in terms of accuracy, precision, and noise immunity. EVIDENCE LEVEL: 3 Technical Efficacy: Stage 1.

Prognostic value of metabolic tumor volume of extranodal involvement in diffuse large B cell lymphoma.

Extranodal involvement predicts poor outcomes of diffuse large B cell lymphoma (DLBCL), but the impact of the metabolic tumor burden (MTV) of extranodal sites using positron emission tomography has not been clarified. This study aimed to assess the impact of extranodal MTV on overall survival (OS). We retrospectively analyzed 145 newly diagnosed DLBCL patients and verified the prognostic impact of each extranodal and nodal MTV. Multivariate Cox hazards modelling using both extranodal and nodal MTV as covariables identified extranodal MTV as a significant factor for OS (hazard ratio [HR] 1.072, 95% confidence interval [CI] 1.019-1.129, P = 0.008), but not nodal MTV. Multivariate Cox modelling using restricted cubic splines demonstrated that the impact of total MTV depends on the MTV of extranodal sites, not of nodal sites. When both the number and MTV of extranodal involvements were used as covariables, extranodal MTV remained a significant predictor of OS (HR 1.070, 95%CI 1.017-1.127, P = 0.009), but the number of extranodal sites did not. Extranodal MTV potentially had a more significant role on prognosis than nodal MTV. When considering prognostic impacts, the MTV of extranodal involvement is significantly more important than the number.

Regional cortical hypoperfusion and atrophy correlate with striatal dopaminergic loss in Parkinson's disease: a study using arterial spin labeling MR perfusion.

PURPOSE: To investigate the relationship of the striatal dopamine transporter density to changes in the gray matter (GM) volume and cerebral perfusion in patients with Parkinson's disease (PD). METHODS: We evaluated the regional cerebral blood flow (CBF) and GM volume, concurrently measured using arterial spin labeling and T1-weighted magnetic resonance imaging, respectively, as well as the striatal specific binding ratio (SBR) in 123I-N-ω-fluoropropyl-2ß-carboxymethoxy-3ß-(4-iodophenyl)nortropane (123I-FP-CIT) single-photon emission computed tomography in 30 non-demented patients with PD (15 men and 15 women; mean age, 67.2 ± 8.8 years; mean Hoehn-Yahr stage, 2.2 ± 0.9). Voxel-wise regression analyses using statistical parametric mapping (SPM) were performed to explore the brain regions that showed correlations of the striatal SBR to the GM volume and CBF, respectively, with a height threshold of p < 0.0005 at the voxel level and p < 0.05 family-wise error-corrected at the cluster level. RESULTS: SPM analysis showed a significant positive correlation between the SBR and GM volume in the inferior frontal gyrus (IFG). Whereas, a positive correlation between the SBR and CBF was widely found in the frontotemporal and parietotemporal regions, including the IFG. Notably, the opercular part of the IFG showed significant correlations in both SPM analyses of the GM volume (r2 = 0.90, p < 0.0001) and CBF (r2 = 0.88, p < 0.0001). CONCLUSION: The voxel-wise analyses revealed the brain regions, mainly the IFG, that showed hypoperfusion and atrophy related to dopaminergic loss, which suggests that the progression of dopaminergic neurodegeneration leads to regional cortical dysfunction in PD.

Feasibility of [18F]FDG PET/MRI with Early-Delayed and Extended PET as One-Stop Imaging for Staging and Predicting Metastasis in Rectal Cancer.

BACKGROUND: We aimed to evaluate the diagnostic accuracy of 2-[18F]-fluoro-2-deoxy-D-glucose positron emission tomography/magnetic resonance imaging ([18F]FDG PET/MRI) for preoperative staging and usefulness of the detection of extramural vascular invasion (EMVI) for predicting metastasis in rectal cancer. METHODS: Twenty-three patients underwent pretreatment [18F]FDG PET/MRI, including early-delayed and extended PET and dedicated pelvic MRI without using anticonvulsant or contrast agents. Seven patients received preoperative treatment and all subsequently underwent surgery. Clinical cancer stages were evaluated using postoperative histopathology as a reference. PET/MR-defined EMVI (pmrEMVI) and pathological (p) TN stages were correlated with disease progression for a maximum of 2 years. RESULTS: Of 16 patients without preoperative treatment, 10 had pT3, 4 tumors, 7 had pN1-3 lymph nodes, and 5 had synchronous metastases (SM; liver, lung, inguinal node). The sensitivity, specificity, and accuracy of PET/MRI were 90%, 67%, and 81% for T staging (T1, 2 vs. T3, 4), and 89%, 100%, and 94% for N staging (N0 vs. N1-3), respectively. Patient-based accuracy for SM staging was 100% (4/4). Of 23 patients, 6 were positive for pmrEMVI and 4 had metachronous metastases or local recurrence (MM; pelvic node, brain, lung, skin) during the follow-up periods. Five of the 6 pmrEMVI-positive patients had SM and/or MM (odds ratio = 37.5). Among pT, pN, and pmrEMVI, pmrEMVI-positivity was the only significant predictor for poorer progression-free survival (p < 0.05). CONCLUSIONS: [18F]FDG PET/MRI according to our suggested protocol is a one-stop, non-contrast, and valid diagnostic method for rectal cancer staging, and pmr-EMVI can be used as an imaging biomarker for predicting metastases.

Arterial spin labeling imaging for the detection of cerebral blood flow asymmetry in patients with corticobasal syndrome.

PURPOSE: Corticobasal syndrome (CBS) and Parkinson's disease (PD) both present with asymmetrical extrapyramidal symptoms, often leading to a diagnostic dilemma. Patients with CBS frequently show cerebral blood flow (CBF) asymmetry alongside asymmetrical cortical atrophy. This study aimed to evaluate the clinical utility of arterial spin labeling (ASL) magnetic resonance imaging (MRI) to detect CBF asymmetry in patients with CBS. METHODS: We retrospectively investigated asymmetries of regional CBF and cortical volume, measured using ASL and T1-weighted MRI, in 13 patients with CBS and 22 age-matched patients with PD. Regional CBF and cortical volume values were derived from nine brain regions on each side. CBF and volume asymmetries were calculated as %difference in each region, respectively. RESULTS: CBF asymmetry showed significantly greater differences in seven of nine regions, such as the perirolandic area (- 8.7% vs. - 1.4%, p < 0.001) and parietal cortex (- 9.7% vs. - 1.3%, p < 0.001) in patients with CBS compared with patients with PD. In contrast, significant differences in volume asymmetry were observed in three regions included within the seven regions showing CBF asymmetry, which indicated that CBF asymmetry has greater sensitivity than volume asymmetry to detect asymmetricity in CBS. CONCLUSION: ASL imaging showed significant CBF asymmetry in a wider range of brain regions in patients with CBS, which suggests that noninvasive MRI with ASL imaging is a promising tool for the diagnosis of CBS, with advantages that include the simultaneous evaluation of asymmetrical hypoperfusion in addition to focal atrophy.

The vertebral 3'-deoxy-3'-18F-fluorothymidine uptake predicts the hematological toxicity after systemic chemotherapy in patients with lung cancer.

OBJECTIVES: Although hematological toxicities (HT) are the leading adverse events of systemic chemotherapy, the estimation of severe HT is challenging. Recently, 3'-deoxy-3'-[18F]-fluorothymidine (18F-FLT) accumulation with PET has been considered a biomarker of the cell proliferation. This study aims to elucidate whether the vertebral accumulation of 18F-FLT could estimate severe HT during platinum-doublet chemotherapy. METHODS: In this Institutional Review Board-approved retrospective study, 50 patients with primary lung cancer underwent 18F-FLT PET scan before platinum-doublet chemotherapy. We evaluated the standardized uptake value, total vertebral proliferation (TVP), and TVP/body surface area (TVP/BSA) of the vertebral body (Th4, Th8, Th12, and L4), and then the associations between those parameters and frequency of severe HT during platinum-doublet chemotherapy were assessed. RESULTS: Severe HT (grade 3/4) was observed in 40.0% of patients during the first cycle. The ROC curve analyses revealed that the TVP/BSA of L4 was the most discriminative parameter among PET parameters for the prediction of severe HT. The multivariate logistic regression analysis revealed the TVP/BSA of L4 (odds ratio [OR], 0.94; p = 0.0036) and the frequency of the grade 3/4 hematological toxicity in previous clinical trials (OR, 1.03; p = 0.023) were independent predictors. Furthermore, the sensitivity, specificity, and accuracy of the TVP/BSA of L4 cut-off of 68.7 to predict grade 3/4 HT were 80.0%, 86.7%, and 84.0%, respectively. A low TVP/BSA of L4 (< 68.7) as a binary variable was a significant indicator of severe HT (OR, 26.0; p = 0.000026). CONCLUSIONS: The low 18F-FLT uptake in the lower vertebral body is a predictor of severe HT in patients with lung cancer who receive platinum-doublet chemotherapy. TRIAL REGISTRATION: Trial registration: UMIN000027540 KEY POINTS: • The vertebral 18 F-FLT uptake with PET is an independent predictor of the severe hematological toxicity during the first cycle of platinum-doublet chemotherapy. • The 18 F-FLT uptake in L4 vertebral body estimated hematological toxicities better than that in the upper vertebra (Th4, Th8, and Th12). • The evaluation of the amount and activity of hematopoietic cells in the bone marrow cavity using 18 F-FLT PET imaging could provide predictive data of severe hematological toxicities and help determine an appropriate drug combination or dose intensity in patients with advanced malignant diseases.

Precise Evaluation of Striatal Oxidative Stress Corrected for Severity of Dopaminergic Neuronal Degeneration in Patients with Parkinson's Disease: A Study with 62Cu-ATSM PET and 123I-FP-CIT SPECT.

BACKGROUND: This study sought to precisely evaluate striatal oxidative stress and its relationship with the disease severity in Parkinson's disease (PD) using double brain imaging, 62Cu-diacetyl-bis (N4-methylthiosemicarbazone) (62Cu-ATSM) PET and 123I-FP-CIT SPECT. METHODS: Nine PD patients were studied with brain 62Cu-ATSM PET for oxidative stress and 123I-FP-CIT SPECT for the density of striatal dopamine transporter. Standardized uptake values (SUVs) were obtained from the delayed phase of dynamic 62Cu-ATSM PET, and striatum-to-cerebellum SUV ratio (SUVR) was calculated. To correct the effect of neuronal loss in the striatum, 62Cu-ATSM SUVR was corrected for striatal specific binding ratio (SBR) values of 123I-FP-CIT (SUVR/SBR). RESULTS: 62Cu-ATSM SUVR without correction was not significantly correlated with disease severity estimated by the Unified Parkinson's Disease Rating Scale (UPDRS) scores or 123I-FP-CIT SBR. In contrast, the SUVR/SBR showed significant correlations with the UPDRS total and motor scores, and 123I-FP-CIT SBR. CONCLUSION: Oxidative stress in the remaining striatal dopaminergic neurons estimated by SUVR/SBR was increased with disease severity in PD patients, suggesting that oxidative stress based on mitochondrial dysfunction contributes to promoting dopaminergic neuronal degeneration in PD. 62Cu-ATSM PET with 123I-FP-CIT SPECT correction would be a promising tool to evaluate dopaminergic neuronal oxidative stress in PD.

Metabolic tumor burden predicts prognosis of ovarian cancer patients who receive platinum-based adjuvant chemotherapy.

Volumetric parameters of positron emission tomography-computed tomography using 18F-fludeoxyglucose ((18) F-FDG PET/CT) that comprehensively reflect both metabolic activity and tumor burden are capable of predicting survival in several cancers. The aim of this study was to investigate the predictive performance of metabolic tumor burden measured by (18) F-FDG PET/CT in ovarian cancer patients who received platinum-based adjuvant chemotherapy after cytoreductive surgery. Included in this study were 37 epithelial ovarian cancer patients. Metabolic tumor burden in terms of metabolic tumor volume (MTV) and total lesion glycolysis (TLG), clinical stage, histological type, residual tumor after primary cytoreductive surgery, baseline serum carbohydrate antigen 125 (CA125) level, and the maximum standardized uptake value (SUVmax ) were determined, and compared for their performance in predicting progression-free survival (PFS). Metabolic tumor volume correlated with CA125 (r = 0.547, P < 0.001), and TLG correlated with SUVmax and CA125 (SUVmax , r = 0.437, P = 0.007; CA125, r = 0.593, P < 0.001). Kaplan-Meier analysis showed a significant difference in PFS between the groups categorized by TLG (P = 0.043; log-rank test). Univariate analysis indicated that TLG was a statistically significant risk factor for poor PFS. Multivariate analysis adjusted according to the clinicopathological features was carried out for MTV, TLG, SUVmax , tumor size, and CA125. Only TLG showed a significant difference (P = 0.038), and a 3.915-fold increase in the hazard ratio of PFS. Both MTV and TLG (especially TLG) could serve as potential surrogate biomarkers for recurrence in patients who undergo primary cytoreductive surgery followed by platinum-based chemotherapy, and could identify patients at high risk of recurrence who need more aggressive treatment.

Comparison of image quality with 62Cu and 64Cu-labeled radiotracers in positron emission tomography whole-body phantom imaging.

OBJECTIVE: PET imaging is possible with copper (Cu) isotopes, (60)Cu, (61)Cu, (62)Cu and (64)Cu. Although (62)Cu- and (64)Cu-labeled radiotracers are often used for preclinical and clinical PET studies, we do not know which radiotracers have better image quality for tumor imaging. In this study, we compare image quality between (62)Cu and (64)Cu imaging with a different acquisition mode and reconstruction algorithm using a whole-body phantom for tumor imaging. METHODS: In a National Electrical Manufacturers Association (NEMA) 2001 whole-body phantom, the concentration of (62)Cu-ATSM and (64)Cu-ATSM was, respectively, approximately 2.7 and 1.8MBq/mL in all the spheres and approximately 0.9 and 0.6MBq/mL in the background. After adjustment for true coincidence events between (62)Cu and (64)Cu, two-dimensional (2D) and three-dimensional (3D) PET scan data were acquired for 10min. The data were reconstructed using filtered back projection (FBP) and the ordered subset expectation maximization (OSEM) algorithm. Image quality of (62)Cu and (64)Cu was compared using recovery coefficient (RC), sphere-to-background ratio (SBR) and coefficient of variation (%COV). RESULTS: There were little significant differences between (62)Cu and (64)Cu imaging, visually. Recovery coefficients of (64)Cu images were higher than those of (62)Cu images. The RC of (64)Cu images with 3D acquisition mode and OSEM was the highest in all experiments. No SBR values were significantly different from the true value of 3.0 in 37mm sphere diameters, but 3D acquisition and OSEM yielded slight overestimations compared with 2D acquisition and FBP, the gold standard for quantification in PET studies. Percentage COV values of (64)Cu with OSEM were significantly lower than those of (62)Cu. CONCLUSIONS: Copper-64 radiotracers provide higher image quality than (62)Cu-radiotracers in whole-body tumor imaging only when the 3D acquisition mode and OSEM algorithm are applied. However, the quantitative values for smaller tumors may be slightly overestimated.

In vitro and in vivo evaluation of (11)C-SD5024, a novel PET radioligand for human brain imaging of cannabinoid CB1 receptors.

We recently developed a novel cannabinoid subtype-1 (CB1) receptor radioligand (11)C-SD5024 for brain imaging. This study aimed to evaluate (11)C-SD5024 both in vitro and in vivo and compare it with the other CB1 receptor ligands previously used in humans, i.e., (11)C-MePPEP, (11)C-OMAR, (18)F-MK-9470, and (18)F-FMPEP-d2. In vitro experiments were performed to measure dissociation constant (Ki) in the human brain and to measure the lipophilicity of the five CB1 receptor ligands listed above. In vivo specific binding in monkeys was measured by comparing total distribution volume (VT) at baseline and after full receptor blockade. The kinetics of (11)C-SD5024 in humans were evaluated in seven healthy subjects with compartmental modeling. SD5024 showed Ki=0.47nM, which was at an intermediate level among the five CB1 receptor ligands. Lipophilicity (LogD7.4) was 3.79, which is appropriate for brain imaging. Monkey scans showed high proportion of specific binding: ~80% of VT. In humans, (11)C-SD5024 showed peak brain uptake of 1.5-3 standardized uptake value, which was slightly higher than that of (11)C-OMAR and (18)F-MK-9470. One-compartment model showed good fitting, consistent with the vast majority of brain uptake being specific binding found in the monkey. Regional VT values were consistent with known distribution of CB1 receptors. VT calculated from 80 and 120min of scan data was strongly correlated (R(2)=0.97), indicating that 80min provided adequate information for quantitation and that the influence of radiometabolites was low. Intersubject variability for VT of (11)C-SD5024 was 22%, which was low among the five radioligands and indicated precise measurement. In conclusion, (11)C-SD5024 has appropriate affinity and lipophilicity, high specific binding, moderate brain uptake, and provides good precision to measure the binding. The results suggest that (11)C-SD5024 is slightly better than or equivalent to (11)C-OMAR and that both are suitable for clinical studies, especially those that involve two scans in one day.

Evaluation in monkey of two candidate PET radioligands, [11 C]RX-1 and [18 F]RX-2, for imaging brain 5-HT4 receptors.

The serotonin subtype-4 (5-HT4 ) receptor, which is known to be involved physiologically in learning and memory, and pathologically in Alzheimer's disease, anxiety, and other neuropsychiatric disorders-has few radioligands readily available for imaging in vivo. We have previously reported two novel 5-HT4 receptor radioligands, namely [methoxy-11 C](1-butylpiperidin-4-yl)methyl 4-amino-3-methoxybenzoate; [11 C]RX-1), and the [18 F]3-fluoromethoxy analog ([18 F]RX-2), and in this study we evaluated them by PET in rhesus monkey. Brain scans were performed at baseline, receptor preblock or displacement conditions using SB 207710, a 5-HT4 receptor antagonist, on the same day for [11 C]RX-1 and on different days for [18 F]RX-2. Specific-to-nondisplaceable ratio (BPND ) was measured with the simplified reference tissue model from all baseline scans. To determine specific binding, total distribution volume (VT ) was also measured in some monkeys by radiometabolite-corrected arterial input function after ex vivo inhibition of esterases from baseline and blocked scans. Both radioligands showed moderate to high peak brain uptake of radioactivity (2-6 SUV). Regional BPND values were in the rank order of known 5-HT4 receptor distribution with a trend for higher BPND values from [18 F]RX-2. One-tissue compartmental model provided good fits with well identified VT values for both radioligands. In the highest 5-HT4 receptor density region, striatum, 50-60% of total binding was specific. The VT in receptor-poor cerebellum reached stable values by about 60 min for both radioligands indicating little influence of radiometabolites on brain signal. In conclusion, both [11 C]RX-1 and [18 F]RX-2 showed positive attributes for PET imaging of brain 5-HT4 receptors, validating the radioligand design strategy. Synapse 68:613-623, 2014. © 2014 Wiley Periodicals, Inc.

High efficacy of particle beam therapies against tumors under hypoxia and prediction of the early stage treatment effect using 3'-deoxy-3'-[18F]fluorothymidine positron emission tomography.

OBJECTIVE: Compared with radiation therapy using photon beams, particle therapies, especially those using carbons, show a high relative biological effectiveness and low oxygen enhancement ratio. Using cells cultured under normoxic conditions, our group reported a greater suppressive effect on cell growth by carbon beams than X-rays, and the subsequent therapeutic effect can be predicted by the cell uptake amount of 3'-deoxy-3'-[18F]fluorothymidine (18F-FLT) the day after treatment. On the other hand, a hypoxic environment forms locally around solid tumors, influencing the therapeutic effect of radiotherapy. In this study, the influence of tumor hypoxia on particle therapies and the ability to predict the therapeutic effect using 18F-FLT were evaluated. METHODS: Using a murine colon carcinoma cell line (colon 26) cultured under hypoxic conditions (1.0% O2 and 5.0% CO2), the suppressive effect on cell growth by X-ray, proton, and carbon irradiation was evaluated. In addition, the correlation between decreased 18F-FLT uptake after irradiation and subsequent suppression of cell proliferation was investigated. RESULTS: Tumor cell growth was suppressed most efficiently by carbon-beam irradiation. 18F-FLT uptake temporarily increased the day after irradiation, especially in the low-dose irradiation groups, but then decreased from 50 h after irradiation, which is well correlated with the subsequent suppression on tumor cell growth. CONCLUSIONS: Carbon beam treatment shows a strong therapeutic effect against cells under hypoxia. Unlike normoxic tumors, it is desirable to perform 18F-FLT positron emission tomography 2-3 days after irradiation for early prediction of the treatment effect.

Evaluation of calcification distribution by CT-based textural analysis for discrimination of immature teratoma.

BACKGROUND: Mature and immature teratomas are differentiated based on tumor markers and calcification or fat distribution. However, no study has objectively quantified the differences in calcification and fat distributions between these tumors. This study aimed to evaluate the diagnostic potential of CT-based textural analysis in differentiating between mature and immature teratomas in patients aged < 20 years. MATERIALS AND METHODS: Thirty-two patients with pathologically proven mature cystic (n = 28) and immature teratomas (n = 4) underwent transabdominal ultrasound and/or abdominal and pelvic CT before surgery. The diagnostic performance of CT for assessing imaging features, including subjective manual measurement and objective textural analysis of fat and calcification distributions in the tumors, was evaluated by two experienced readers. The histopathological results were used as the gold standard. The Mann-Whitney U test was used for statistical analysis. RESULTS: We evaluated 32 patients (mean age, 14.5 years; age range, 6-19 years). The mean maximum diameter and number of calcifications of immature teratomas were significantly larger than those of mature cystic teratomas (p < 0.01). The mean number of fats of immature teratomas was significantly larger than that of mature cystic teratomas (p < 0.01); however, no significant difference in the maximum diameter of fats was observed. CT textural features for calcification distribution in the tumors showed that mature cystic teratomas had higher homogeneity and energy than immature teratomas. However, immature teratomas showed higher correlation, entropy, and dissimilarity than mature cystic teratomas among features derived from the gray-level co-occurrence matrix (GLCM) (p < 0.05). No significant differences were observed in the CT features of fats derived from GLCM. CONCLUSION: Our results demonstrate that calcification distribution on CT is a potential diagnostic biomarker to discriminate mature from immature teratomas, thus enabling optimal therapeutic selection for patients aged < 20 years.

Specific Binding Ratio Estimation of [123I]-FP-CIT SPECT Using Frontal Projection Image and Machine Learning.

This study aimed to develop a new convolutional neural network (CNN) method for estimating the specific binding ratio (SBR) from only frontal projection images in single-photon emission-computed tomography using [123I]ioflupane. We created five datasets to train two CNNs, LeNet and AlexNet: (1) 128FOV used a 0° projection image without preprocessing, (2) 40FOV used 0° projection images cropped to 40 × 40 pixels centered on the striatum, (3) 40FOV training data doubled by data augmentation (40FOV_DA, left-right reversal only), (4) 40FOVhalf, and (5) 40FOV_DAhalf, split into left and right (20 × 40) images of 40FOV and 40FOV_DA to separately evaluate the left and right SBR. The accuracy of the SBR estimation was assessed using the mean absolute error, root mean squared error, correlation coefficient, and slope. The 128FOV dataset had significantly larger absolute errors compared to all other datasets (p < 0. 05). The best correlation coefficient between the SBRs using SPECT images and those estimated from frontal projection images alone was 0.87. Clinical use of the new CNN method in this study was feasible for estimating the SBR with a small error rate using only the frontal projection images collected in a short time.