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Purpose: Radiation pneumonitis (RP) is one of the common side effects of radiation therapy in the thoracic region. Radiomics and dosiomics quantify information implicit within medical images and radiation therapy dose distributions. In this study we demonstrate the prognostic potential of radiomics, dosiomics, and clinical features for RP prediction. Methods and Materials: Radiomics, dosiomics, dose-volume histogram (DVH) metrics, and clinical parameters were obtained on 314 retrospectively collected and 35 prospectively enrolled patients diagnosed with lung cancer between 2013 to 2019. A radiomics risk score (R score) and dosiomics risk score (D score), as well as a DVH-score, were calculated based on logistic regression after feature selection. Six models were built using different combinations of R score, D score, DVH score, and clinical parameters to evaluate their added prognostic power. Overoptimism was evaluated by bootstrap resampling from the training set, and the prospectively collected cohort was used as the external test set. Model calibration and decision-curve characteristics of the best-performing models were evaluated. For ease of further evaluation, nomograms were constructed for selected models. Results: A model built by integrating all of the R score, D score, and clinical parameters had the best discriminative ability with areas under the curve of 0.793 (95% confidence interval [CI], 0.735-0.851), 0.774 (95% CI, 0.762-0.786), and 0.855 (95% CI, 0.719-0.990) in the training, bootstrapping, and external test sets, respectively. The calibration curve image showed good agreement between the predicted and actual values, with a slope of 1.21 and intercept of –0.04. The decision curve image showed a positive net benefit for the final model based on the nomogram. Conclusions: Radiomic and dosiomic features have the potential to assist with the prediction of RP, and the combination of radiomics, dosiomics, and clinical parameters led to the best prognostic model in the present study.

Objective: To determine the association between early post-endovascular treatment (EVT) contrast extravasation (CE) on dual-energy CT (DECT) and stroke outcomes. Methods: EVT records in 2010–2019 were screened. Exclusion criteria included the occurrence of immediate post-procedural intracranial haemorrhage (ICH). Hyperdense areas on iodine overlay maps were scored according to the Alberta Stroke Programme Early CT Score (ASPECTS), thus forming a CE-ASPECTS. Maximum parenchymal iodine concentration and maximum iodine concentration relative to the torcula were recorded. Follow-up imaging was reviewed for ICH. The primary outcome measure was the modified Rankin Scale (mRS) at 90 days. Results: Out of 651 records, 402 patients were included. CE was found in 318 patients (79%). Thirty-five patients developed ICH on follow-up imaging. Fourteen ICHs were symptomatic. Stroke progression occurred in 59 patients. Multivariable regression showed a significant association between decreasing CE-ASPECTS and the mRS at 90 days (adjusted (a)cOR: 1.10, 95% CI: 1.03–1.18), NIHSS at 24–48 h (aβ: 0.57, 95% CI: 0.29–0.84), stroke progression (aOR: 1.14, 95% CI: 1.03–1.26) and ICH (aOR: 1.21, 95% CI: 1.06–1.39), but not symptomatic ICH (aOR 1.19, 95% CI: 0.95–1.38). Iodine concentration was significantly associated with the mRS (acOR: 1.18, 95% CI: 1.06–1.32), NIHSS (aβ: 0.68, 95% CI: 0.30–1.06), ICH (aOR: 1.37, 95% CI: 1.04–1.81) and symptomatic ICH (aOR: 1.19, 95% CI: 1.02–1.38), but not stroke progression (aOR: 0.99, 95% CI: 0.86–1.15). Results of the analyses with relative iodine concentration were similar and did not improve prediction. Conclusions: CE-ASPECTS and iodine concentration are both associated with short- and long-term stroke outcomes. CE-ASPECTS is likely a better predictor for stroke progression.

Purpose To investigate whether locoregional staging of colon cancer by experienced radiologists can be improved by training and feedback to minimize the risk of over-staging into the context of patient selection for neoadjuvant therapy and to identify potential pitfalls of CT staging by characterizing pathologic traits of tumors that remain challenging for radiologists. Methods Forty-five cases of stage I-III colon cancer were included in this retrospective study. Five experienced radiologists evaluated the CTs; 5 baseline scans followed by 4 sequential batches of 10 scans. All radiologists were trained after baseline scoring and 2 radiologists received feedback. The learning curve, diagnostic performance, reader confidence, and reading time were evaluated with pathologic staging as reference. Pathology reports and H&E slides of challenging cases were reviewed to identify potential pitfalls. Results Diagnostic performance in distinguishing T1-2 vs. T3-4 improved significantly after training and with increasing number of reviewed cases. Inaccurate staging was more frequently related to under-staging rather than over-staging. Risk of over-staging was minimized to 7% in batch 3–4. N-staging remained unreliable with an overall accuracy of 61%. Pathologic review identified two tumor characteristics causing under-staging for T-stage in 5/7 cases: (1) very limited invasive part beyond the muscularis propria and (2) mucinous composition of the invading part. Conclusion The high accuracy and specificity of T-staging reached in our study indicate that sufficient training and practice of experienced radiologists can ensure high validity for CT staging in colon cancer to safely use neoadjuvant therapy without significant risk of over-treatment, while N-staging remained unreliable.

Background Empiric antifungal therapy is considered the standard of care for high-risk neutropenic patients with persistent fever. The impact of a preemptive, diagnostic-driven approach based on galactomannan screening and chest computed tomography scan on demand on survival and on the risk of invasive fungal disease (IFD) during the first weeks of high-risk neutropenia is unknown. Methods Patients with acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS) and allogeneic hematopoietic cell transplant recipients were randomly assigned to receive caspofungin empirically (arm A) or preemptively (arm B), while receiving fluconazole 400 mg daily prophylactically. The primary end point of this noninferiority study was overall survival (OS) 42 days after randomization. Results Of 556 patients recruited, 549 were eligible: 275 in arm A and 274 in arm B. Eighty percent of the patients had AML or MDS requiring high-dose chemotherapy, and 93% of them were in the first induction phase. At day 42, the OS was not inferior in arm B (96.7%; 95% confidence interval [CI], 93.8%–98.3%) when compared with arm A (93.1%; 95% CI, 89.3%–95.5%). The rates of IFDs at day 84 were not significantly different, 7.7% (95% CI, 4.5%–10.8%) in arm B vs 6.6% (95% CI, 3.6%–9.5%) in arm A. The rate of patients who received caspofungin was significantly lower in arm B (27%) than in arm A (63%; P < .001). Conclusions The preemptive antifungal strategy was safe for high-risk neutropenic patients given fluconazole as prophylaxis, halving the number of patients receiving antifungals without excess mortality or IFDs. Clinical Trials Registration. NCT01288378; EudraCT 2010-020814-27.

PURPOSE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is regarded as a multisystemic disease. Patients with preexisting cardiovascular disease have an increased risk for a more severe disease course. This study aimed to investigate if a higher degree of coronary artery calcifications (CAC) on a standard chest computed tomography (CT) scan in mechanically ventilated patients was associated with a more severe multiorgan failure over time.MATERIALS AND METHODS: All mechanically ventilated intensive care unit patients with SARS-CoV-2 infection who underwent a chest CT were prospectively included. CT was used to establish the extent of CAC using a semiquantitative grading system. We categorized patients into 3 sex-specific tertiles of CAC: lowest, intermediate, and highest CAC score. Daily, the Sequential Organ Failure Assessment (SOFA) scores were collected to evaluate organ failure over time. Linear mixed-effects regression was used to investigate differences in SOFA scores between tertiles. The models were adjusted for age, sex, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, cardiovascular risk factors, and chronic liver, lung, and renal disease.RESULTS: In all, 71 patients were included. Patients in the highest CAC tertile had, on average, over time, 1.8 (0.5-3.1) points higher SOFA score, compared with the lowest CAC tertile (P=0.005). This association remained significant after adjustment for age, sex, and APACHE II score (1.4 [0.1-2.7],P=0.042) and clinically relevant after adjustment for cardiovascular risk factors (1.3 [0.0-2.7],P=0.06) and chronic diseases (1.3 [-0.2 to 2.7],P=0.085).CONCLUSION: A greater extent of CAC is associated with a more severe multiorgan failure in mechanically ventilated coronavirus disease 2019 patients.

In forensic radiology, computed tomography (CT) is often used as a medical imaging technique to identify the cause and manner of death of deceased victims of a possible crime. In this study, medical imaging is used to examine concealed bodies and packaging materials. Medical imaging techniques, mainly CT scan, were used to scan packaged or concealed bodies inside containers to identify clues and evidence indicating whether a crime might have been committed. Also, scene integrity and scene safety along with a systematic search for relevant evidentiary items value were considered. Eighteen concealed bodies that had been assessed using medical imaging techniques between 2010 and 2018 at the request of the Dutch National Police were selected. The file records of each case contained imaging data, a photographic record of the unpacking procedure, a list of all items and traces found in the package, and the forensic pathology report. The images were assessed with respect to the different aspects of the case and through a systematic approach. The packages included adult males, adult females, newborn infants, and animals. All human cases were related to criminal offences. In nine adult cases, evidence of a possible violent death could be determined using CT imaging. The cause of death in newborn infants, however, could not be determined. In cases of dismemberment, the completeness of the body could be determined by CT imaging, and the cutting surfaces of bones could be matched on CT images. Regarding scene safety and integrity, in this study all relevant macroscopic items were detected on the CT images. The CT-scans were supplemented with fiduciary markers to better map CT data with the real objects. This information in combination with 2D and 3D images provided the forensic investigator with information on how to unwrap the package layer by layer and help determine different types of packaging materials. Different textiles could not always be identified. The orientation of the body within the packages was provided in all cases, and advice could be given on the optimal approach to access the contents. The overall detection rate of items was 78%. This is one of the first studies to illustrate the contribution of medical imaging, specifically CT scan, to the analysis of concealed bodies and packaging materials prior to unpacking. This demonstrates its contribution to a systematic approach of the investigation by ensuring the safety and health of the investigator while documenting and maintaining the integrity of the crime scene. Imaging also provides information that can be helpful to determine whether a crime might have been committed and reducing the risk of damaging a concealed body. Medical imaging also provides the forensic investigator with information to draw up a workplan prior to unpacking, minimising loss of evidence and determining whether different forensic specialists (e.g., digital or DNA) are needed. It is therefore strongly recommended to use medical imaging, especially CT scanning, before opening a package containing a concealed body.

Trials show that low-dose computed tomography (CT) lung cancer screening in long-term (ex-)smokers reduces lung cancer mortality. However, many individuals were exposed to unnecessary diagnostic procedures. This project aims to improve the efficiency of lung cancer screening by identifying high-risk participants, and improving risk discrimination for nodules. This study is an extension of the Dutch-Belgian Randomized Lung Cancer Screening Trial, with a focus on personalized outcome prediction (NELSON-POP). New data will be added on genetics, air pollution, malignancy risk for lung nodules, and CT biomarkers beyond lung nodules (emphysema, coronary calcification, bone density, vertebral height and body composition). The roles of polygenic risk scores and air pollution in screen-detected lung cancer diagnosis and survival will be established. The association between the AI-based nodule malignancy score and lung cancer will be evaluated at baseline and incident screening rounds. The association of chest CT imaging biomarkers with outcomes will be established. Based on these results, multisource prediction models for pre-screening and post-baseline-screening participant selection and nodule management will be developed. The new models will be externally validated. We hypothesize that we can identify 15-20% participants with low-risk of lung cancer or short life expectancy and thus prevent ~140,000 Dutch individuals from being screened unnecessarily. We hypothesize that our models will improve the specificity of nodule management by 10% without loss of sensitivity as compared to assessment of nodule size/growth alone, and reduce unnecessary work-up by 40-50%. ispartof: EUROPEAN JOURNAL OF EPIDEMIOLOGY vol:38 issue:4 pages:445-454 ispartof: location:Netherlands status: published

Objective To investigate the association between clinical joint tenderness and intra- and periarticular inflammation as assessed by ultrasound and MRI in patients with active PsA and to explore if the associations differ according to patient-reported outcomes (PROs) and structural damage. Methods Forty-one patients with active PsA and hand involvement had 76/78 joints examined for swelling/tenderness and ultrasound and MRI of 24 and 12 finger joints, respectively. Synovitis, tenosynovitis, periarticular inflammation and erosions were assessed using OMERACT definitions and scoring systems. Correlation between imaging inflammation sum-scores (intra-and periarticular) and tender/swollen joint counts were calculated using Spearman’s rho, agreement at joint level was examined using prevalence and bias adjusted kappa (PABAK). Subgroup analyses explored the influence of PROs and radiographic erosive disease on these associations. Results No significant correlations were found between tender or swollen joint counts and imaging inflammation sum-scores (rho = −0.31–0.38). In patients with higher level of overall pain, disability and lower self-reported mental health, a tendency towards negative correlations were found. At joint level, intra- and periarticular imaging inflammatory lesions had slight agreement with joint tenderness (PABAK = 0.02–0.19) and slight to moderate with swelling (PABAK = 0.16–0.54). For tender joints, agreement with imaging inflammation was even weaker in patients with either high overall pain scores, high disability scores, and/or non-erosive disease. Conclusion Joint tenderness had low association with imaging signs of inflammation in PsA patients, particularly in patients with high self-reported pain, disability and low mental health, indicating that tenderness is influenced by other parameters than local inflammation.

The structural similarity index metric is used to measure the similarity between two images. The aim here was to study the feasibility of this metric to measure the structural similarity and fracture characteristics of midfacial fractures in computed tomography (CT) datasets following radiation dose reduction, iterative reconstruction (IR) and deep learning reconstruction. Zygomaticomaxillary fractures were inflicted on four human cadaver specimen and scanned with standard and low dose CT protocols. Datasets were reconstructed using varying strengths of IR and the subsequently applying the PixelShine™ deep learning algorithm as post processing. Individual small and non-dislocated fractures were selected for the data analysis. After attenuating the osseous anatomy of interest, registration was performed to superimpose the datasets and subsequently to measure by structural image quality. Changes to the fracture characteristics were measured by comparing each fracture to the mirrored contralateral anatomy. Twelve fracture locations were included in the data analysis. The most structural image quality changes occurred with radiation dose reduction (0.980036±0.011904), whilst the effects of IR strength (0.995399±0.001059) and the deep learning algorithm (0.999996±0.000002) were small. Radiation dose reduction and IR strength tended to affect the fracture characteristics. Both the structural image quality and fracture characteristics were not affected by the use of the deep learning algorithm. In conclusion, evidence is provided for the feasibility of using the structural similarity index metric for the analysis of structural image quality and fracture characteristics.

PURPOSE We aimed to compare the inter-center cranial computed tomography (CT) acquisition rates, CT findings, CT-related radiation dose, and variability of CT acquisition parameters for neurologic events among patients with implantable cardioverter-defibrillator (ICD) or left ventricular assist device (LVAD). METHODS A total of 224 patients (ICD group, n=155; LVAD group, n=69) who had at least one cranial CT scan were enrolled from 3 medical centers (Centers A, B, and C). The variability and effect of the number, indication, and findings of cranial CT scans as well as CT acquisition parameters including tube potential (kV), tube current (mAs), tube rotation time, slice collimation, and spiral or sequential scanning techniques on CT dose index volume (CTDIvol), and total dose length product (DLP) were analyzed. RESULTS The mean DLP value of Center A and the mean CTDIvol values of Centers A and C were significantly lower than those of Center B (P

Radiomics is the quantitative analysis of standard-of-care medical imaging; the information obtained can be applied within clinical decision support systems to create diagnostic, prognostic, and/or predictive models. Radiomics analysis can be performed by extracting hand-crafted radiomics features or via deep learning algorithms. Radiomics has evolved tremendously in the last decade, becoming a bridge between imaging and precision medicine. Radiomics exploits sophisticated image analysis tools coupled with statistical elaboration to extract the wealth of information hidden inside medical images, such as computed tomography (CT), magnetic resonance (MR), and/or Positron emission tomography (PET) scans, routinely performed in the everyday clinical practice. Many efforts have been devoted in recent years to the standardization and validation of radiomics approaches, to demonstrate their usefulness and robustness beyond any reasonable doubts. However, the booming of publications and commercial applications of radiomics approaches warrant caution and proper understanding of all the factors involved to avoid "scientific pollution" and overly enthusiastic claims by researchers and clinicians alike. For these reasons the present review aims to be a guidebook of sorts, describing the process of radiomics, its pitfalls, challenges, and opportunities, along with its ability to improve clinical decision-making, from oncology and respiratory medicine to pharmacological and genotyping studies.

Objectives: To assess the impact of low kilo-electronvolt (keV) virtual monoenergetic image (VMI) energies and iterative reconstruction on image quality of clinical photon-counting detector coronary CT angiography (CCTA). Methods: CCTA with PCD-CT (prospective ECG-triggering, 120 kVp, automatic tube current modulation) was performed in a high-end cardiovascular phantom with dynamic flow, pulsatile heart motion, and including different calcified plaques with various stenosis grades and in 10 consecutive patients. VMI at 40,50,60 and 70 keV were reconstructed without (QIR-off) and with all quantum iterative reconstruction (QIR) levels (QIR-1 to 4). In the phantom, noise power spectrum, vessel attenuation, contrast-to-noise-ratio (CNR), and vessel sharpness were measured. Two readers graded stenoses in the phantom and graded overall image quality, subjective noise, vessel sharpness, vascular contrast, and coronary artery plaque delineation on 5-point Likert scales in patients. Results: In the phantom, noise texture was only slightly affected by keV and QIR while noise increased by 69% from 70 keV QIR-4 to 40 keV QIR-off. Reconstructions at 40 keV QIR-4 exhibited the highest CNR (46.1 ± 1.8), vessel sharpness (425 ± 42 ∆HU/mm), and vessel attenuation (1098 ± 14 HU). Stenosis measurements were not affected by keV or QIR level (p > 0.12) with an average error of 3%/6% for reader 1/reader 2, respectively. In patients, across all subjective categories and both readers, 40 keV QIR-3 and QIR-4 images received the best scores (p < 0.001). Conclusion: Forty keV VMI with QIR-4 significantly improved image quality of CCTA with PCD-CT. Advances in knowledge: PCD-CT at 40 keV and QIR-4 improves image quality of CCTA.

Objectives Increasing evidence suggests a role for epicardial fat in the development of coronary artery disease in the general population. Heart transplantation patients are at increased risk of developing a specific form of coronary artery disease, cardiac allograft vasculopathy (CAV), which has far-reaching consequences in terms of morbidity and mortality. Until now, the role of epicardial fat volume (EFV) in the development of CAV remains unknown. Hence, we investigated the relationship between EFV and CAV as well as the influence of donor/recipient sex on EFV. Methods Adult heart transplant patients who underwent coronary computed tomography angiography (CCTA) for CAV screening who were four or more years post-HT were included. Using the CT examinations, we quantified the EFV and the degree of CAV. Ordinal and linear regression models were used to assess the association of EFV with CAV. Results In total, 149 (median age 44.5 years, 36% women) patients were included. The median time between HT and the CT scan was 11.0 (7.3–16.1) years. CAV grade 0, 1, 2 and 3 were seen in 85 (57%), 32 (22%), 14 (9%), and 18 (12%) patients, respectively. The median EFV was 208.4 (128.9–276.0) mL. Larger EFV were related to higher degrees of CAV (median of 164.7 to 290.6 mL for CAV grade 0 and 3, respectively, OR 5.23 (2.47–11.06), p < 0.001). Male recipients had significantly more EFV than female recipients irrespective of the donor sex (232.7 mL vs. 147.2 mL respectively, p < 0.001). Determinants for EFV were recipient sex, number of rejections, donor age, time between HT and CT scan, recipient BMI, and diabetes mellitus. Conclusions EFV was associated with higher degrees of CAV. The recipient sex influenced the EFV more than the donor sex. Key Points • Patients after heart transplantation have a high amount of epicardial fat while larger amounts of epicardial fat are related to higher grades of cardiac allograft vasculopathy. • Determinants of higher epicardial fat volume included recipient sex, number of rejections, donor age, time between HT and CT scan, recipient BMI, and diabetes mellitus. • Longitudinal studies are needed to further disentangle the role of epicardial fat in the development and progression of cardiac allograft vasculopathy. Graphical abstract

Self-healing is recognized as a promising technique for increasing the durability of concrete structures by healing cracks, thereby reducing the need for maintenance activities over the service life and decreasing the environmental impact. Various self-healing technologies have been applied to a wide range of cementitious materials, and the performance has generally been assessed under 'ideal' laboratory conditions. Performance tests under ideal conditions, tailored to the self-healing mechanism, can demonstrate the self-healing potential. However, there is an urgent need to prove the robustness and reliability of self-healing under realistic simulated conditions and in real applications before entering the market. This review focuses on the influence of cracks on degradation phenomena in reinforced concrete structures, the efficiency of different healing agents in various realistic (aggressive) scenarios, test methods for evaluating self-healing efficiency, and provides a pathway for integrating self-healing performance into a life-cycle encompassing durability-based design.

The aim of the study was to assess factors leading to revision surgery and implant position of primary orbital fracture reconstructions. A retrospective cohort included patients who underwent orbital floor and/or medial wall fracture reconstruction for recent trauma. Demographics, fracture type, surgery and implant-related variables, and postoperative implant position were analyzed. The overall revision surgery rate was 6.5% (15 of 232 surgeries). The rate was highest in combined midfacial fractures with rim involvement (14.0%), lower in zygomatico-orbital fractures (8.7%), and lowest in isolated blowout fractures (3.8%). Fracture type, orbital rim fixation and implant malposition predicted revision. The best positioning was achieved with patient-specific milled titanium implants (mtPSI) and resorbable materials, whereas the poorest with preformed three-dimensional titanium plates. Combined midfacial fractures with rim involvement in particular have a high risk for orbital revision surgery. Within the limitations of the present study, mtPSIs should be preferred in the reconstruction of primary orbital fractures if possible. (C) 2021 The Author(s). Published by Elsevier Ltd on behalf of European Association for Cranio-Maxillo-Facial Surgery.

A solvothermal route to prepare Glutathione capped hybrid ytterbium/iron oxide nanoparticles with potential applications as multiplatform contrast agent in medical image techniques has been developed. The influence of ytterbium/iron molar ratio used as precursor, as well as the degree of the autoclave filling on the structural and morphological characteristics of the obtained nanoparticles has been extensively studied. Although all nanoparticles present similar composition, with YbFeO3 being the majority phase, size and morphology of the as synthetized nanoparticles are highly influenced by the critical temperature and by the over -saturation reached during the solvothermal process. We have demonstrated that glutathione properly functionalizes the hybrid nanoparticles, increasing their colloidal stability and decreasing their cytotoxicity. Additionally, they show good imaging in magnetic resonance and X-ray computerized tomography, thereby indicating promising potential as a dual contrast agent. This work presents, for the first time, glutathione functionalized ytterbium/iron oxide nanoparticles with potential applications in Biomedicine., This work was supported by the Spanish Ministry of Economy and Competitiveness (MAT2015-67354-R) for O.B-M and PID2020-117544RB-I00, for F.G-CPECART-0096-2020, Consejería Salud y Familias. JA Spain; and P20_01293, Consejería Economía, Conocimiento, Empresas y Universidad. JA Spain; for F.G-C; Spanish MCIN/AEI/10.13039/501100011033 (project PID2020-118329RB-I00) for E.N; and MINECO/ FEDER Project MAT2017-87579-R. The authors would like to thank the Nanotechnology in translational hyperthermia RED2018-102626-T network.

High resolution peripheral quantitative computed tomography (HR-pQCT) provides methods for quantifying volumetric bone mineral density and microarchitecture necessary for early diagnosis of bone disease. When combined with a longitudinal imaging protocol and finite element analysis, HR-pQCT can be used to assess bone formation and resorption (i.e., remodeling) and the relationship between this remodeling and mechanical loading (i.e., mechanoregulation) at the tissue level. Herein, 25 patients with a contralateral distal radius fracture were imaged with HR-pQCT at baseline and 9–12 months follow-up: 16 patients were prescribed vitamin D3 with/without calcium supplement based on a blood biomarker measures of bone metabolism and dual-energy X-ray absorptiometry image-based measures of normative bone quantity which indicated diminishing (n = 9) or poor (n = 7) bone quantity and 9 were not. To evaluate the sensitivity of this imaging protocol to microstructural changes, HR-pQCT images were registered for quantification of bone remodeling and image-based micro-finite element analysis was then used to predict local bone strains and derive rules for mechanoregulation. Remodeling volume fractions were predicted by both average values of trabecular and cortical thickness and bone mineral density (R2 > 0.8), whereas mechanoregulation was affected by dominance of the arm and group classification (p < 0.05). Overall, longitudinal, extended HR-pQCT analysis enabled the identification of changes in bone quantity and quality too subtle for traditional measures., Scientific Reports, 12, ISSN:2045-2322

Acute mesenteric ischemia (AMI) is a group of diseases characterized by an interruption of the blood supply to varying portions of the intestine, leading to ischemia and secondary inflammatory changes. If untreated, this process may progress to life-threatening intestinal necrosis. The incidence is low, estimated at 0.09-0.2% of all acute surgical admissions, but increases with age. Although the entity is an uncommon cause of abdominal pain, diligence is required because if untreated, mortality remains in the range of 50%. Early diagnosis and timely surgical intervention are the cornerstones of modern treatment to reduce the high mortality associated with this entity. The advent of endovascular approaches in parallel with modern imaging techniques is evolving and provides new treatment options. Lastly, a focused multidisciplinary approach based on early diagnosis and individualized treatment is essential. Thus, we believe that updated guidelines from World Society of Emergency Surgery are warranted, in order to provide the most recent and practical recommendations for diagnosis and treatment of AMI.

ObjectiveAortic valve calcification (AVC) and coronary artery calcification (CAC) are predictors of cardiovascular disease (CVD), presumably sharing risk factors. Our objectives were to determine the prevalence and extent of AVC in a large population of men aged 60–74 years and to assess the association between AVC and cardiovascular risk factors including CAC and biomarkers.MethodsParticipants from the DANish CArdioVAscular Screening and intervention trial (DANCAVAS) with AVC and CAC scores and without previous valve replacement were included in the study. Calcification scores were calculated on non-contrast CT scans. Cardiovascular risk factors were self-reported, measured or both, and further explored using descriptive and regression analysis for AVC association.Results14 073 men aged 60–74 years were included. The AVC scores ranged from 0 to 9067 AU, with a median AVC of 6 AU (IQR 0–82). In 8156 individuals (58.0%), the AVC score was >0 and 215 (1.5%) had an AVC score ≥1200. In the regression analysis, all cardiovascular risk factors were associated with AVC; however, after inclusion of CAC ≥400, only age (ratio of expected counts (REC) 1.07 (95% CI 1.06 to 1.09)), hypertension (REC 1.24 (95% CI 1.09 to 1.41)), obesity (REC 1.34 (95% CI 1.20 to 1.50)), known CVD (REC 1.16 (95% CI 1.03 to 1.31)) and serum phosphate (REC 2.25 (95% CI 1.66 to 3.10) remained significantly associated, while smoking, diabetes, hyperlipidaemia, estimated glomerular filtration rate and serum calcium were not.ConclusionsAVC was prevalent in the general population of men aged 60–74 years and was significantly associated with all modifiable cardiovascular risk factors, but only selectively after adjustment for CAC ≥400 AU.Trial registration numberNCT03946410 and ISRCTN12157806.

Objectives Degenerative thoracic aortic aneurysm (TAA) patients are known to be at risk of life-threatening acute aortic events. Guidelines recommend preemptive surgery at diameters of greater than 55 mm, although many patients with small aneurysms show only mild growth rates and more than half of complications occur in aneurysms below this threshold. Thus, assessment of hemodynamics using 4-dimensional flow magnetic resonance has been of interest to obtain more insights in aneurysm development. Nonetheless, the role of aberrant flow patterns in TAA patients is not yet fully understood. Materials and Methods A total of 25 TAA patients and 22 controls underwent time-resolved 3-dimensional phase contrast magnetic resonance imaging with 3-directional velocity encoding (ie, 4-dimensional flow magnetic resonance imaging). Hemodynamic parameters such as vorticity, helicity, and wall shear stress (WSS) were calculated from velocity data in 3 anatomical segments of the ascending aorta (root, proximal, and distal). Regional WSS distribution was assessed for the full cardiac cycle. Results Flow vorticity and helicity were significantly lower for TAA patients in all segments. The proximal ascending aorta showed a significant increase in peak WSS in the outer curvature in TAA patients, whereas WSS values at the inner curvature were significantly lower as compared with controls. Furthermore, positive WSS gradients from sinotubular junction to midascending aorta were most prominent in the outer curvature, whereas from midascending aorta to brachiocephalic trunk, the outer curvature showed negative WSS gradients in the TAA group. Controls solely showed a positive gradient at the inner curvature for both segments. Conclusions Degenerative TAA patients show a decrease in flow vorticity and helicity, which is likely to cause perturbations in physiological flow patterns. The subsequent differing distribution of WSS might be a contributor to vessel wall remodeling and aneurysm formation.

This work presents a rapid and facile way to access the cell wall of wood with magnetic nanoparticles (NPs), providing insights into a method of wood modification to prepare hybrid bio-based functional materials. Diffusion-driven infiltration into Scots pine (Pinus sylvestris L.) sapwood was achieved using colloidal Fe3O4 nanoparticles. Optical microscopy, scanning electron microscopy/energy-dispersive X-ray spectroscopy, transmission electron microscopy, and X-ray powder diffraction analyses were used to detect and assess the accessibility of the cell wall to Fe3O4. The structural changes, filling of tracheids (cell lumina), and NP infiltration depth were further evaluated by performing X-ray microcomputed tomography analysis. Fourier transform infrared spectroscopy was used to assess the chemical changes in Scots pine induced by the interaction of the wood with the solvent. The thermal stability of Fe3O4-modified wood was studied by thermogravimetric analysis. Successful infiltration of the Fe3O4 NPs was confirmed by measuring the magnetic properties of cross-sectioned layers of the modified wood. The results indicate the feasibility of creating multiple functionalities that may lead to many future applications, including structural nanomaterials with desirable thermal properties, magnetic devices, and sensors., The work has been supported by the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS) in the Project “Utilization of solid inorganic waste from the aquaculture industry as wood reinforcement material for flame retardancy” (Grant No. 2018-01198). Magnetic characterization at G.U. has been supported by the US NSF (ECCS-1933527). The acquisition of a Magnetic Property Measurement System (MPMS3, Quantum Design) at G.U. used here was supported by the US NSF (DMR-1828420). We acknowledge Dr. Agnieszka Ziolkowska at the Umeå Centre for Electron Microscopy (UCEM), Sweden, and the National Microscopy Infrastructure, NMI (VR-RFI 2019-00217) for providing assistance in TEM microscopy.

Radiomics is the quantitative analysis of standard-of-care medical imaging; the information obtained can be applied within clinical decision support systems to create diagnostic, prognostic, and/or predictive models. Radiomics analysis can be performed by extracting hand-crafted radiomics features or via deep learning algorithms. Radiomics has evolved tremendously in the last decade, becoming a bridge between imaging and precision medicine. Radiomics exploits sophisticated image analysis tools coupled with statistical elaboration to extract the wealth of information hidden inside medical images, such as computed tomography (CT), magnetic resonance (MR), and/or Positron emission tomography (PET) scans, routinely performed in the everyday clinical practice. Many efforts have been devoted in recent years to the standardization and validation of radiomics approaches, to demonstrate their usefulness and robustness beyond any reasonable doubts. However, the booming of publications and commercial applications of radiomics approaches warrant caution and proper understanding of all the factors involved to avoid "scientific pollution" and overly enthusiastic claims by researchers and clinicians alike. For these reasons the present review aims to be a guidebook of sorts, describing the process of radiomics, its pitfalls, challenges, and opportunities, along with its ability to improve clinical decision-making, from oncology and respiratory medicine to pharmacological and genotyping studies.

Objective Coronary artery calcium (CAC) score is a strong predictor for future adverse cardiovascular events. Anthropomorphic phantoms are often used for CAC studies on computed tomography (CT) to allow for evaluation or variation of scanning or reconstruction parameters within or across scanners against a reference standard. This often results in large number of datasets. Manual assessment of these large datasets is time consuming and cumbersome. Therefore, this study aimed to develop and validate a fully automated, open-source quantification method (FQM) for coronary calcium in a standardized phantom.Materials and Methods A standard, commercially available anthropomorphic thorax phantom was used with an insert containing nine calcifications with different sizes and densities. To simulate two different patient sizes, an extension ring was used. Image data were acquired with four state-of-the-art CT systems using routine CAC scoring acquisition protocols. For interscan variability, each acquisition was repeated five times with small translations and/or rotations. Vendor-specific CAC scores (Agatston, volume, and mass) were calculated as reference scores using vendor-specific software. Both the international standard CAC quantification methods as well as vendor-specific adjustments were implemented in FQM. Reference and FQM scores were compared using Bland-Altman analysis, intraclass correlation coefficients, risk reclassifications, and Cohen's kappa. Also, robustness of FQM was assessed using varied acquisitions and reconstruction settings and validation on a dynamic phantom. Further, image quality metrics were implemented: noise power spectrum, task transfer function, and contrast- and signal-to-noise ratio among others. Results were validated using imQuest software.Results Three parameters in CAC scoring methods varied among the different vendor-specific software packages: the Hounsfield unit (HU) threshold, the minimum area used to designate a group of voxels as calcium, and the usage of isotropic voxels for the volume score. The FQM was in high agreement with vendor-specific scores and ICC's (median [95% CI]) were excellent (1.000 [0.999-1.000] to 1.000 [1.000-1.000]). An excellent interplatform reliability of kappa = 0.969 and kappa = 0.973 was found. TTF results gave a maximum deviation of 3.8% and NPS results were comparable to imQuest.Conclusions We developed a fully automated, open-source, robust method to quantify CAC on CT scans in a commercially available phantom. Also, the automated algorithm contains image quality assessment for fast comparison of differences in acquisition and reconstruction parameters.

Medical imaging techniques, such as (cone beam) computed tomography and magnetic resonance imaging, have proven to be a valuable component for oral and maxillofacial surgery (OMFS). Accurate segmentation of the mandible from head and neck (H&N) scans is an important step in order to build a personalized 3D digital mandible model for 3D printing and treatment planning of OMFS. Segmented mandible structures are used to effectively visualize the mandible volumes and to evaluate particular mandible properties quantitatively. However, mandible segmentation is always challenging for both clinicians and researchers, due to complex structures and higher attenuation materials, such as teeth (filling) or metal implants that easily lead to high noise and strong artifacts during scanning. Moreover, the size and shape of the mandible vary to a large extent between individuals. Therefore, mandible segmentation is a tedious and time-consuming task and requires adequate training to be performed properly. With the advancement of computer vision approaches, researchers have developed several algorithms to automatically segment the mandible during the last two decades. The objective of this review was to present the available fully (semi)automatic segmentation methods of the mandible published in different scientific articles. This review provides a vivid description of the scientific advancements to clinicians and researchers in this field to help develop novel automatic methods for clinical applications.

Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 +/- 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean +/- standard deviation [SD], 19.5 +/- 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 +/- 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 +/- 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

Zusammenfassung Kachexie wird als multifaktorielles Syndrom definiert, das durch einen unfreiwillig fortschreitenden Gewichtsverlust infolge einer Verringerung der Skelettmuskelmasse mit oder ohne Reduktion des Fettgewebes gekennzeichnet ist. Der Abbau von Muskelgewebe wird als Sarkopenie bezeichnet. Diese wird klinisch als Verlust von Muskelmasse und/oder Muskelkraft definiert, wobei der Verlust von Muskelkraft im Vordergrund steht. Mit Sarkopenie verbunden ist der Zustand der Myosteatose, der durch eine Zunahme der intra- und extrazellularen Fettspeicher gekennzeichnet ist und mit einer verminderten Muskelfunktion einhergeht. Kachexie ist fur den Tod von mindestens 20% aller Krebspatienten mitverantwortlich. Die Inzidenz variiert bei diesen Patienten je nach Art der Erkrankung zwischen 80% fur Patienten mit Magen- und Bauchspeicheldrusenkrebs, 50% fur Patienten mit Lungen-, Dickdarm- und Prostatakrebs sowie etwa 40% fur Patienten mit Brustkrebs oder Leukamie. Hierbei ist eine Unterscheidung zwischen tumorassoziierter Kachexie und einer durch Nebenwirkungen und Komplikationen der onkologischen Therapie bedingten Kachexie oft schwierig. Das wesentliche klinische Merkmal der Kachexie ist ein unfreiwilliger Gewichtsverlust, der sich jedoch nicht immer klinisch manifestiert, sodass die Identifizierung von Risikopatienten erheblich erschwert ist. Nicht nur das Langzeit-Outcome der Patienten wird von Kachexie und Sarkopenie beeinflusst. Auch die unmittelbaren postoperativen Komplikationsraten (Morbiditat) werden erhoht und haben tiefgreifende Auswirkungen auf die Krankheitslast und das Leiden der Patienten nach einer chirurgischen Behandlung. Kachexie, Sarkopenie und Myosteatose sind somit fur den klinischen Alltag hochrelevante Parameter, die einen signifikanten Einfluss auf das postoperative Outcome der Patienten haben. Es wurden verschiedene Methoden entwickelt, um die fruhzeitige Identifizierung von Patienten mit einem erhohten Risiko zu verbessern. Diese bieten die Moglichkeit, ungewollten Gewichtsverlust, verringerte Muskelkraft und die Fitness der Patienten zu testen. Derartige Ma ss nahmen sollten Teil unserer taglichen klinischen Routine werden, um diejenigen Patienten mit dem hochsten postoperativen Risiko zu erkennen. Entsprechend konnen neuartige Prakonditionierungskonzepte fur bestimmte Patientengruppen in der Lage sein, die postoperative Morbiditat zu verringern.Abstract Cachexia is defined as a multifactorial syndrome characterised by involuntary progressive weight loss due to a decrease in skeletal muscle mass, with or without a reduction in adipose tissue. The breakdown of muscle tissue is known as sarcopenia. This is clinically defined as loss of muscle mass and/or muscle strength, with loss of muscle strength being more important than muscle mass. Cachexia is responsible for the death of at least 20% of all cancer patients. The incidence in these patients varies, depending on the type of disease, between 80% for patients with gastric and pancreatic cancer, 50% for patients with lung, colon and prostate cancer, and about 40% for patients with breast cancer or leukemia. It is often difficult to distinguish between tumour-associated cachexia and cachexia caused by side effects and complications of oncological therapy. The main clinical feature of cachexia is involuntary weight loss, but this does not always manifest itself clinically, making it much more difficult to identify patients at risk. Not only the long-term outcome of the patient is influenced by cachexia and sarcopenia. Immediate postoperative complication rates (morbidity) are also increased and have profound effects on the burden of disease and the suffering of patients after surgical treatment. Cachexia, sarcopenia and myosteatosis are therefore highly relevant parameters for everyday clinical practice, which have a significant influence on the postoperative outcome of the patient. Several tools have been developed to aid the identification of patients with nutritional risk, i.e. involuntary weight loss, reduced muscle strength and physical condition. Such measures should be a part of our daily clinical routine to ensure the identification of patients with the highest postoperative risk. Novel preconditioning treatment may be beneficial to certain patient groups to reduce postoperative morbidity.

Background Computed tomography angiography (CTA) imaging is needed in current guideline-based stroke diagnosis, and infarct core size is one factor in guiding treatment decisions. We studied the efficacy of a convolutional neural network (CNN) in final infarct volume prediction from CTA and compared the results to a CT perfusion (CTP)-based commercially available software (RAPID, iSchemaView). Methods We retrospectively selected 83 consecutive stroke cases treated with thrombolytic therapy or receiving supportive care that presented to Helsinki University Hospital between January 2018 and July 2019. We compared CNN-derived ischaemic lesion volumes to final infarct volumes that were manually segmented from follow-up CT and to CTP-RAPID ischaemic core volumes. Results An overall correlation of r = 0.83 was found between CNN outputs and final infarct volumes. The strongest correlation was found in a subgroup of patients that presented more than 9 h of symptom onset (r = 0.90). A good correlation was found between the CNN outputs and CTP-RAPID ischaemic core volumes (r = 0.89) and the CNN was able to classify patients for thrombolytic therapy or supportive care with a 1.00 sensitivity and 0.94 specificity. Conclusions A CTA-based CNN software can provide good infarct core volume estimates as observed in follow-up imaging studies. CNN-derived infarct volumes had a good correlation to CTP-RAPID ischaemic core volumes.