Dual-Energy CT-Derived Electron Density for Diagnosing Metastatic Mediastinal Lymph Nodes in Non-Small Cell Lung Cancer: Comparison With Conventional CT and FDG PET/CT Findings.

BACKGROUND. Accurate nodal staging is essential to guide treatment selection in patients with non-small cell lung cancer (NSCLC). To our knowledge, measurement of electron density (ED) using dual-energy CT (DECT) is unexplored for this purpose. OBJECTIVE. The purpose of our study was to assess the utility of ED from DECT in diagnosing metastatic mediastinal lymph nodes in patients with NSCLC in comparison with conventional CT and FDG PET/CT. METHODS. This retrospective study included 57 patients (36 men, 21 women; mean age, 68.4 ± 8.9 [SD] years) with NSCLC and surgically resected mediastinal lymph nodes who underwent preoperative DECT and FDG PET/CT. The patients had a total of 117 resected mediastinal lymph nodes (33 metastatic, 84 nonmetastatic). Two radiologists independently reviewed the morphologic features of nodes on the 120-kVp images and also measured the iodine concentration (IC) and ED of nodes using maps generated from DECT data; consensus was reached for discrepancies. Two different radiologists assessed FDG PET/CT examinations in consensus for positive node uptake. Diagnostic performance was evaluated for individual and pairwise combinations of features. RESULTS. The sensitivity, specificity, and accuracy for nodal metastasis were 15.2%, 98.8%, and 75.2% for the presence of necrosis, respectively; 54.5%, 85.7%, and 76.9% for short-axis diameter greater than 8.5 mm; 63.6%, 73.8%, and 70.9% for long-axis diameter greater than 13.0 mm; 51.5%, 79.8%, and 71.8% for attenuation on 120-kVp images of 95.8 HU or less; 87.9%, 58.3%, and 66.7% for ED of 3.48 × 1023/cm3 or less; and 66.7%, 75.0%, and 72.6% for positive FDG uptake. Among pairwise combinations of features, accuracy was highest for the combination of ED and short-axis diameter (accuracy, 82.9%; sensitivity, 54.5%; specificity, 94.0%) and the combination of ED and positive FDG uptake (accuracy, 82.1%; sensitivity, 60.6%; specificity, 90.5%); these accuracies were greater than those for the individual features (p < .05). The remaining combinations exhibited accuracies ranging from 74.4% to 77.8%. Interobserver agreement analysis showed an intraclass correlation coefficient of 0.90 for ED. IC was not significantly different between metastatic and nonmetastatic nodes (p = .18) and was excluded from the diagnostic performance analysis. CONCLUSION. ED derived from DECT may help diagnose metastatic lymph nodes in NSCLC given decreased ED in metastatic nodes. CLINICAL IMPACT. ED may complement conventional CT findings and FDG uptake on PET/CT in diagnosing metastatic nodes.

Intermolecular Interaction of Tetrabutylammonium and Tetrabutylphosphonium Salt Hydrates by Low-Frequency Raman Observation.

Semi-clathrate hydrates are attractive heat storage materials because the equilibrium temperatures, located above 0 °C in most cases, can be changed by selecting guest cations and anions. The equilibrium temperatures are influenced by the size and hydrophilicity of guest ions, hydration number, crystal structure, and so on. This indicates that intermolecular and/or interionic interaction in the semi-clathrate hydrates may be related to the variation of the equilibrium temperatures. Therefore, intermolecular and/or interionic interaction in semi-clathrate hydrates with quaternary onium salts was directly observed using low-frequency Raman spectroscopy, a type of terahertz spectroscopy. The results show that Raman peak positions were mostly correlated with the equilibrium temperatures: in the semi-clathrate hydrates with higher equilibrium temperatures, Raman peaks around 65 cm-1 appeared at a higher wavenumber and the other Raman peaks at around 200 cm-1 appeared at a lower wavenumber. Low-frequency Raman observation is a valuable tool with which to study the equilibrium temperatures in semi-clathrate hydrates.

The clinical value of texture analysis of dual-time-point 18F-FDG-PET/CT imaging to differentiate between 18F-FDG-avid benign and malignant pulmonary lesions.

OBJECTIVES: To examine whether the texture analysis of dual-time-point (DTP) F-18-fluorodeoxyglucose (18F-FDG)-PET/CT imaging can differentiate between 18F-FDG-avid benign and malignant pulmonary lesions. METHODS: We compared standardized uptake value (SUV)-related (SUVmax [g/ml] and SUVmean [g/ml]), volumetric (metabolic tumor volume [MTV] [cm3] and total lesion glycolysis [TLG] [g]), and texture (entropy, homogeneity, dissimilarity, intensity variability [IV], size-zone variability [SZV], and zone percentage [ZP]) (MTV ≥ 5.0 cm3 and SUV ≥ 2.5 g/ml) parameters between 13 benign and 46 malignant lesions using the Mann-Whitney U test. Diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis. Stepwise logistic regression analysis was performed to identify and use the independent variables that correctly differentiate between benign and malignant lesions. RESULTS: Malignant pulmonary lesions showed significantly higher SUVmax, SUVmean, MTV, TLG, entropy, dissimilarity, IV, and SZV and significantly lower homogeneity and ZP than benign pulmonary lesions (all p < 0.05) in both early and delayed images. Their areas under the ROC curves (AUCs) ranged between 0.69 and 0.94, and diagnostic accuracies between 64.4% and 93.2%. Entropy-early (p = 0.014), SUVmean-delay (p = 0.039), and dissimilarity-delay (p = 0.027) were independent parameters, and combined use of them yielded the highest AUC (0.98) with 100% sensitivity (46/46), 84.6% specificity (11/13), and 96.7% (57/59) accuracy for distinguishing between benign and malignant lesions. CONCLUSIONS: The individual early and delayed SUV-related, volumetric, and texture parameters showed a wide range of accuracy. Combined use of independent parameters extracted from DTP imaging might yield a high diagnostic accuracy with balanced sensitivity and specificity to differentiate between benign and malignant 18F-FDG-avid pulmonary lesions. KEY POINTS: • Malignant pulmonary lesions showed significantly higher SUV-related (SUVmax and SUVmean) and volumetric (MTV and TLG) parameters than benign pulmonary lesions in both early and delayed images. • Malignant pulmonary lesions showed significantly more heterogeneous18F-FDG uptake than benign pulmonary lesions in both early and delayed images. • Combined use of independent parameters extracted from DTP imaging might yield a high diagnostic accuracy to differentiate between benign and malignant18F-FDG-avid pulmonary lesions.

Response to neoadjuvant chemotherapy for breast cancer judged by PERCIST - multicenter study in Japan.

PURPOSE: The purpose of this study was to evaluate therapeutic response to neoadjuvant chemotherapy (NAC) and predict breast cancer recurrence using Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST). MATERIALS AND METHODS: Fifty-nine breast cancer patients underwent fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) before and after NAC prior to planned surgical resection. Pathological complete response (pCR) of the primary tumor was evaluated using PERCIST, while effects of clinicopathological factors on progression-free survival (PFS) were examined using log-rank and Cox methods. RESULTS: Fifty-six patients and 54 primary tumors were evaluated. Complete metabolic response (CMR), partial metabolic response, stable metabolic disease, and progressive metabolic disease were seen in 45, 7, 3, and 1 patients, respectively, and 43, 7, 3, and 1 primary tumors, respectively. Eighteen (33.3%) of the 54 primary tumors showed pCR. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of PERCIST to predict pCR were 100% (18/18), 30.6% (11/36), 41.9% (18/43), 100% (11/11), and 53.7% (29/54), respectively. An optimal percent decrease in peak standardized uptake value for a primary tumor corrected for lean body mass (SULpeak) of 84.3% was found to have a sensitivity of 77.8% (14/18), specificity of 77.8% (28/36), PPV of 63.6% (14/22), NPV of 87.5% (28/32), and accuracy of 77.8% (42/54). Seven (12.5%) of the 56 patients developed recurrent disease (median follow-up 28.1 months, range 11.4-96.4 months). CMR (p = 0.031), pCR (p = 0.024), and early TNM stage (p = 0.033) were significantly associated with longer PFS. CONCLUSION: PERCIST is useful for predicting pathological response and prognosis following NAC in breast cancer patients. However, FDG-PET/CT showed a tendency toward underestimation of the residual tumor, and relatively low specificity and PPV of PERCIST showed that a combination of other imaging modalities would still be needed to predict pCR.

Water-Processable, Air-Stable Organic Nanoparticle-Carbon Nanotube Nanocomposites Exhibiting n-Type Thermoelectric Properties.

Water-dispersed organic base nanoparticles are utilized for the highly stable n-type doping of single-walled carbon nanotubes in aqueous dispersion. Long-term stability is often a critical challenge in the application of n-type organic conductors. The present n-type organic materials exhibit almost no degradation in the thermoelectric properties over months, in air.

A pilot study for texture analysis of 18F-FDG and 18F-FLT-PET/CT to predict tumor recurrence of patients with colorectal cancer who received surgery.

PURPOSE: This retrospective study was done to examine whether the heterogeneity in primary tumor F-18-fluorodeoxyglucose (18F-FDG) and 18F-3'-fluoro-3'-deoxythymidine (18F-FLT) distribution can predict prognosis of patients with colorectal cancer who received surgery. METHODS: The enrolled 32 patients with colorectal cancer underwent both 18F-FDG- and 18F-FLT-PET/CT studies before surgery. Clinicopathological factors, stage, SUVmax, SUVmean, metabolic tumor volume (SUV ≥ 2.5), total lesion glycolysis, total lesion proliferation and seven texture heterogeneity parameters (coefficient of variation, local parameters: entropy, homogeneity, and dissimilarity; and regional parameters: intensity variability [IV], size-zone variability [SZV], and zone percentage [ZP]) were obtained. Progression free survival (PFS) was calculated by the Kaplan-Meier method. Prognostic significance was assessed by Cox proportional hazards analysis. RESULTS: Eight patients had eventually come to progression, and 24 patients were alive without progression during clinical follow-up [mean follow-up PFS; 55.9 months (range, 1-72)]. High stage (p = 0.004), high 18F-FDG-IV (p = 0.015), high 18F-FDG-SZV (p = 0.013) and high 18F-FLT-entropy (p = 0.015) were significant in predicting poor 5-year PFS. Other parameters did not predict the disease outcome. At bivariate analysis, disease event hazards ratios for 18F-FDG-IV and 18F-FDG-SZV remained significant when adjusted for stage and 18F-FLT-entropy (18F-FDG-IV; p = 0.004 [adjusted for stage], 0.007 [adjusted for 18F-FLT-entropy]; 18F-FDG-SZV; p = 0.028 [adjusted for stage], 0.040 [adjusted for 18F-FLT-entropy]). CONCLUSION: 18F-FDG PET heterogeneity parameters, IV and SZV, have a potential to be strong prognostic factors to predict PFS of patients with surgically resected colorectal cancer and are more useful than 18F-FLT-PET/CT heterogeneity parameters.

A small pancreatic hamartoma with an obstruction of the main pancreatic duct and avid FDG uptake mimicking a malignant pancreatic tumor: a systematic case review.

BACKGROUND: Pancreatic hamartomas are extremely rare and may be misdiagnosed as malignant tumors. We report herein a case of a small, solid-type pancreatic hamartoma. CASE PRESENTATION: A 72-year-old female was incidentally detected pancreatic lesion by ultrasonography. Computed tomography and magnetic resonance imaging revealed a 2.0-cm solid lesion. The main pancreatic duct (MPD) was obstructed by the lesion in the head of the pancreas, and the upstream MPD was dilated. 18F-fluorodeoxyglucose (FDG) accumulated avidly in the lesion and increased in FDG intensity from the early to the delayed images. The histopathological studies confirmed the diagnosis of pancreatic hamartoma. Immunohistochemically, the cell membrane of the accessory glands and ducts showed homogeneous expression of glucose transporter type I and hexokinase II. CONCLUSION: Pancreatic hamartomas causing dilatation of the MPD are extremely rare, and this appears to be the first case of a hamartoma to take up FDG avidly. It was a rare occurrence and should be noted that pancreatic hamartomas can cause an obstruction of the MPD and show avid FDG uptake, thereby mimicking malignant pancreatic tumors.

Identification and characterization of oxidative metabolites of 1-chloropyrene.

Polycyclic aromatic hydrocarbons (PAHs) and chlorinated PAHs (ClPAHs) are ubiquitous contaminants that bind to the aryl hydrocarbon receptor (AhR) and exhibit mutagenic potential. It is difficult to monitor human exposure levels to ClPAHs because the exposure routes are complicated, and environmental concentrations are not always correlated with the levels of PAHs. Urinary PAH metabolites are useful biomarkers for evaluating PAH exposure, and ClPAH metabolites may therefore contribute to the estimation of ClPAH exposure. One of the most abundant ClPAHs present in the environment is 1-chloropyrene (ClPyr), and urinary ClPyr metabolites have the potential to be good biomarkers to evaluate the level of exposure to ClPAHs. Since the metabolic pathways involving ClPAHs are still undetermined, we investigated the effect of human cytochrome P450 enzymes on ClPyr and identified three oxidative metabolites by liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance. We found that ClPyr was metabolized most efficiently by the P450 1A1 enzyme, followed by the 1B1 and 1A2 enzymes. Similar to ClPyr, these metabolites were shown to have agonist activity for the human AhR. We detected these metabolites when ClPyr reacted with a pooled human liver S9 fraction as well as in human urine samples. These results suggest that the metabolites may be used as biomarkers to evaluate the extent of exposure to ClPAHs.

Correlations of (18)F-fluorothymidine uptake with pathological tumour size, Ki-67 and thymidine kinase 1 expressions in primary and metastatic lymph node colorectal cancer foci.

OBJECTIVE: To examine correlations of (18)F-fluorothymidine (FLT) uptake with pathological tumour size and immunohistochemical Ki-67, and thymidine kinase 1 (TK-1) expressions in primary and metastatic node colorectal cancer foci. METHODS: Thirty primary cancers (PCs) and 37 metastatic nodes (MNs) were included. FLT uptake was assessed by visual scores (non-visible: 0-1 and visible: 2-4), standardized uptake value (SUV), and correlated with size, Ki-67, and TK-1. SUV was measured in visible lesions. FLT heterogeneity was assessed by visual scores (no heterogeneous uptake: 0 and heterogeneous uptake: 1-4). RESULTS: Forty-two lesions were visible. The visible group showed significantly higher values than the non-visible group in size, Ki-67, and TK-1 (each p < 0.05). Size correlated significantly with visual score (PC; ρ = 0.74 and MN; ρ = 0.63), SUVmax (PC; ρ = 0.49, and MN; ρ = 0.76), and SUVmean (PC; ρ = 0.40 and MN; ρ = 0.76) (each p < 0.05). Visual score correlated significantly with size (ρ = 0.86), Ki-67max (ρ = 0.35), Ki-67mean (ρ = 0.38), TK-1max (ρ = 0.35) and TK-1mean (ρ = 0.25) (each p < 0.05). No significant correlations were found between FLT uptake and Ki-67 or TK-1 in 42 visible lesions (each p > 0.05). Heterogeneous FLT uptake was noted in 73 % (22/30) of PCs. CONCLUSION: FLT uptake correlated with size. Heterogeneous FLT distribution in colorectal cancers may be one of the causes of weak or lack of FLT uptake/Ki-67 or TK-1 correlation. KEY POINTS: FLT uptake correlated well with tumour size in colorectal cancer. Weak or lack of FLT uptake/Ki-67 and TK-1 correlations were observed. Immunohistochemical Ki-67 and TK-1 expressions are not always correlated with FLT uptake.

Reactions of HOCO radicals through hydrogen-atom hopping utilizing clathrate hydrates as an observational matrix.

The carboxyl (HOCO) radical, which is an important species in atmospheric chemistry and combustion, is an intermediate in the reaction: CO + OH → CO2 + H and serves as a hydrogen donor to the reaction partners. The cis-HOCO radical, one of the ground-state HOCO radicals, is supposed to be decomposed into CO2 and the hydrogen atom by a tunneling effect. In order to prove the hypothesis, we performed electron spin resonance (ESR) measurements to investigate the decay mechanisms of the ground-state HOCO and DOCO radicals in gamma-ray-irradiated CO2 hydrates, which may hold the radicals stably. The ground-state HOCO and DOCO radicals decayed according to a second-order decay model and transformed into formic acid and CO2. The ratio of the decay rate constants of HOCO and DOCO radicals shows a good agreement with that in the kinetic isotope effect for the hydrogen and deuterium abstraction reactions. These results indicate that they react with another HOCO radical in the adjacent hydrate cage without the tunneling effect. This implies that the ground-state HOCO radicals are not decomposed by the tunneling effect but are decayed through reactions with some atoms, molecules, and/or radicals even in the gas phase. In addition, the hydrogen-atom hopping through the temporary hydrogen bonds between the HOCO radical and CO2 results in a seeming diffusion of the HOCO radicals in the CO2 hydrate; this would be an important concept for the studies of the radical diffusions and the supply of hydrogen atoms in gas, liquid, and solid phases.

Imaging discrepancies between magnetic resonance imaging and brain perfusion single-photon emission computed tomography in the diagnosis of Alzheimer's disease, and verification with amyloid positron emission tomography.

BACKGROUND: In the diagnosis of Alzheimer's disease (AD), discrepancies are often observed between magnetic resonance imaging (MRI) and brain perfusion single-photon emission computed tomography (SPECT) findings. MRI, brain perfusion SPECT, and amyloid positron emission tomography (PET) findings were compared in patients with mild cognitive impairment or early AD to clarify the discrepancies between imaging modalities. METHODS: Several imaging markers were investigated, including the cortical average standardized uptake value ratio on amyloid PET, the Z-score of a voxel-based specific regional analysis system for AD on MRI, periventricular hyperintensity grade, deep white matter hyperintense signal grade, number of microbleeds, and three indicators of the easy Z-score imaging system for a specific SPECT volume-of-interest analysis. Based on the results of the regional analysis and the three indicators, we classified patients into four groups and then compared the results of amyloid PET, periventricular hyperintensity grade, deep white matter hyperintense signal grade, and the numbers of microbleeds among the groups. RESULTS: The amyloid deposition was the highest in the group that presented typical AD findings on both the regional analysis and the three indicators. The two groups that showed an imaging discrepancy between the regional analysis and the three indicators demonstrated intermediate amyloid deposition findings compared with the typical and atypical groups. The patients who showed hippocampal atrophy on the regional analysis and atypical AD findings using the three indicators were approximately 60% amyloid-negative. The mean periventricular hyperintensity grade was highest in the typical group. CONCLUSIONS: Patients showing discrepancies between MRI and SPECT demonstrated intermediate amyloid deposition findings compared with patients who showed typical or atypical findings. Strong white matter signal abnormalities on MRI in patients who presented typical AD findings provided further evidence for the involvement of vascular factors in AD.

Machine learning approach using 18F-FDG-PET-radiomic features and the visibility of right ventricle 18F-FDG uptake for predicting clinical events in patients with cardiac sarcoidosis.

OBJECTIVES: To investigate the usefulness of machine learning (ML) models using pretreatment 18F-FDG-PET-based radiomic features for predicting adverse clinical events (ACEs) in patients with cardiac sarcoidosis (CS). MATERIALS AND METHODS: This retrospective study included 47 patients with CS who underwent 18F-FDG-PET/CT scan before treatment. The lesions were assigned to the training (n = 38) and testing (n = 9) cohorts. In total, 49 18F-FDG-PET-based radiomic features and the visibility of right ventricle 18F-FDG uptake were used to predict ACEs using seven different ML algorithms (namely, decision tree, random forest [RF], neural network, k-nearest neighbors, Naïve Bayes, logistic regression, and support vector machine [SVM]) with tenfold cross-validation and the synthetic minority over-sampling technique. The ML models were constructed using the top four features ranked by the decrease in Gini impurity. The AUCs and accuracies were used to compare predictive performances. RESULTS: Patients who developed ACEs presented with a significantly higher surface area and gray level run length matrix run length non-uniformity (GLRLM_RLNU), and lower neighborhood gray-tone difference matrix_coarseness and sphericity than those without ACEs (each, p < 0.05). In the training cohort, all seven ML algorithms had a good classification performance with AUC values of > 0.80 (range: 0.841-0.944). In the testing cohort, the RF algorithm had the highest AUC and accuracy (88.9% [8/9]) with a similar classification performance between training and testing cohorts (AUC: 0.945 vs 0.889). GLRLM_RLNU was the most important feature of the modeling process of this RF algorithm. CONCLUSION: ML analyses using 18F-FDG-PET-based radiomic features may be useful for predicting ACEs in patients with CS.

Diagnosis of metastases from postoperative differentiated thyroid cancer: comparison between FDG and FLT PET/CT studies.

PURPOSE: To compare positron emission tomography (PET)/computed tomography (CT) studies performed with the glucose analog fluorine 18 ((18)F) fluorodeoxyglucose (FDG) and the cell proliferation tracer (18)F fluorothymidine (FLT) in the diagnosis of metastases from postoperative differentiated thyroid cancer. MATERIALS AND METHODS: The institutional ethics review board approved this prospective study. From March 2010 to February 2012, 20 patients (mean age, 53 years; age range, 22-79 years) with postoperative differentiated thyroid cancer underwent both FDG and FLT PET/CT as a staging work-up before radioiodine therapy. In each patient, 28 anatomic areas were set and analyzed for lymph node and distant metastases. The McNemar exact or χ(2) test was used to examine differences in diagnostic indexes in the detection of lymph node and distant metastases between both tracer PET/CT studies. RESULTS: There were 34 lymph node metastases and/or 73 distant metastases (70 metastases in lung and one each in bone, nasopharynx, and brain) in 13 patients. At patient-based analysis, the sensitivity, specificity, and accuracy were 92% (12 of 13 patients), 86% (six of seven patients), and 90% (18 of 20 patients), respectively, for FDG PET/CT and 69% (nine of 13 patients), 29% (two of seven patients), and 55% (11 of 20 patients) for FLT PET/CT. The accuracy of FDG PET/CT was significantly better than that of FLT PET/CT (P = .023). At lesion-based analysis, the sensitivity, specificity, and accuracy for diagnosing lymph node metastases were 85% (29 of 34 lesions), 99.6% (245 of 246 lesions), and 97.9% (274 of 280 lesions), respectively, for FDG PET/CT and 50% (17 of 34 lesions), 90.7% (223 of 246 lesions), and 85.7% (240 of 280 lesions) for FLT PET/CT. The sensitivity, specificity, and accuracy for diagnosing distant metastases were 45% (33 of 73 lesions), 100% (207 of 207 lesions), and 85.7% (240 of 280 lesions), respectively, for FDG PET/CT and 6.8% (five of 73 lesions), 100% (207 of 207 lesions), and 75.7% (212 of 280 lesions) for FLT PET/CT. The sensitivity (P = .002), specificity (P < .001), and accuracy (P < .001) of FDG PET/CT in the diagnosis of lymph node metastases were superior to those of FLT PET, as were the sensitivity (P < .001) and accuracy (P < .001) in the diagnosis of distant metastases. CONCLUSION: FDG PET/CT is superior to FLT PET/CT in the diagnosis of postoperative differentiated thyroid cancer lymph node and distant metastases. Thus, FDG PET/CT is more suitable than FLT PET/CT for examining recurrence of postoperative differentiated thyroid cancer.

Investigation of the provenance of Okinose sand using ESR signals of quartz in granite and granodiorite around Osaka Bay.

A submarine dune on the seabed in the Okinose area of Osaka Bay, Japan, was found to be composed mainly of coarse quartz sand. To investigate the provenance of this sand, quartz extracted from granite and granodiorite sources near Osaka Bay was measured by electron spin resonance; E1', Ti-Li and Al centres were detected in all samples. Although the heat-treated E1' centre was found not to be useful for the present provenance study, the ratio of the signal intensities of the Ti-Li centre to the Al centre classified the potential sources into two groups, based on their likelihood. The results indicated that granite and granodiorite from Awaji Island as well as Rokko granite could be the source of the Okinose sand.

Hydrogen transfer reactions via organic radicals in gamma-irradiated chibaite.

Chibaite, a silica-framework structure with cage-like voids occupied by gaseous molecules, was found in marine sediments. Its formation age could be evaluated using electron spin resonance (ESR) if the radicals formed by natural radiation can be assumed to accumulate over time. To investigate whether hydrogen transfer reactions, where organic radicals withdraw hydrogen atoms from other molecules in adjacent cages, occur in chibaite and affect ESR dating, gamma-irradiated chibaite was measured by ESR. Methyl, ethyl, n-propyl, isopropyl, tert-butyl radicals and hydrogen atoms were created by gamma irradiation at 77 K. The amount of tert-butyl radicals increased around 240 K and the similar amount of the other organic radicals decreased simultaneously, implying that hydrogen transfer reactions occur between isobutane and the organic radicals in chibaite around 240 K and therefore would have no influence on ESR dating because the reactions are completed at the environmental temperature.

Application of 123I-MIBG myocardial maximum standardized uptake value to characterize cardiac function in patients with pheochromocytoma: comparison with echocardiography.

PURPOSE: This study examined the usefulness of the maximum standardized uptake value (SUVmax) of myocardial [123I]-metaiodobenzylguanidine ([123I]-MIBG) to characterize myocardial function by comparing it with echocardiographic parameters in patients with pheochromocytoma. MATERIALS AND METHODS: This study included 18 patients with pheochromocytoma who underwent both planar and [123I]-MIBG single-photon emission computed tomography/computed tomography scans and echocardiography before surgery. Myocardial [123I]-MIBG visibility and SUVmax were compared with echocardiographic parameters related to systolic and diastolic functions. The Mann-Whitney U test, Fisher exact test, or Spearman rank correlation assessed differences or relationships between two quantitative variables. RESULTS: On visual analysis, 6 patients showed normal myocardial [123I]-MIBG uptake, whereas 12 patients showed decreased myocardial [123I]-MIBG uptake. No patients showed systolic dysfunction. A significant difference was observed in the incidence of diastolic dysfunction between the groups with normal and decreased uptake (p = 0.009), and left ventricular (LV) diastolic dysfunction was observed in 9 (75%) of 12 patients with decreased myocardial uptake. The myocardial SUVmax was significantly lower in 9 patients with LV diastolic dysfunction than in 9 patients with normal cardiac function (1.67 ± 0.37 vs. 3.03 ± 1.38, p = 0.047). Myocardial SUVmax was positively correlated with septal e' (early diastolic velocity of septal mitral annulus) (ρ = 0.51, p = 0.031) and negatively correlated with the septal E/e' ratio (early mitral E-velocity to early diastolic velocity of septal mitral annulus; ρ = - 0.64, p = 0.004), respectively. CONCLUSIONS: LV diastolic dysfunction was inversely related to myocardial [123I]-MIBG uptake. Myocardial [123I]-MIBG SUVmax may be useful for characterizing cardiac function in patients with pheochromocytoma. Second abstract. The semiquantitative analysis using the myocardial SUVmax in 123I-MIBG SPECT/CT was found to be potentially useful for characterizing cardiac function in patients with pheochromocytoma.

The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [18F]-FDG-PET/CT Radiomic Features for Predicting Prognosis in Hypopharyngeal Cancer.

PURPOSE: To examine whether the machine learning (ML) analyses using clinical and pretreatment 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography ([18F]-FDG-PET)-based radiomic features were useful for predicting prognosis in patients with hypopharyngeal cancer. PROCEDURES: This retrospective study included 100 patients with hypopharyngeal cancer who underwent [18F]-FDG-PET/X-ray computed tomography (CT) before treatment, and these patients were allocated to the training (n=80) and validation (n=20) cohorts. Eight clinical (age, sex, histology, T stage, N stage, M stage, UICC stage, and treatment) and 40 [18F]-FDG-PET-based radiomic features were used to predict disease progression. A feature reduction procedure based on the decrease of the Gini impurity was applied. Six ML algorithms (random forest, neural network, k-nearest neighbors, naïve Bayes, logistic regression, and support vector machine) were compared using the area under the receiver operating characteristic curve (AUC). Progression-free survival (PFS) was assessed using Cox regression analysis. RESULTS: The five most important features for predicting disease progression were UICC stage, N stage, gray level co-occurrence matrix entropy (GLCM_Entropy), gray level run length matrix run length non-uniformity (GLRLM_RLNU), and T stage. Patients who experienced disease progression displayed significantly higher UICC stage, N stage, GLCM_Entropy, GLRLM_RLNU, and T stage than those without progression (each, p<0.001). In both cohorts, the logistic regression model constructed by these 5 features was the best performing classifier (training: AUC=0.860, accuracy=0.800; validation: AUC=0.803, accuracy=0.700). In the logistic regression model, 5-year PFS was significantly higher in patients with predicted non-progression than those with predicted progression (75.8% vs. 8.3%, p<0.001), and this model was only the independent factor for PFS in multivariate analysis (hazard ratio = 3.22; 95% confidence interval = 1.03-10.11; p=0.045). CONCLUSIONS: The logistic regression model constructed by UICC, T and N stages and pretreatment [18F]-FDG-PET-based radiomic features, GLCM_Entropy, and GLRLM_RLNU may be the most important predictor of prognosis in patients with hypopharyngeal cancer.

The usefulness of machine-learning-based evaluation of clinical and pretreatment 18F-FDG-PET/CT radiomic features for predicting prognosis in patients with laryngeal cancer.

OBJECTIVE: To examine whether machine learning (ML) analyses involving clinical and 18F-FDG-PET-based radiomic features are helpful in predicting prognosis in patients with laryngeal cancer. METHODS: This retrospective study included 49 patients with laryngeal cancer who underwent18F-FDG-PET/CT before treatment, and these patients were divided into the training (n = 34) and testing (n = 15) cohorts.Seven clinical (age, sex, tumor size, T stage, N stage, Union for International Cancer Control stage, and treatment) and 40 18F-FDG-PET-based radiomic features were used to predict disease progression and survival. Six ML algorithms (random forest, neural network, k-nearest neighbors, naïve Bayes, logistic regression, and support vector machine) were used for predicting disease progression. Two ML algorithms (cox proportional hazard and random survival forest [RSF] model) considering for time-to-event outcomes were used to assess progression-free survival (PFS), and prediction performance was assessed by the concordance index (C-index). RESULTS: Tumor size, T stage, N stage, GLZLM_ZLNU, and GLCM_Entropy were the five most important features for predicting disease progression.In both cohorts, the naïve Bayes model constructed by these five features was the best performing classifier (training: AUC = 0.805; testing: AUC = 0.842). The RSF model using the five features (tumor size, GLZLM_ZLNU, GLCM_Entropy, GLRLM_LRHGE and GLRLM_SRHGE) exhibited the highest performance in predicting PFS (training: C-index = 0.840; testing: C-index = 0.808). CONCLUSION: ML analyses involving clinical and 18F-FDG-PET-based radiomic features may help predict disease progression and survival in patients with laryngeal cancer. ADVANCES IN KNOWLEDGE: ML approach using clinical and 18F-FDG-PET-based radiomic features has the potential to predict prognosis of laryngeal cancer.

Application of Machine Learning Analyses Using Clinical and [18F]-FDG-PET/CT Radiomic Characteristics to Predict Recurrence in Patients with Breast Cancer.

PURPOSE: To develop and identify machine learning (ML) models using pretreatment clinical and 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography ([18F]-FDG-PET)-based radiomic characteristics to predict disease recurrences in patients with breast cancers who underwent surgery. PROCEDURES: This retrospective study included 112 patients with 118 breast cancer lesions who underwent [18F]-FDG-PET/ X-ray computed tomography (CT) preoperatively, and these lesions were assigned to training (n=95) and testing (n=23) cohorts. A total of 12 clinical and 40 [18F]-FDG-PET-based radiomic characteristics were used to predict recurrences using 7 different ML algorithms, namely, decision tree, random forest (RF), neural network, k-nearest neighbors, naive Bayes, logistic regression, and support vector machine (SVM) with a 10-fold cross-validation and synthetic minority over-sampling technique. Three different ML models were created using clinical characteristics (clinical ML models), radiomic characteristics (radiomic ML models), and both clinical and radiomic characteristics (combined ML models). Each ML model was constructed using the top ten characteristics ranked by the decrease in Gini impurity. The areas under ROC curves (AUCs) and accuracies were used to compare predictive performances. RESULTS: In training cohorts, all 7 ML algorithms except for logistic regression algorithm in the radiomics ML model (AUC = 0.760) achieved AUC values of >0.80 for predicting recurrences with clinical (range, 0.892-0.999), radiomic (range, 0.809-0.984), and combined (range, 0.897-0.999) ML models. In testing cohorts, the RF algorithm of combined ML model achieved the highest AUC and accuracy (95.7% (22/23)) with similar classification performance between training and testing cohorts (AUC: training cohort, 0.999; testing cohort, 0.992). The important characteristics for modeling process of this RF algorithm were radiomic GLZLM_ZLNU and AJCC stage. CONCLUSIONS: ML analyses using both clinical and [18F]-FDG-PET-based radiomic characteristics may be useful for predicting recurrence in patients with breast cancers who underwent surgery.

Interlaboratory comparison of electron paramagnetic resonance tooth enamel dosimetry with investigations of the dose responses of the standard samples.

A total of seven Japanese laboratories participated in an intercomparison study to estimate the dose given to tooth enamel samples, using the electron spin resonance method. Each of four of the participating laboratories prepared a set of tooth enamel samples, using the electron spin resonance method. Four of the participating laboratories each prepared a set of tooth enamel samples, consisting of seven standard aliquots irradiated from 100 to 2000 mGy and three samples with an 'unknown' dose between 140 and 960 mGy, were intended to eliminate bias from sample preparation. Although not all seven laboratories measured all four sets of samples, the major finding was that systematic biases in estimating doses may be caused by differences in laboratory measurements rather than by the enamel extracting procedures. When doses were averaged by measurements made by multiple laboratories, the averaged values were close to the actual values. Scattering in the intercepts in the standard dose response would be a serious problem in actual dosimetry where no background sample is available.