Chemical Shift-Encoded MRI of the Lumbar Vertebral Bone Marrow for Detecting Osteoporosis With Low Trabecular Bone Quality in Patients With Breast Cancer Receiving Aromatase Inhibitors.

BACKGROUND: Osteoporosis with low trabecular bone quality (OLB) in patients with breast cancer receiving aromatase inhibitor (AI) therapy is associated with an increased risk of vertebral fractures. The capability of chemical shift-encoded MRI (CSE-MRI) in detecting OLB needs to be investigated. PURPOSE: To assess the diagnostic performance of proton density fat fraction (PDFF) and R2* measurements from CSE-MRI for detecting OLB in postmenopausal women with breast cancer undergoing AI therapy. STUDY TYPE: Prospective. POPULATION: 126 postmenopausal females (mean age: 69.5 ± 8.8 years) receiving AIs (average period: 41.6 ± 26.5 months) after breast cancer surgery. FIELD STRENGTH/SEQUENCE: 1.5-T, three-dimensional CSE-MRI (six echoes), T1-weighted Dixon, short tau inversion recovery, and diffusion-weighted images. ASSESSMENT: Both CSE-MRI and dual-energy x-ray absorptiometry were performed on the same day. Measurements included averaged PDFF, R2*, bone mineral density (BMD), and trabecular bone score (TBS) from L1 to L4 vertebrae. A T-score ≤ -2.5 from BMD measurements indicated osteoporosis, whereas T-scores of ≤ - 2.5 plus TBS ≤-3.7 indicated OLB. The diagnostic performance of PDFF, R2*, and the combination of PDFF and R2* for identifying osteoporosis or OLB was assessed. STATISTICAL TESTS: Student's t-test; Mann-Whitney U test; χ2 or Fisher exact tests; Pearson correlation; multivariate analysis; Receiver operating characteristic (ROC) analysis with the area under the curve (AUC); logistic regression model; intraclass correlation coefficient. A P-value <0.05 was considered statistically significant. RESULTS: For detecting osteoporosis, AUC values were 0.59 (PDFF), 0.66 (R2*), and 0.65 (combined PDFF and R2*). Significant mean differences were noted between patients with and without OLB for PDFF (66.11 ± 5.36 vs. 57.49 ± 6.43) and R2* (46.62 ± 9.24 vs. 63.36 ± 12.44). AUC values for detecting OLB were 0.75 (PDFF), 0.82 (R2*), and 0.84 (combined PDFF and R2*). DATA CONCLUSION: R2* may perform better than PDFF for identifying OLB in patients with breast cancer receiving AIs. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 4.

Deep learning-based noise reduction for coronary CT angiography: using four-dimensional noise-reduction images as the ground truth.

BACKGROUND: To assess low-contrast areas such as plaque and coronary artery stenosis, coronary computed tomography angiography (CCTA) needs to provide images with lower noise without increasing radiation doses. PURPOSE: To develop a deep learning-based noise-reduction method for CCTA using four-dimensional noise reduction (4DNR) as the ground truth for supervised learning. MATERIAL AND METHODS: \We retrospectively collected 100 retrospective ECG-gated CCTAs. We created 4DNR images using non-rigid registration and weighted averaging three timeline CCTA volumetric data with intervals of 50 ms in the mid-diastolic phase. Our method set the original reconstructed image as the input and the 4DNR as the target image and obtained the noise-reduced image via residual learning. We evaluated the objective image quality of the original and deep learning-based noise-reduction (DLNR) images based on the image noise of the aorta and the contrast-to-noise ratio (CNR) of the coronary arteries. Further, a board-certified radiologist evaluated the blurring of several heart structures using a 5-point Likert scale subjectively and assigned a coronary artery disease reporting and data system (CAD-RADS) category independently. RESULTS: DLNR CCTAs showed 64.5% lower image noise (P < 0.001) and achieved a 2.9 times higher CNR of coronary arteries than that in original images, without significant blurring in subjective comparison (P > 0.1). The intra-observer agreement of CAD-RADS in the DLNR image was excellent (0.87, 95% confidence interval = 0.77-0.99) with original CCTAs. CONCLUSION: Our DLNR method supervised by 4DNR significantly reduced the image noise of CCTAs without affecting the assessment of coronary stenosis.

Generative adversarial network-based post-processed image super-resolution technology for accelerating brain MRI: comparison with compressed sensing.

BACKGROUND: It is unclear whether deep-learning-based super-resolution technology (SR) or compressed sensing technology (CS) can accelerate magnetic resonance imaging (MRI) . PURPOSE: To compare SR accelerated images with CS images regarding the image similarity to reference 2D- and 3D gradient-echo sequence (GRE) brain MRI. MATERIAL AND METHODS: We prospectively acquired 1.3× and 2.0× faster 2D and 3D GRE images of 20 volunteers from the reference time by reducing the matrix size or increasing the CS factor. For SR, we trained the generative adversarial network (GAN), upscaling the low-resolution images to the reference images with twofold cross-validation. We compared the structural similarity (SSIM) index of accelerated images to the reference image. The rate of incorrect answers of a radiologist discriminating faster and reference image was used as a subjective image similarity (ISM) index. RESULTS: The SR demonstrated significantly higher SSIM than the CS (SSIM=0.9993-0.999 vs. 0.9947-0.9986; P < 0.001). In 2D GRE, it was challenging to discriminate the SR image from the reference image, compared to the CS (ISM index 40% vs. 17.5% in 1.3×; P = 0.039 and 17.5% vs. 2.5% in 2.0×; P = 0.034). In 3D GRE, the CS revealed a significantly higher ISM index than the SR (22.5% vs. 2.5%; P = 0.011) in 2.0 × faster images. However, the ISM index was identical for the 2.0× CS and 1.3× SR (22.5% vs. 27.5%; P = 0.62) with comparable time costs. CONCLUSION: The GAN-based SR outperformed CS in image similarity with 2D GRE for MRI acceleration. In addition, CS was more advantageous in 3D GRE than SR.

Applicability Evaluation of Full-Reference Image Quality Assessment Methods for Computed Tomography Images.

Image quality assessments (IQA) are an important task for providing appropriate medical care. Full-reference IQA (FR-IQA) methods, such as peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), are often used to evaluate imaging conditions, reconstruction conditions, and image processing algorithms, including noise reduction and super-resolution technology. However, these IQA methods may be inapplicable for medical images because they were designed for natural images. Therefore, this study aimed to investigate the correlation between objective assessment by some FR-IQA methods and human subjective assessment for computed tomography (CT) images. For evaluation, 210 distorted images were created from six original images using two types of degradation: noise and blur. We employed nine widely used FR-IQA methods for natural images: PSNR, SSIM, feature similarity (FSIM), information fidelity criterion (IFC), visual information fidelity (VIF), noise quality measure (NQM), visual signal-to-noise ratio (VSNR), multi-scale SSIM (MSSSIM), and information content-weighted SSIM (IWSSIM). Six observers performed subjective assessments using the double stimulus continuous quality scale (DSCQS) method. The performance of IQA methods was quantified using Pearson's linear correlation coefficient (PLCC), Spearman rank order correlation coefficient (SROCC), and root-mean-square error (RMSE). Nine FR-IQA methods developed for natural images were all strongly correlated with the subjective assessment (PLCC and SROCC > 0.8), indicating that these methods can apply to CT images. Particularly, VIF had the best values for all three items, PLCC, SROCC, and RMSE. These results suggest that VIF provides the most accurate alternative measure to subjective assessments for CT images.

A Triplet/Singlet Ground-State Switch via the Steric Inhibition of Conjugation in 4,6-Bis(trifluoromethyl)-1,3-phenylene Bisnitroxide.

Ground triplet 4,6-bis(trifluoromethyl)-1,3-phenylene bis(tert-butyl nitroxide) (TF2PBN) reacted with [Y(hfac)3(H2O)2] (hfac = 1,1,1,5,5,5-hexafluoropentane-2,4-dionate), affording a doubly hydrogen-bonded adduct [Y(hfac)3(H2O)2(TF2PBN)]. The biradical was recovered from the adduct through recrystallization. Crystallographic analysis indicates that the torsion angles (|θ| ≤ 90°) between the benzene ring and nitroxide groups were 74.9 and 84.8° in the adduct, which are larger than those of the starting material TF2PBN. Steric congestion due to o-trifluoromethyl groups gives rise to the reduction of π-conjugation. Two hydrogen bonds enhance this deformation. Susceptometry of the adduct indicates a ground singlet with 2J/kB = -128(2) K, where 2J corresponds to the singlet-triplet gap. The observed magneto-structure relation is qualitatively consistent with Rajca's pioneering work. A density functional theory calculation at the UB3LYP/6-311+G(2d,p) level using the atomic coordinates determined provided a result of 2J/kB = -162.3 K for the adduct, whilst the corresponding calculation on intact TF2PBN provided +87.2 K. After a comparison among a few known compounds, the 2J vs. |θ| plot shows a negative slope with a critical torsion of 65(3)°. The ferro- and antiferromagnetic coupling contributions are balanced in TF2PBN, being responsible for ground-state interconversion by means of small structural perturbation like hydrogen bonds.

Deep Learning-based Post Hoc CT Denoising for Myocardial Delayed Enhancement.

Background To improve myocardial delayed enhancement (MDE) CT, a deep learning (DL)-based post hoc denoising method supervised with averaged MDE CT data was developed. Purpose To assess the image quality of denoised MDE CT images and evaluate their diagnostic performance by using late gadolinium enhancement (LGE) MRI as a reference. Materials and methods MDE CT data obtained by averaging three acquisitions with a single breath hold 5 minutes after the contrast material injection in patients from July 2020 to October 2021 were retrospectively reviewed. Preaveraged images obtained in 100 patients as inputs and averaged images as ground truths were used to supervise a residual dense network (RDN). The original single-shot image, standard averaged image, RDN-denoised original (DLoriginal) image, and RDN-denoised averaged (DLave) image of holdout cases were compared. In 40 patients, the CT value and image noise in the left ventricular cavity and myocardium were assessed. The segmental presence of MDE in the remaining 40 patients who underwent reference LGE MRI was evaluated. The sensitivity, specificity, and accuracy of each type of CT image and the improvement in accuracy achieved with the RDN were assessed using odds ratios (ORs) estimated with the generalized estimation equation. Results Overall, 180 patients (median age, 66 years [IQR, 53-74 years]; 107 men) were included. The RDN reduced image noise to 28% of the original level while maintaining equivalence in the CT values (P < .001 for all). The sensitivity, specificity, and accuracy of the original images were 77.9%, 84.4%, and 82.3%, of the averaged images were 89.7%, 87.9%, and 88.5%, of the DLoriginal images were 93.1%, 87.5%, and 89.3%, and of the DLave images were 95.1%, 93.1%, and 93.8%, respectively. DLoriginal images showed improved accuracy compared with the original images (OR, 1.8 [95% CI: 1.2, 2.9]; P = .011) and DLave images showed improved accuracy compared with the averaged images (OR, 2.0 [95% CI: 1.2, 3.5]; P = .009). Conclusion The proposed denoising network supervised with averaged CT images reduced image noise and improved the diagnostic performance for myocardial delayed enhancement CT. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Vannier and Wang in this issue.

Long-term effects of safinamide adjunct therapy on levodopa-induced dyskinesia in Parkinson's disease: post-hoc analysis of a Japanese phase III study.

This post-hoc analysis investigated the long-term effects of safinamide on the course of dyskinesia and efficacy outcomes using data from a phase III, open-label 52-week study of safinamide 50 or 100 mg/day in Japanese patients with Parkinson's disease (PD) with wearing-off. Patients (N = 194) were grouped using the UPDRS Part IV item 32: with and without pre-existing dyskinesia (pre-D subgroup; item 32 > 0 at baseline [n = 81], without pre-D subgroup; item 32 = 0 at baseline [n = 113]). ON-time with troublesome dyskinesia (ON-TD) increased significantly from baseline to Week 4 in the pre-D subgroup (+ 0.25 ± 0.11 h [mean ± SE], p = 0.0355) but gradually decreased up to Week 52 (change from baseline: - 0.08 ± 0.17 h, p = 0.6224); ON-TD did not change significantly in the Without pre-D subgroup. UPDRS Part IV item 32 score increased significantly at Week 52 compared with baseline in the Without pre-D subgroup, but no UPDRS Part IV dyskinesia related-domains changed in the pre-D subgroup. Both subgroups improved in ON-time without TD, UPDRS Part III, and Part II [OFF-phase] scores. The cumulative incidence of new or worsening dyskinesia (adverse drug reaction) at Week 52 was 32.5 and 5.0% in the pre-D and Without pre-D subgroups, respectively. This study suggested that safinamide led to short-term increasing dyskinesia but may be not associated with marked dyskinesia at 1-year follow-up in patients with pre-existing dyskinesia, and that it improved motor symptoms regardless of the presence or absence of dyskinesia at baseline. Further studies are warranted to investigate this association in more details.Trial registration: JapicCTI-153057 (Registered: 2015/11/02).

Rare-Earth (RE = Y, Gd, Tb, Dy, Ho, and Er) Chains Bridged with a Triplet Biradical and Magnetic Hysteresis Recorded for RE = Tb.

Complex formation of 5-tert-butyl-1,3-phenylene bis(tert-butyl nitroxide) and rare-earth (RE) metal ions gave a linear chain where each nitroxide O atom is directly bonded to the RE ion. The bridge was proven to be a ground triplet molecule in the complexes. A hysteresis loop was recorded below 2.8 K as a single-chain magnet for the RE = Tb derivative.

Ferromagnetic 2p-2p and 4f-2p Couplings in a Macrocycle from Two Biradicals and Two Gadolinium(III) Ions.

A new ground triplet biradical 2',4',6'-triisopropylbiphenyl-3,5-diyl bis(tert-butyl nitroxide) (iPr3BPBN) was prepared and characterized by means of room-temperature ESR spectroscopy displaying a zero-field splitting pattern together with a half-field signal. Complex formation with gadolinium(III) 1,1,1,5,5,5-hexafluoropentane-2,4-dionate (hfac) afforded a macrocycle [{Gd(hfac)3(µ-iPr3BPBN)}2]. As the X-ray crystallographic analysis clarified, the biradical serves as a bridging ligand, giving a 16-membered ring, where each nitroxide radical oxygen atom is directly bonded to a Gd3+ ion. The magnetic study revealed that the iPr3BPBN bridge behaved as a practically triplet biradical and that the Gd3+-radical magnetic coupling was weakly ferromagnetic. The exchange parameters were estimated as 2jrad-rad/kB > 300 K and 2JGd-rad/kB = 1.2 K in the H = −2J S1•S2 convention. The DFT calculation based on the atomic coordinates clarified the ground triplet nature in metal-free iPr3BPBN and the enhanced triplet character upon coordination. The calculation also suggests that ferromagnetic coupling would be favorable when the Gd-O-N-C(sp2) torsion comes around 100°. The present results are compatible with the proposed magneto-structure relationship on the nitroxide-Gd compounds.

Utilizing Graphical Analysis of Chest Radiographs for Primary Screening of Osteoporosis.

Background and Objectives: Osteoporosis is a major risk of fractures, harming patients' quality of life. Dual-energy X-ray absorptiometry (DXA), which can detect osteoporosis early, is too expensive to be conducted on a regular basis. Therefore, we aimed to evaluate a screening method using chest radiographs developed in Japan applied to another population. Materials and Methods: Fifty-five patients who had a chest radiograph and DXA and applied within three months of each test were recruited from the patient database of Semmelweis University (Budapest, Hungary). Graphical analysis of the chest radiographs was conducted to identify the ratio of the cortical bone in the clavicle of each patient. Two researchers performed the analysis, and multiple regression was conducted to determine the bone mineral density of each patient provided by DXA. Results: The Pearson correlation between two examiners' determinations of the cortical bone ratio was 0.769 (p < 0.001). The multiple regression model proved to be statistically significant in identifying osteoporosis, but the model adopted for the Hungarian population was different compared to the Japanese population. Conclusions: This simple, economic Japanese graphical analysis method for chest radiographs may be feasible in detecting osteoporosis. Further studies with a larger population of patients with greater variety of ethnicity would be of value in improving the accuracy of this model.

Strong Antiferromagnetic Interaction in a Gadolinium(III) Complex with Methoxy-TEMPO Radical: A Relation between the Coupling and the Gd-O-N Angle.

A new compound [Gd(hfac)3(MeOTEMPO)(MeOH)] (MeOTEMPO = 4-methoxy-2,2,6,6-tetramethylpiperidin-1-oxyl) was prepared. From the X-ray crystal structure analysis, the Gd-O-N angle is 170.9(3)°. The magnetic study clarified the Gd3+-radical interaction with 2J/kB = -26.6(3) K (in the H = -2JS1·S2 convention), which corresponds to one of the strongest antiferromagnetic couplings in the Gd-nitroxide systems. Wider Gd-O-N angles seem to favor stronger antiferromagnetic couplings.

Radiomics-Based Machine Learning Classification for Glioma Grading Using Diffusion- and Perfusion-Weighted Magnetic Resonance Imaging.

OBJECTIVE: The aim of this study was to evaluate various radiomics-based machine learning classification models using the apparent diffusion coefficient (ADC) and cerebral blood flow (CBF) maps for differentiating between low-grade gliomas (LGGs) and high-grade gliomas (HGGs). METHODS: Fifty-two glioma patients, including 18 LGGs (grade II) and 34 HGGs (grade III/IV), were examined using a 3.0-T magnetic resonance scanner. The ADC and CBF maps were obtained from diffusion-weighted imaging and pseudo-continuous arterial spin labeling perfusion-weighted imaging, respectively. A total of 91 radiomic features were extracted from each of the tumor volume on the ADC and CBF maps. We constructed 4 types of machine learning classifiers based on (1) least absolute shrinkage and selection operator regularized logistic regression (LASSO-LR), (2) random forest (RF), (3) support vector machine (SVM) with the radial basis function kernel (SVM-RBF), and (4) SVM with the linear kernel (SVM-L). A training set with 36 gliomas (70%) was used to select the important radiomic features and train each model using 5-fold cross-validation. The remaining 16 gliomas (30%) were used as a test set. Receiver operating characteristic analysis was performed to evaluate the model performance. RESULTS: A radiomic feature, ADC first-order-based skewness, was selected as an important variable in all classification models. According to the receiver operating characteristic analysis, the areas under the curve of the LASSO-LR, RF, SVM-RBF, and SVM-L models for the training set were 0.965, 1.000, 0.979, and 0.969, respectively. For the test set, the areas under the curve of the LASSO-LR, RF, SVM-RBF, and SVM-L models were 0.883, 0.917, 0.717, and 0.917, respectively. All classification models showed sufficient diagnostic performance on the test set. CONCLUSIONS: Radiomics-based machine learning classifiers using the quantitative ADC and CBF maps are useful for differentiating HGGs from LGGs.

Odd-Even Effect on the Spin-Crossover Temperature in Iron(II) Complex Series Involving an Alkylated or Acyloxylated Tripodal Ligand.

In the context of magneto-structural study, a relatively short alkyl group was introduced to anionic spin-crossover (SCO) building blocks based on [Fe(py3CR)(NCS)3]-, where py3CR stands for tris(2-pyridyl)methyl derivatives. The linear alkyl and acyloxyl derivatives of Me4N[Fe(py3CR)(NCS)3] with R = CnH2n+1 (n = 1-7) and CnH2n+1CO2 (n = 1-6) were synthesized, and the magnetic study revealed that all the compounds investigated here exhibited SCO. The SCO temperature (T1/2) varied in 289-338 K for the alkylated compounds, and those of the acyloxylated ones were lower with a narrower variation width (T1/2 = 216-226 K). The crystal structures of the former with n = 3, 4, and 5 and the latter with n = 1, 4, 5, and 6 were determined, and various molecular arrangements were characterized. There is no structural evidence for a molecular fastener effect. The plots on T1/2 against n displayed a pronounced odd-even effect; the SCO temperatures of the homologues with even n are relatively higher than those of the homologues with odd n. The odd-even effect on T1/2 may be related with the entropy difference across the SCO, rather than crystal field modification or intermolecular interaction. The present work will help molecular design to fine-tune T1/2 by means of simple chemical modification like alkylation and acyloxylation.

A Hidden Coordination-Bond Torsional Deformation as a Sign of Possible Spin Transition in Nickel(II)-Bis(nitroxide) Compounds.

Complex formation of nickel(II) tetrafluoroborate and tert-butyl 5-phenyl-2-pyridyl nitroxide (phpyNO) in the presence of sodium cyanate gave a discrete molecule [Ni(phpyNO)2(X)2] (X = NCO). The Ni-O-N-Csp2 torsion angles were reduced on heating; 33.5(5)° and 36.2(4)° at 100 K vs. 25.7(10)° and 32.3(11)° at 400 K. The magnetic behavior was almost diamagnetic below ca. 100 K, and the χmT value reached 1.04 cm3 K mol-1 at 400 K. An analysis using the van't Hoff equation indicates a possible spin transition at T1/2 >> 400 K. Density functional theory calculation shows that the singlet-quintet energy gap decreases as the structural change from 100 to 400 K. The geometry optimization results suggest that the diamagnetic state has the Ni-O-N-Csp2 torsion angles of 32.7° while the Stotal = 2 state has those of 11.9°. The latter could not be experimentally observed even at 400 K. After overviewing the results on the known X = Br, Cl, and NCS derivatives, the magnetic behavior is described in a common phase diagram. The Br and Cl compounds undergo the energy level crossing of the high-/low-spin states, but the NCS and NCO compounds do not in a conventional experimental temperature range. The spin transition mechanism in this series involves the exchange coupling switch between ferro- and antiferromagnetic interactions, corresponding to the high- and low-spin phases, respectively.

High-Spin and Incomplete Spin-Crossover Polymorphs in Doubly Chelated [Ni(L)2Br2] (L = tert-Butyl 5-Phenyl-2-pyridyl Nitroxide).

Complexation of nickel(II) bromide with tert-butyl 5-phenyl-2-pyridyl nitroxide (phpyNO) gave two morphs of doubly chelated [Ni(phpyNO)2Br2] as a 2p-3d-2p heterospin triad. The α phase crystallizes in the orthorhombic space group Pbcn. An asymmetric unit involves a half-molecule. The torsion angle around Ni-O-N-C2py is as small as 6.5(3)° at 100 K and 7.0(6)° at 400 K, guaranteeing an orthogonal arrangement between the magnetic radical π* and metal 3dx2-y2 and 3dz2 orbitals. Magnetic study revealed the high-spin ground state with the exchange coupling constant 2J/kB = +288(5) K, on the basis of a symmetrical spin Hamiltonian. The ß phase crystallizes in the monoclinic space group P21/n. The whole molecule is an independent unit. The Ni-O-N-C2py torsion angles are 24.2(6) and 37.2(5)° at 100 K and 10.4(7) and 25.9(6)° at 400 K. A magnetic study revealed a very gradual and nonhysteretic spin transition. An analysis based on the van't Hoff equation gave a successful fit with the spin-crossover temperature of 134(1) K, although the susceptibility did not reach the theoretical high-spin value at 400 K. Density functional theory calculation on the ß phase showed ground Stotal = 0 in the low-temperature structure while Stotal = 2 in the high-temperature structure, supporting the synchronized exchange coupling switch on both sides. Consequently, the ß phase can be recognized as an "incomplete spin crossover" material, as a result of conflicting thermal depopulation effects in a high-temperature region.

Iron(II) and 1,1,1-Tris(2-pyridyl)nonadecane Complex Showing an Order-Disorder-Type Structural Transition and Spin-Crossover Synchronized over Both Conformers.

The title compound (Me4N)[Fe{(2-py)3C- n-C18H37}(NCS)3] having a C18 chain underwent spin-crossover (SCO). There are two crystallographically independent molecules in a triclinic cell at 100 K but only one in a monoclinic cell at 300 K. The complex showed a gradual one-step SCO in the same temperature region as that of the structural transition. The SCO is supported with the 57Fe Mössbauer spectroscopy. The molecules are differentiated on cooling, but the SCO was synchronized.

Current prescription status of antihypertensive drugs in Japanese patients with hypertension: Analysis by type of comorbidities.

In 2014, the Japanese Society of Hypertension (JSH) issued revised guidelines for hypertension management. To assess adherence to the guidelines, this retrospective study evaluated the real-world status of antihypertensive drug prescribing for Japanese patients with hypertension, classified by comorbidity: diabetes mellitus, dyslipidemia, gout/hyperuricemia and renal diseases. Data on 59,867 hypertensive patients who received their first prescription for antihypertensive therapy between April 2014 and March 2015, were obtained from a medical insurance claims database for hospitals participating in the Diagnosis Procedure Combination/Per-Diem payment system. The most common drugs prescribed for each comorbidity subgroup were calcium channel blockers (CCBs) and angiotensin II receptor blockers (ARBs), with prescription rates of around 60-70%. Contrary to JSH recommendations, diuretics and angiotensin-converting enzyme inhibitors were prescribed less often than ß-blockers. Whereas diabetes mellitus is a compelling indication for use of renin-angiotensin system inhibitors, CCBs were commonly prescribed in this subgroup. The treatment pattern for patients with comorbid dyslipidemia closely resembled that for the overall patient population. Loop diuretics were prescribed more frequently for patients with renal diseases or gout/hyperuricemia than for those with diabetes mellitus or dyslipidemia. Although antihypertensive drug prescribing varied by comorbidity, JSH 2014 guidelines appeared not to be incorporated adequately into actual clinical practice.

Enhancement of ghrelin-signaling system by Rikkunshi-To attenuates teriparatide-induced pica in rats.

Teriparatide is clinically used for the treatment of osteoporosis; however, nausea is often observed in patients. Its insufficient control affects the ability to continue teriparatide therapy. Rikkunshi-To (RKT), a traditional Japanese herbal medicine, improves the gastrointestinal function via activation of the ghrelin-signaling system. We investigated the therapeutic effects of RKT on teriparatide-induced nausea in rats and the involvement of ghrelin in these effects. We previously reported that ovariectomized rats showed pica (kaolin ingestion), a behavior that can be used to assess nausea in rats, after the subcutaneous administration of teriparatide; thus, the behavior was used as an index of nausea. Ovariectomized rats were fed diets with or without RKT (1%) for 2 weeks, and then they received the subcutaneous injection of teriparatide (400 µg/kg). Teriparatide significantly increased the incidence of pica, while suppressing intestinal motility and plasma ghrelin levels in rats fed normal diets; however, rats fed diets with RKT showed improvements in all of the teriparatide-induced adverse reactions. These therapeutic effects were antagonized by a ghrelin receptor antagonist ([D-Lys3]-GHRP-6; 200 nmol/rat). These findings suggest that the enhancement of ghrelin-signaling is involved in RKT's therapeutic effect, and that RKT is a potentially useful treatment for teriparatide-induced nausea.

Application of Super-Resolution Convolutional Neural Network for Enhancing Image Resolution in Chest CT.

In this study, the super-resolution convolutional neural network (SRCNN) scheme, which is the emerging deep-learning-based super-resolution method for enhancing image resolution in chest CT images, was applied and evaluated using the post-processing approach. For evaluation, 89 chest CT cases were sampled from The Cancer Imaging Archive. The 89 CT cases were divided randomly into 45 training cases and 44 external test cases. The SRCNN was trained using the training dataset. With the trained SRCNN, a high-resolution image was reconstructed from a low-resolution image, which was down-sampled from an original test image. For quantitative evaluation, two image quality metrics were measured and compared to those of the conventional linear interpolation methods. The image restoration quality of the SRCNN scheme was significantly higher than that of the linear interpolation methods (p < 0.001 or p < 0.05). The high-resolution image reconstructed by the SRCNN scheme was highly restored and comparable to the original reference image, in particular, for a ×2 magnification. These results indicate that the SRCNN scheme significantly outperforms the linear interpolation methods for enhancing image resolution in chest CT images. The results also suggest that SRCNN may become a potential solution for generating high-resolution CT images from standard CT images.