Prediction of histologic grade of hepatocellular carcinoma using dual-layer spectral-detector computed tomography (CT): comparison of two region of interest plotting methods.

Background: Multi-parameter imaging technology, which is based on substance separation, helps to predict the pathological grade of tumors. When using dual-layer spectral-detector computed tomography (DLCT) to quantify tumor properties, different methods of placing regions of interest (ROIs) directly impact the measurement of parameters, thus affecting the clinical diagnosis of lesions. Consequently, in this study, we aimed to compare the performance of 2 different ROI plotting methods on DLCT in differentiating the histologic grade of hepatocellular carcinoma (HCC). Methods: This retrospective study included 48 consecutive patients with pathologically confirmed HCC, who underwent DLCT from May 2022 to March 2023. The attenuation value of conventional computed tomography (CT), electron density relative to water (EDW), normalized effective atomic number (NZeff), and normalized iodine density (NID) were measured by 2 radiologists using the conventional planar sketching (PS) method and the volumetric analysis method, respectively. The differences in parameters between the arterial phase (AP) and venous phase (VP) were calculated for each parameter (∆CT, ∆EDW, ∆NZeff, ∆NID). We used 2-sample t-test or Mann-Whitney U test was used to compare the differences in parameters between the 2 methods. Spearman correlation analysis was used to determine the correlation between each parameter and histologic grade. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance. Results: The mean values for the spectral quantitative parameters (CTAP, NZeffAP, NIDAP) and the difference between the arterial phase and venous phase (AP-VP) of parameters (∆CT, ∆EDW, ∆NZeff) measured using the volumetric analysis method were significantly lower than those of the PS method (P<0.05). For the ∆NZeff, the volumetric analysis method achieved the highest area under the curve (AUC) with a value of 0.918 [95% confidence interval (CI): 0.847-0.988], followed by the PS method (AUC =0.853, 95% CI: 0.743-0.963). Conclusions: The spectral parameters of DLCT provide a novel quantitative method for evaluating histological differentiation in patients with HCC, which is worthy of clinical recommendation. Different ROI plotting methods significantly impact the measurement of spectral parameters. Therefore, the whole tumor region should be covered in the parameter measurement of HCC lesions as much as feasible, which is more helpful in predicting the histological grading of tumors before treatment.

Comparison of the efficacy of ROI-C cage with Zero-P device in anterior cervical discectomy and fusion of cervical degenerative disc disease: a two-year follow-up study.

Background: This study aimed to compare the clinical outcomes of Zero-P and ROI-C devices applied to anterior cervical discectomy and fusion (ACDF) surgery of cervical degenerative disc disease (CDDD). Methods: From January 2020 and December 2020, 56 patients with CDDD who underwent ACDF using Zero-P or ROI-C were included in this retrospective study. The outcomes included visual analogue scale (VAS) score, Japanese Orthopedic Association (JOA) score, neck disability index (NDI) score, Cobb angle, dysphagia, and bone fusion rate. Dysphagia was assessed using the Bazaz grading system. The comparison of outcomes between the two groups was based on the 2-year follow-up time point, which was defined as the last follow-up visit. Results: The Zero-P group included 16 males and 14 females, with a mean age of 56.2 (range, 35-65) years. The ROI-C group included 11 males and 15 females, with a mean age of 57.4 (range, 36-67) years. There was no significant difference in gender and mean age between the two groups. There were no significant differences in VAS score, JOA score, NDI score, Cobb angle, dysphagia, and bone fusion rate between two groups at the last follow up visit. In the Zero-P group, the duration of surgeries involving C3-4 or C6-7 segments was significantly longer than those including C4-5 or C5-6 segments (135.0 ± 19.0 vs. 105.6 ± 17.5 min, P < 0.05). In surgeries involving C3-4 or C6-7 segments, the operation time of ROI-C was significantly shorter than that of Zero-P (106.5 ± 19.5 vs.112.2 ± 20.5 min, P < 0.05). There were no significant differences in the dysphagia or cage subsidence rates between the Zero-P and ROI-C groups (P > 0.05). The Cobb angle in the last follow-up visit in the Zero-P group (24.4 ± 4.5°) was significantly higher than that in the ROI-C group (18.1 ± 2.3°) (P < 0.05). Conclusions: ACDF using ROI-C device showed an efficacy similar to the Zero-P device, as well as a shorter operation time for surgeries involving C3-4 or C6-7 segments. However, ROI-C could cause more loss of Cobb angle over time, which could lead to uncomfortable symptoms.

SIPAS: A comprehensive susceptibility imaging process and analysis studio.

Quantitative susceptibility mapping (QSM) is a rising MRI-based technology and quite a few QSM-related algorithms have been proposed to reconstruct maps of tissue susceptibility distribution from phase images. In this paper, we develop a comprehensive susceptibility imaging process and analysis studio (SIPAS) that can accomplish reliable QSM processing and offer a standardized evaluation system. Specifically, SIPAS integrates multiple methods for each step, enabling users to select algorithm combinations according to data conditions, and QSM maps could be evaluated by two aspects, including image quality indicators within all voxels and region-of-interest (ROI) analysis. Through a sophisticated design of user-friendly interfaces, the results of each procedure are able to be exhibited in axial, coronal, and sagittal views in real-time, meanwhile ROIs can be displayed in 3D rendering visualization. The accuracy and compatibility of SIPAS are demonstrated by experiments on multiple in vivo human brain datasets acquired from 3T, 5T, and 7T MRI scanners of different manufacturers. We also validate the QSM maps obtained by various algorithm combinations in SIPAS, among which the combination of iRSHARP and SFCR achieves the best results on its evaluation system. SIPAS is a comprehensive, sophisticated, and reliable toolkit that may prompt the QSM application in scientific research and clinical practice.

Return on investment in science: twenty years of European Commission funded research in Alzheimer's dementia, breast cancer and prostate cancer.

Alzheimer's disease (AD), breast cancer (BC) and prostate cancer (PC) continue to be high in the research and innovation agenda of the European Commission (EC). This is due to their exceptionally large burden to the national health systems, the profound economic effects of opportunity costs attributable to decreased working ability, premature mortality and the ever-increasing demand for both hospital and home-based medical care. Over the last two decades, the EC has been steadily increasing both the number of proposals being funded and the amounts of financial resources being allocated to these fields of research. This trend has continued throughout four consecutive science funding cycles, namely framework programme (FP)5, FP6, FP7 and Horizon 2020 (H2020). We performed a retrospective assessment of the outputs and outcomes of EC funding in AD, BC and PC research over the 1999-2019 period by means of selected indicators. These indicators were assessed for their ability to screen the past, present and future for an array of causal relationships and long-term trends in clinical, epidemiological and public health sphere, while considering also the broader socioeconomic impact of funded research on the society at large. This analysis shows that public-private partnerships with large industry and university-based consortia have led to some of the most impactful proposals being funded over the analysed time period. New pharmaceuticals, small molecules and monoclonal antibodies alike, along with screening and prevention, have been the most prominent sources of innovation in BC and PC, extending patients' survival and enhancing their quality of life. Unlike oncology, dementia drug development has been way less successful, with only minor improvements related to the quality of supportive medical care for symptoms and more sensitive diagnostics, without any ground-breaking disease-modifying treatment(s). Significant progresses in imaging diagnostics and nanotechnology have been largely driven by the participation of medical device industry multinational companies. Clinical trials funded by the EC were conducted, leading to the development of brand-new drug molecules featuring novel mechanisms of action. Some prominent cases of breakthrough discoveries serve as evidence for the European capability to generate cutting-edge technological innovation in biomedicine. Less productive areas of research may be reconsidered as priorities when shaping the new agenda for forthcoming science funding programmes.

Structural changes in eloquent cortex secondary to glioma in sensorimotor area.

This study aims to investigate the structural reorganization in the sensorimotor area of the brain in patients with gliomas, distinguishing between those with impaired and unimpaired strength. Using voxel-based morphometry (VBM) and region of interest (ROI) analysis, gray matter volumes (GMV) were compared in the contralesional primary motor gyrus, primary sensory gyrus, premotor area, bilateral supplementary motor area, and medial Brodmann area 8 (BA8). The results revealed that in patients with right hemisphere gliomas, the right medial BA8 volume was significantly larger in the impaired group than in the unimpaired group, with both groups exceeding the volume in 16 healthy controls (HCs). In patients with left hemisphere gliomas, the right supplementary motor area (SMA) was more pronounced in the impaired group compared to the unimpaired group, and both groups were greater than HCs. Additionally, the volumes of the right medial BA8 in both the impaired group were greater than HCs. Contralateral expansions in the gray matter of hand- and trunk-related cortices of the premotor area, precentral gyrus, and postcentral gyrus were observed compared to HCs. Furthermore, a negative correlation was found between hand Medical Research Council (MRC) score and volumes of the contralateral SMA and bilateral medial BA8. Notably, our findings reveal consistent results across both analytical approaches in identifying significant structural reorganizations within the sensorimotor cortex. These consistent findings underscore the adaptive neuroplastic responses to glioma presence, highlighting potential areas of interest for further neurosurgical planning and rehabilitation strategies.

Preoperative assessment of bone density for dental implantation: a comparative study of three different ROI methods.

BACKGROUND: Dental cone beam computed tomography (CBCT) is commonly used to evaluate cancellous bone density before dental implant surgery. However, to our knowledge, no measurement approach has been standardized yet. This study aimed to evaluate the relationship between three different regions of interest (ROI) methods on cancellous bone density at the dental implant site using dental CBCT images. METHODS: Patients' dental CBCT images (n = 300) obtained before dental implant surgery were processed using Mimics (Materialise, Leuven, Belgium). At the potential implant sites, the rectangle, cylinder, and surrounding cylinder ROI methods were used to measure bone density. Repeated measures one-way analysis of variance was performed to compare the three ROI methods in terms of measurement results. Pearson correlation analysis was performed to identify the likely pair-wise correlations between the three ROI methods. RESULTS: The density value obtained using the surrounding cylinder approach (grayscale value [GV],523.56 ± 228.03) was significantly higher than the values obtained using the rectangle (GV, 497.04 ± 236.69) and cylinder (GV,493 ± 231.19) ROI methods in terms of results. Furthermore, significant correlations were noted between the ROI methods (r > 0.965; p < 0.001). CONCLUSIONS: The density measured using the surrounding cylinder method was the highest. The choice of method may not influence the trends of measurement results. TRIAL REGISTRATION: This study was approved by the Institutional Review Board of China Medical University Hospital, No. CMUH111-REC3-205. Informed consent was waived by the Institutional Review Board of China Medical University Hospital, CMUH111-REC3-205, owing to the retrospective nature of the study.

A Novel Data Augmentation Method for Radiomics Analysis Using Image Perturbations.

Radiomics extracts hundreds of features from medical images to quantitively characterize a region of interest (ROI). When applying radiomics, imbalanced or small dataset issues are commonly addressed using under or over-sampling, the latter being applied directly to the extracted features. Aim of this study is to propose a novel balancing and data augmentation technique by applying perturbations (erosion, dilation, contour randomization) to the ROI in cardiac computed tomography images. From the perturbed ROIs, radiomic features are extracted, thus creating additional samples. This approach was tested addressing the clinical problem of distinguishing cardiac amyloidosis (CA) from aortic stenosis (AS) and hypertrophic cardiomyopathy (HCM). Twenty-one CA, thirty-two AS and twenty-one HCM patients were included in the study. From each original and perturbed ROI, 107 radiomic features were extracted. The CA-AS dataset was balanced using the perturbation-based method along with random over-sampling, adaptive synthetic (ADASYN) and the synthetic minority oversampling technique (SMOTE). The same methods were tested to perform data augmentation dealing with CA and HCM. Features were submitted to robustness, redundancy, and relevance analysis testing five feature selection methods (p-value, least absolute shrinkage and selection operator (LASSO), semi-supervised LASSO, principal component analysis (PCA), semi-supervised PCA). Support vector machine performed the classification tasks, and its performance were evaluated by means of a 10-fold cross-validation. The perturbation-based approach provided the best performances in terms of f1 score and balanced accuracy in both CA-AS (f1 score: 80%, AUC: 0.91) and CA-HCM (f1 score: 86%, AUC: 0.92) classifications. These results suggest that ROI perturbations represent a powerful approach to address both data balancing and augmentation issues.

Microstructural changes of the white matter in systemic lupus erythematosus patients without neuropsychiatric symptoms: a multi-shell diffusion imaging study.

BACKGROUND: Diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) provide more comprehensive and informative perspective on microstructural alterations of cerebral white matter (WM) than single-shell diffusion tensor imaging (DTI), especially in the detection of crossing fiber. However, studies on systemic lupus erythematosus patients without neuropsychiatric symptoms (non-NPSLE patients) using multi-shell diffusion imaging remain scarce. METHODS: Totally 49 non-NPSLE patients and 41 age-, sex-, and education-matched healthy controls underwent multi-shell diffusion magnetic resonance imaging. Totally 10 diffusion metrics based on DKI (fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis and radial kurtosis) and NODDI (neurite density index, orientation dispersion index and volume fraction of the isotropic diffusion compartment) were evaluated. Tract-based spatial statistics (TBSS) and atlas-based region-of-interest (ROI) analyses were performed to determine group differences in brain WM microstructure. The associations of multi-shell diffusion metrics with clinical indicators were determined for further investigation. RESULTS: TBSS analysis revealed reduced FA, AD and RK and increased ODI in the WM of non-NPSLE patients (P < 0.05, family-wise error corrected), and ODI showed the best discriminative ability. Atlas-based ROI analysis found increased ODI values in anterior thalamic radiation (ATR), inferior frontal-occipital fasciculus (IFOF), forceps major (F_major), forceps minor (F_minor) and uncinate fasciculus (UF) in non-NPSLE patients, and the right ATR showed the best discriminative ability. ODI in the F_major was positively correlated to C3. CONCLUSION: This study suggested that DKI and NODDI metrics can complementarily detect WM abnormalities in non-NPSLE patients and revealed ODI as a more sensitive and specific biomarker than DKI, guiding further understanding of the pathophysiological mechanism of normal-appearing WM injury in SLE.

Multiscale apple recognition method based on improved CenterNet.

Traditional apple-picking robots are unable to detect apples in real-time in complex environments. In order to improve detection efficiency, a fast CenterNet apple recognition method for multiple apple targets in dense scenes is proposed. This method can quickly and accurately identify multiple apple targets in dense scenes. The backbone network mainly consists of resnet-44 fully convolutional network, region of interest network (RPN), and region of interest (ROI). The experimental results show that the improved YoloV5 network model has a higher recognition accuracy of 94.1% and 95.8% for apple in the night environment, which improves the recognition accuracy of the occluded features and the features in the dark light, and the model is more robust in the actual data set.

Commentary: Value of information case study strongly supports use of the Threshold of Toxicological Concern (TTC).

A Value of Information (VOI) analysis can play a key role in decision-making for adopting new approach methodologies (NAMs). We applied EPA's recently developed VOI framework to the Threshold of Toxicological Concern (TTC). Obtaining/deriving a TTC value for use as a toxicity reference value (TRV) for substances with limited toxicity data was shown to provide equivalent or greater health protection, immense return on investment (ROI), greater net benefit, and substantially lower costs of delay (CoD) compared with TRVs derived from either traditional human health assessment (THHA) chronic toxicity testing in lab animals or the 5-day in vivo EPA Transcriptomic Assessment Product (ETAP). For all nine exposure scenarios examined, the TTC was more economical terms of CoD and ROI than the ETAP or the THHA; expected net benefit was similar for the TTC and ETAP with both of these more economical than the THHA The TTC ROI was immensely greater (5,000,000-fold on average) than the ROI for THHA and the ETAP ROI (100,000-fold on average). These results support the use of the TTC for substances within its domain of applicability to waive requiring certain in vivo tests, or at a minimum, as an initial screening step before conducting either the ETAP or THHA in vivo studies.

Relationships between Size-specific Dose Estimate and Signal to Noise Ratio under Chest CT Examinations with Tube Current Modulation.

PURPOSE: Exploring the relationship between the signal-to-noise ratio (SNR) of organs and size-specific dose estimate (SSDE) in tube current modulation (TCM) chest CT examination. METHODS: Forty patients who received TCM chest CT scanning were retrospectively collected and divided into four groups according to the tube voltage and sexes. We chose to set up the region of interest (ROI) at the tracheal bifurcation and its upper and lower parts in slice images of the heart, aorta, lungs, paracranial muscles, and female breast, and the SNR of each organ was calculated. We also calculated the corresponding axial volume CT dose index (CTDIvolz) and axial size-specific dose estimate (SSDEz). RESULTS: The correlation analysis showed that the correlation between the SNR of the slice images of most organs and SSDEz was more significant than 0.8, and that between the SNR and CTDIvol was more significant than 0.7. The simple linear regression analysis results showed that when the sex is the same, the SNR of the same organ at 100kVp was higher than 120kVp, except for the lung. In multiple regression analysis, the result indicated that the determination coefficients of the SNR and SSDEz of the four groups were 0.934, 0.971, 0.905, and 0.709, respectively. CONCLUSION: In chest CT examinations with TCM, the correlation between the SNR of each organ in slice images and SSDEz was better than that of CTDIvolz. And when the SSDEz was the same, the SNR at 100 kVp was better than that at 120 kVp.

The Impact of Different Regions of Interest on Shear Wave Elastography Assessment of the Meniscus in the Knee Joint.

RATIONALE AND OBJECTIVES: To investigate the impact of different regions of interest (ROI) on the assessment of shear wave elastography (SWE) in evaluating the meniscus of the knee joint. MATERIALS AND METHODS: After ethical approval, a total of 141 participants were enrolled in this prospective study from February to October 2023. SWE was utilized to evaluate the anterior horn of the lateral meniscus (LM) and medial meniscus (MM), using two different ROIs (ROI-Small and ROI-Trace) to measure the elastic mean value (Emean) and elastic maximum value (Emax). The differences in elasticity values between the normal menisci and torn menisci were compared, and the impact of different ROI selection methods on the diagnostic performance of elastic parameters in the torn menisci was assessed using receiver operating characteristic (ROC) curves. RESULTS: In Emean comparison, only MM in the tear group showed higher ROI-S than ROI-T. When comparing Emax, all ROI-T values were higher than the ROI-S values, and this difference was statistically significant. Different sizes of ROI did not significantly impact the diagnostic performance of Emean in LM and MM, nor the diagnostic effectiveness of Emax in LM. However, only the area under the curve (AUC) of MM for Emax in both ROI-S and ROI-T showed a statistically significant difference. CONCLUSION: The shear wave elasticity values and diagnostic performance may vary depending on the ROI settings. Therefore, it is recommended to use a 2 mm diameter ROI placed at the central position of the meniscus, with Emean as the elasticity index.

Neuroimaging Methods for MRI Analysis in CSF Biomarkers Studies.

Among others, the existence of pathophysiological biomarkers such as cerebrospinal fluid (CSF) Aß-42, t-tau, and p-tau preceding the onset of Alzheimer's disease (AD) symptomatology has shifted the conceptualization of AD as a continuum. In addition, magnetic resonance imaging (MRI) enables the study of structural and functional cross-sectional correlates and longitudinal changes in vivo, and therefore, the combination of CSF data and imaging analyses emerges as a synergistic approach to understand the structural correlates related with specific AD-related biomarkers. In this chapter, we describe the methods used in neuroimaging that will allow researchers to combine data on CSF metabolites with imaging analyses.

Lossless compression-based detection of osteoporosis using bone X-ray imaging.

BACKGROUND: Digital X-ray imaging is essential for diagnosing osteoporosis, but distinguishing affected patients from healthy individuals using these images remains challenging. OBJECTIVE: This study introduces a novel method using deep learning to improve osteoporosis diagnosis from bone X-ray images. METHODS: A dataset of bone X-ray images was analyzed using a newly proposed procedure. This procedure involves segregating the images into regions of interest (ROI) and non-ROI, thereby reducing data redundancy. The images were then processed to enhance both spatial and statistical features. For classification, a Support Vector Machine (SVM) classifier was employed to distinguish between osteoporotic and non-osteoporotic cases. RESULTS: The proposed method demonstrated a promising Area under the Curve (AUC) of 90.8% in diagnosing osteoporosis, benchmarking favorably against existing techniques. This signifies a high level of accuracy in distinguishing osteoporosis patients from healthy controls. CONCLUSIONS: The proposed method effectively distinguishes between osteoporotic and non-osteoporotic cases using bone X-ray images. By enhancing image features and employing SVM classification, the technique offers a promising tool for efficient and accurate osteoporosis diagnosis.

A ROI-based quantitative pipeline for 18F-FDG PET metabolism and pCASL perfusion joint analysis: Validation of the 18F-FDG PET line.

In Mild Cognitive Impairment (MCI), the study of brain metabolism, provided by 18F-FluoroDeoxyGlucose Positron Emission Tomography (18F-FDG PET) can be integrated with brain perfusion through pseudo-Continuous Arterial Spin Labeling Magnetic Resonance sequences (MR pCASL). Cortical hypometabolism identification generally relies on wide control group datasets; pCASL control groups are instead not publicly available yet, due to lack of standardization in the acquisition parameters. This study presents a quantitative pipeline to be applied to PET and pCASL data to coherently analyze metabolism and perfusion inside 16 matching cortical regions of interest (ROIs) derived from the AAL3 atlas. The PET line is tuned on 36 MCI patients and 107 healthy control subjects, to agree in identifying hypometabolic regions with clinical reference methods (visual analysis supported by a vendor tool and Statistical Parametric Mapping, SPM, with two parametrizations here identified as SPM-A and SPM-B). The analysis was conducted for each ROI separately. The proposed PET analysis pipeline obtained accuracy 78 % and Cohen's к 60 % vs visual analysis, accuracy 79 % and Cohen's к 58 % vs SPM-A, accuracy 77 % and Cohen's к 54 % vs SPM-B. Cohen's к resulted not significantly different from SPM-A and SPM-B Cohen's к when assuming visual analysis as reference method (p-value 0.61 and 0.31 respectively). Considering SPM-A as reference method, Cohen's к is not significantly different from SPM-B Cohen's к as well (p-value = 1.00). The complete PET-pCASL pipeline was then preliminarily applied on 5 MCI patients and metabolism-perfusion regional correlations were assessed. The proposed approach can be considered as a promising tool for PET-pCASL joint analyses in MCI, even in the absence of a pCASL control group, to perform metabolism-perfusion regional correlation studies, and to assess and compare perfusion in hypometabolic or normo-metabolic areas.

To assess the quantitative features of focal liver lesions in gadoxetic acid enhanced MRI and to determine whether these features can accurately differentiate benign form malignant lesions.

PURPOSE: The study aims at assessing the quantitative features which distinguish focal liver lesions (FLLs) in gadoxetic acid (GA) enhanced liver MRI and at determining whether these features can accurately differentiate benign from malignant lesions. MATERIAL AND METHODS: 107 patients with 180 unequivocal FLLs in previous examinations were included in a single-center retrospective study. All patients underwent a MRI test of the liver with GA. 99 benign and 74 malignant lesions were included. The group of benign lesions consisted of 60 focal nodular hyperplasias (FNH), 22 hemangiomas (HMG), 6 hepatic adenomas (HA), and 11 other benign lesions (1 angiomyolipioma, 6 lesions histopathology diagnoses as benign without further specification, or ones lacking features of malignancy, and 4 lesions radiologically diagnosed as benign which remained stable in the follow-up studies). The group of malignant lesions consisted of primary 51 hepatocellular carcinomas, 12 metastases, and 11 metastases from melanoma malignum (MM meta). 7 FLLs were excluded (4 cases of uncertain histopathological diagnosis, 2 cholangiocarcinomas, and 1 regenerative nodule). For the included lesions ROI (region of interest) measurements were taken by two observers in the T2-w, ADC (apparent diffusion coefficient) and in the T1-w sequence in the hepatobiliary phase (HBP). The interobserver agreement was evaluated with the Wilcoxon test. The Kruskal - Wallis, Mann - Whitney U and post hoc Dunn's tests were applied to assess if there were any significant differences in the ROI values between individual lesions. The variables with the p values of < 0.05 were considered statistically significant. RESULTS: We found significant differences in the ROI values between lesions with p < 0.0001. Strikingly high ROI values in the T2-w sequence were found for HMG. The lowest ADC values were encountered for metastases and MM metastases. The highest ROI values in the HBP were found for FNH, and the lowest for metastases. We also found statistically significant differences in the ROI values between benign and malignant lesions with benign lesions presenting statistically higher ROI values compared to malignant lesions. CONCLUSIONS: There were significant differences in the ROI values among different types of FLLs. The predominant quantitative feature in the T2-w sequence was a strikingly high ROI value for HMG. Benign lesions presented statistically higher ROI values in the T2-w, ADC, and HBP sequences compared to malignant lesions. This was true for all lesions except for HA.

A methodology for projecting the return on investment of training technologies.

Each year significant tax dollars are spent on the development of new technologies to increase efficiency and/or reduce costs of military training. However, there are currently no validated methods or measures to quantify the return on investment for adopting these new technologies for military training. Estimating the return on investment (ROI) for training technology adoption involves 1) developing a methodology or framework, 2) validating measures and methods, and 3) assessing predictive validity. The current paper describes a projective methodology using the Kirkpatrick framework to compare projected tangible and intangible benefits against tangible and intangible costs to estimate future ROI. The use-case involved an advanced technology demonstration in which sixty aircrew participated in a series of live, virtual, and constructive (LVC) exercises over a five-week period. Participants evaluated the technology's potential costs and benefits according to the Kirkpatrick framework of training program evaluation, and analyses resulted in a nominal projection of $488 million dollars saved, significant enhancements in large-force proficiency, and 1.4 lives saved over ten years at an implementation rate of 0.5% of budgeted flight hours. A discussion of theoretical implications, data-based limitations, and recommendations for future research are provided.

Short-term economic evaluation of physical activity-based corporate health programs: a systematic review.

OBJECTIVES: Corporate health programs (CHPs) aim to improve employees' health through health promotion strategies at the workplace. Physical activity (PA) plays a crucial role in primary prevention, leading many companies to implement PA-based CHPs. However, there is limited examination in the scientific literature on whether PA-based CHPs (PA-CHPs) lead to economic benefits. This systematic review aimed to summarize the available literature on the economic aspects of PA-CHPs. METHODS: A systematic review was conducted to identify studies focused on PA-CHPs targeting healthy sedentary workers and reporting at least one economic outcome, such as return on investment (ROI), costs, or sick leave. RESULTS: Of 1036 studies identified by our search strategy, 11 studies involving 60 020 participants met the inclusion criteria. The mean (±SD) cost per capita for PA-CHPs was estimated as 359€ (±238€) (95% CI, 357-361€). In 75% of the studies, the net savings generated by PA-CHPs in 12 months were reported, with an average of 1095€ (±865€) (95% CI, 496-1690€). ROI was assessed in 50% of the included studies, with an average of 3.6 (±1.41) (95% CI, 2.19-5.01). CONCLUSIONS: In addition to promoting a healthy lifestyle, PA-CHPs have the potential to generate significant economic returns. However, the heterogeneity among the existing studies highlights the need for standardization and accurate reporting of costs in future research.

Network dysfunction of sadness facial expression processing and morphometry in euthymic bipolar disorder.

Facial emotion recognition (FER), including sadness, is altered in bipolar disorder (BD). However, the relationship between this impairment and the brain structure in BD is relatively unexplored. Furthermore, its association with clinical variables and with the subtypes of BD remains to be clarified. Twenty euthymic patients with BD type I (BD-I), 28 BD type II (BD-II), and 45 healthy controls completed a FER test and a 3D-T1-weighted magnetic resonance imaging. Gray matter volume (GMV) of the cortico-limbic regions implicated in emotional processing was estimated and their relationship with FER performance was investigated using network analysis. Patients with BD-I had worse total and sadness-related FER performance relative to the other groups. Total FER performance was significantly negatively associated with illness duration and positively associated with global functioning in patients with BD-I. Sadness-related FER performance was also significantly negatively associated with the number of previous manic episodes. Network analysis showed a reduced association of the GMV of the frontal-insular-occipital areas in patients with BD-I, with a greater edge strength between sadness-related FER performance and amygdala GMV relative to controls. Our results suggest that FER performance, particularly for facial sadness, may be distinctively impaired in patients with BD-I. The pattern of reduced interrelationship in the frontal-insular-occipital regions and a stronger positive relationship between facial sadness recognition and the amygdala GMV in BD may reflect altered cortical modulation of limbic structures that ultimately predisposes to emotional dysregulation. Future longitudinal studies investigating the effect of mood state on FER performance in BD are warranted.

Deep Learning Model Based on Multisequence MRI Images for Assessing Adverse Pregnancy Outcome in Placenta Accreta.

BACKGROUND: Preoperative assessment of adverse outcomes risk in placenta accreta spectrum (PAS) disorders is of high clinical relevance for perioperative management and prognosis. PURPOSE: To investigate the association of preoperative MRI multisequence images and adverse pregnancy outcomes by establishing a deep learning model in patients with PAS. STUDY TYPE: Retrospective. POPULATION: 323 pregnant women (age from 20 to 46, the median age is 33), suspected of PAS, underwent MRI to assess the PAS, divided into the training (N = 227) and validation datasets (N = 96). FIELD STRENGTH/SEQUENCE: 1.5T scanner/fast imaging employing steady-state acquisition sequence and single shot fast spin echo sequence. ASSESSMENT: Different deep learning models (i.e., with single MRI input sequence/two sequences/multisequence) were compared to assess the risk of adverse pregnancy outcomes, which defined as intraoperative bleeding ≥1500 mL and/or hysterectomy. Net reclassification improvement (NRI) was used for quantitative comparison of assessing adverse pregnancy outcome between different models. STATISTICAL TESTS: The AUC, sensitivity, specificity, and accuracy were used for evaluation. The Shapiro-Wilk test and t-test were used. A P value of <0.05 was considered statistically significant. RESULTS: 215 cases were invasive placenta accreta (67.44% of them with adverse outcomes) and 108 cases were non-invasive placenta accreta (9.25% of them with adverse outcomes). The model with four sequences assessed adverse pregnancy outcomes with AUC of 0.8792 (95% CI, 0.8645-0.8939), with ACC of 85.93% (95%, 84.43%-87.43%), with SEN of 86.24% (95% CI, 82.46%-90.02%), and with SPC of 85.62% (95%, 82.00%-89.23%) on the test cohort. The performance of model with four sequences improved above 0.10 comparing with that of model with two sequences and above 0.20 comparing with that of model with single sequence in terms of NRI. DATA CONCLUSION: The proposed model showed good diagnostic performance for assessing adverse pregnancy outcomes. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.