Search

Computer-assisted surgery (CAS) allows clinicians to personalize treatments and surgical interventions and has therefore become an increasingly popular treatment modality in maxillofacial surgery. The current maxillofacial CAS consists of three main steps: (1) CT image reconstruction, (2) bone segmentation, and (3) surgical planning. However, each of these three steps can introduce errors that can heavily affect the treatment outcome. As a consequence, tedious and time-consuming manual post-processing is often necessary to ensure that each step is performed adequately. One way to overcome this issue is by developing and implementing neural networks (NNs) within the maxillofacial CAS workflow. These learning algorithms can be trained to perform specific tasks without the need for explicitly defined rules. In recent years, an extremely large number of novel NN approaches have been proposed for a wide variety of applications, which makes it a difficult task to keep up with all relevant developments. This study therefore aimed to summarize and review all relevant NN approaches applied for CT image reconstruction, bone segmentation, and surgical planning. After full text screening, 76 publications were identified: 32 focusing on CT image reconstruction, 33 focusing on bone segmentation and 11 focusing on surgical planning. Generally, convolutional NNs were most widely used in the identified studies, although the multilayer perceptron was most commonly applied in surgical planning tasks. Moreover, the drawbacks of current approaches and promising research avenues are discussed.

Computer-assisted surgery (CAS) allows clinicians to personalize treatments and surgical interventions and has therefore become an increasingly popular treatment modality in maxil-lofacial surgery. The current maxillofacial CAS consists of three main steps: (1) CT image reconstruction, (2) bone segmentation, and (3) surgical planning. However, each of these three steps can introduce errors that can heavily affect the treatment outcome. As a consequence, tedious and time-consuming manual post-processing is often necessary to ensure that each step is performed adequately. One way to overcome this issue is by developing and implementing neural networks (NNs) within the maxillofacial CAS workflow. These learning algorithms can be trained to perform specific tasks without the need for explicitly defined rules. In recent years, an extremely large number of novel NN approaches have been proposed for a wide variety of applications, which makes it a difficult task to keep up with all relevant developments. This study therefore aimed to summarize and review all relevant NN approaches applied for CT image reconstruction, bone segmentation, and surgical planning. After full text screening, 76 publications were identified: 32 focusing on CT image reconstruction, 33 focusing on bone segmentation and 11 focusing on surgical planning. Generally, convolutional NNs were most widely used in the identified studies, although the multilayer perceptron was most commonly applied in surgical planning tasks. Moreover, the drawbacks of current approaches and prom-ising research avenues are discussed.Dentomaxillofacial Radiology (2022) 51, 20210437. doi: 10.1259/dmfr.20210437

Patients with SARS-CoV-2 infection present with different lung compliance and progression of disease differs. Measures of lung mechanics in SARS-CoV-2 patients may unravel different pathophysiologic mechanisms during mechanical ventilation. The objective of this prospective observational study is to describe whether Electrical Impedance Tomography (EIT) guided positive end-expiratory pressure (PEEP) levels unravel changes in EIT-derived parameters over time and whether the changes differ between survivors and non-survivors. Serial EIT-measurements of alveolar overdistension, collapse, and compliance change in ventilated SARS-CoV-2 patients were analysed. In 80 out of 94 patients, we took 283 EIT measurements (93 from day 1–3 after intubation, 66 from day 4–6, and 124 from day 7 and beyond). Fifty-one patients (64%) survived the ICU. At admission mean PaO2/FiO2-ratio was 184.3 (SD 61.4) vs. 151.3 (SD 54.4) mmHg, (p = 0.017) and PEEP was 11.8 (SD 2.8) cmH2O vs. 11.3 (SD 3.4) cmH2O, (p = 0.475), for ICU survivors and non-survivors. At day 1–3, compliance was ~ 55 mL/cmH2O vs. ~ 45 mL/cmH2O in survivors vs. non-survivors. The intersection of overdistension and collapse curves appeared similar at a PEEP of ~ 12–13 cmH2O. At day 4–6 compliance changed to ~ 50 mL/cmH2O vs. ~ 38 mL/cmH2O. At day 7 and beyond, compliance was ~ 38 mL/cmH2O with the intersection at a PEEP of ~ 9 cmH2O vs. ~ 25 mL/cmH2O with overdistension intersecting at collapse curves at a PEEP of ~ 7 cmH2O. Surviving SARS-CoV-2 patients show more favourable EIT-derived parameters and a higher compliance compared to non-survivors over time. This knowledge is valuable for discovering the different groups.

Item does not contain fulltext Purpose To evaluate interobserver variability in the morphologic tumor response assessment of colorectal liver metastases (CRLM) managed with systemic therapy and to assess the relation of morphologic response with gene mutation status, targeted therapy, and Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 measurements. Materials and Methods Participants with initially unresectable CRLM receiving different systemic therapy regimens from the randomized, controlled CAIRO5 trial (NCT02162563) were included in this prospective imaging study. Three radiologists independently assessed morphologic tumor response on baseline and first follow-up CT scans according to previously published criteria. Two additional radiologists evaluated disagreement cases. Interobserver agreement was calculated by using Fleiss κ. On the basis of the majority of individual radiologic assessments, the final morphologic tumor response was determined. Finally, the relation of morphologic tumor response and clinical prognostic parameters was assessed. Results In total, 153 participants (median age, 63 years [IQR, 56-71]; 101 men) with 306 CT scans comprising 2192 CRLM were included. Morphologic assessment performed by the three radiologists yielded 86 (56%) agreement cases and 67 (44%) disagreement cases (including four major disagreement cases). Overall interobserver agreement between the panel radiologists on morphology groups and morphologic response categories was moderate (κ = 0.53, 95% CI: 0.48, 0.58 and κ = 0.54, 95% CI: 0.47, 0.60). Optimal morphologic response was particularly observed in patients treated with bevacizumab (P = .001) and in patients with RAS/BRAF mutation (P = .04). No evidence of a relationship between RECIST 1.1 and morphologic response was found (P = .61). Conclusion Morphologic tumor response assessment following systemic therapy in participants with CRLM demonstrated considerable interobserver variability. Keywords: Tumor Response, Observer Performance, CT, Liver, Metastases, Oncology, Abdomen/Gastrointestinal Clinical trial registration no. NCT02162563 Supplemental material is available for this article. © RSNA, 2022.

Objective: To assess interobserver agreement among radiologists regarding the current Fleischner Society diagnostic criteria for usual interstitial pneumonia (UIP) patterns on computed tomography (CT). Materials and Methods: Using the Fleischner Society criteria for UIP CT patterns, five raters, working independently, categorized the high-resolution CT (HRCT) scans of 44 patients with interstitial lung disease who underwent lung biopsy. The raters also evaluated the presence, extent, and distribution of the most relevant imaging findings, as well as indicating their level of confidence in the most likely diagnosis and in up to three diagnostic hypotheses. Results: There was moderate to substantial interobserver agreement regarding the UIP patterns on HRCT—kappa statistic (κ) = 0.59-0.61. Interobserver agreement for the binary scores was substantial (κ = 0.77-0.79), whereas that for the presence of honeycombing was almost perfect (κ = 0.81-0.96). There was agreement regarding at least one of the three diagnostic hypotheses in only 36.4% of the cases. For the level of confidence in the most likely diagnosis, there was only slight to fair agreement (κ = 0.19-0.21). Conclusion: Interobserver agreement regarding the current Fleischner Society CT criteria for UIP was moderate to substantial among raters with varying levels of experience. There was only slight to fair agreement regarding the diagnostic hypotheses and for the level of confidence in the most likely diagnosis. Resumo Objetivo: Avaliar a concordância interobservador entre radiologistas para os critérios atuais da Fleischner Society para categorias diagnósticas de pneumonia intersticial usual (PIU) em tomografia computadorizada (TC). Materiais e Métodos: Cinco observadores categorizaram independentemente as imagens de TC de 44 pacientes com doença pulmonar intersticial que foram submetidos a biópsia pulmonar empregando as últimas categorias de diagnóstico da Sociedade Fleischner para UIP. Também foram avaliadas presença, extensão e distribuição dos achados de imagem mais relevantes, bem como a confiança no diagnóstico mais provável e em até três hipóteses diagnósticas. Resultados: Houve concordância moderada a alta para as categorias diagnósticas entre os observadores (κ = 0,59-0,61). A concordância interobservador para a pontuação binária foi alta (κ = 0,77-0,79), enquanto para a presença de faveolamento foi considerada de alta a muito alta (κ = 0,81-0,96). Houve concordância em uma das três hipóteses diagnósticas em apenas 36,4% dos casos. Baixa concordância foi encontrada para o diagnóstico mais provável (κ = 0,19-0,21). Conclusão: A concordância entre observadores para os critérios atuais de TC da Fleischner Society para UIP foi moderada a alta entre observadores com diferentes níveis de experiência. Houve baixa concordância nas hipóteses diagnósticas e quanto ao grau de confiança no diagnóstico primário.

Extracting the cerebral anterior vessel tree of patients with an intracranial large vessel occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to treatment decision making. The purpose of our work is to develop a method that can achieve this from routinely acquired computed tomography angiography (CTA) and computed tomography perfusion (CTP) images. To this end, we regard the anterior vessel tree as a set of bifurcations and connected centerlines. The method consists of a proximal policy optimization (PPO) based deep reinforcement learning (DRL) approach for tracking centerlines, a convolutional neural network based bifurcation detector, and a breadth-first vessel tree construction approach taking the tracking and bifurcation detection results as input. We experimentally determine the added values of various components of the tracker. Both DRL vessel tracking and CNN bifurcation detection were assessed in a cross validation experiment using 115 subjects. The anterior vessel tree formation was evaluated on an independent test set of 25 subjects, and compared to interobserver variation on a small subset of images. The DRL tracking result achieves a median overlapping rate until the first error (1.8 mm off the reference standard) of 100, [46, 100] % on 8032 vessels over 115 subjects. The bifurcation detector reaches an average recall and precision of 76% and 87% respectively during the vessel tree formation process. The final vessel tree formation achieves a median recall of 68% and precision of 70%, which is in line with the interobserver agreement.

Background and purposeCT perfusion (CTP) might support decision making in patients with acute ischemic stroke by providing perfusion maps of ischemic tissue. Currently, the reliability of CTP is hampered by varying results between different post-processing software packages. The purpose of this study is to compare ischemic core volumes estimated by IntelliSpace Portal (ISP) and syngo.via with core volumes as estimated by RAPID.MethodsThirty-five CTP datasets from patients in the MR CLEAN trial were post-processed. Core volumes were estimated with ISP using default settings and with syngo.via using three different settings: default settings (method A); additional smoothing filter (method B); and adjusted settings (method C). The results were compared with RAPID. Agreement between methods was assessed using Bland–Altman analysis and intraclass correlation coefficient (ICC). Accuracy for detecting volumes up to 25 mL, 50 mL, and 70 mL was assessed. Final infarct volumes were determined on follow-up non-contrast CT.ResultsMedian core volume was 50 mL with ISP, 41 mL with syngo.via method A, 20 mL with method B, 36 mL with method C, and 11 mL with RAPID. Agreement ranged from poor (ISP: ICC 0.41; method A: ICC 0.23) to good (method B: ICC 0.83; method C: ICC 0.85). The bias (1.8 mL) and limits of agreement (−27, 31 mL) were the smallest with syngo.via with additional smoothing (method B). Agreement for detecting core volumes ≤25 mL with ISP was 54% and 57%, 85% and 74% for syngo.via methods A, B, and C, respectively.ConclusionBest agreement with RAPID software is provided by syngo.via default settings with additional smoothing. Moreover, this method has the highest agreement in categorizing patients with small core volumes.

Summary This study developed a well-standardized and reproducible approach for micro-finite element (mFE) and homogenized-FE (hFE) analyses that can accurately predict the distal radius failure load using either mFE or hFE models when using the approaches and parameters developed in this study. Introduction Micro-FE analyses based on high-resolution peripheral quantitative CT (HR-pQCT) images are frequently used to predict distal radius failure load. With the introduction of a second-generation HR-pQCT device, however, the default modelling approach no longer provides accurate results. The aim of this study was to develop a well-standardized and reproducible approach for mFE and hFE analyses that can provide precise and accurate results for distal radius failure load predictions based on second-generation HR-pQCT images. Methods Second-generation HR-pQCT was used to scan the distal 20-mm section of 22 cadaver radii. The sections were excised and mechanically tested afterwards. For these sections, mFE and hFE models were made that were used to identify required material parameters by comparing predicted and measured results. Using these parameters, the models were cropped to represent the 10-mm region recommended for clinical studies to test their performance for failure load prediction. Results After identification of material parameters, the measured failure load of the 20-mm segments was in good agreement with the results of mFE models (R2 = 0.969, slope = 1.035) and hFE models (R2 = 0.966, slope = 0.890). When the models were restricted to the clinical region, mFE still accurately predicted the measured failure load (R2 = 0.955, slope = 1.021), while hFE predictions were precise but tended to overpredict the failure load (R2 = 0.952, slope = 0.780). Conclusions It was concluded that it is possible to accurately predict the distal radius failure load using either mFE or hFE models when using the approaches and parameters developed in this study. Electronic supplementary material The online version of this article (10.1007/s00198-019-04935-6) contains supplementary material, which is available to authorized users.

Background: The aim of this study was to assess the potential of rest-stress DECT iodine quantification to discriminate between normal, ischemic, and infarcted myocardium.Methods: Patients who underwent rest-stress DECT on a 2nd generation dual-source system and cardiac magnetic resonance (CMR) were retrospectively included from a prospective study cohort. CMR was performed to identify ischemic and infarcted myocardium and categorize patients into ischemic, infarcted, and control groups. Controls were analyzed on a per-slice and per-segment basis. Regions of interest (ROIs) were placed in ischemic and infarcted areas based on CMR. Additionally, ROIs were placed in the septal area to assess normal and remote myocardium.Results: We included 42 patients: 10 ischemic, 17 infarcted, and 15 controls. Iodine concentrations showed no significant between segments in controls. Iodine concentrations for normal myocardium increased significantly from rest to stress (median 3.7 mg/mL (interquartile range 3.5-3.9) vs. 4.5 mg/mL (4.3-4.9)) (p Conclusion: DECT iodine concentration from rest-stress imaging can potentially differentiate between normal, ischemic, and infarcted myocardium.

High-resolution peripheral quantitative computed tomography (HR-pQCT) is a powerful tool to assess bone health. To determine how an individual's or population of interest's HR-pQCT outcomes compare to expected, reference data are required. This study provides reference data for HR-pQCT measures acquired in a population of White adults.PURPOSE: To provide age- and sex-specific reference data for high-resolution peripheral quantitative computed tomography (HR-pQCT) measures of the distal and diaphyseal radius and tibia acquired using a second-generation scanner and percent-of-length offsets proximal from the end of the bone.METHODS: Data were acquired in White adults (aged 18-80 years) living in the Midwest region of the USA. HR-pQCT scans were performed at the 4% distal radius, 30% diaphyseal radius, 7.3% distal tibia, and 30% diaphyseal tibia. Centile curves were fit to the data using the LMS approach.RESULTS: Scans of 867 females and 317 males were included. The fitted centile curves reveal HR-pQCT differences between ages, sexes, and sites. They also indicate differences when compared to data obtained by others using fixed length offsets. Excel-based calculators based on the current data were developed and are provided to enable computation of subject-specific percentiles, z-scores, and t-scores and to plot an individual's outcomes on the fitted curves. In addition, regression equations are provided to convert estimated failure load acquired with the conventional criteria utilized with first-generation scanners and those specifically developed for second-generation scanners.CONCLUSION: The current study provides unique data and resources. The combination of the reference data and calculators provide clinicians and investigators an ability to assess HR-pQCT outcomes in an individual or population of interest, when using the described scanning and analysis procedure. Ultimately, the expectation is these data will be expanded over time so the wealth of information HR-pQCT provides becomes increasingly interpretable and utilized.

Current therapy for hypervascular cancers, e.g., hepatocellular carcinoma, includes occlusion of the tumor blood supply by arterial infusion of embolic microspheres (beads) suspended in iodine-based contrast under fluoroscopic guidance. Available radiopaque, imageable beads use iodine as the radiopacifier and cannot be differentiated from contrast. This study aimed to synthesize and characterize imageable beads using bismuth as the radiopacifier that could be distinguished from iodine contrast based upon the difference in the binding energy of k-shell electrons (k-edge). Radiodense bismuth beads were successfully synthesized some with uniform bismuth distribution across the beads. The beads were spherical and could be infused through clinical microcatheters. The bismuth beads could be imaged with clinical dual-energy computed tomography (CT), where iodine-based contrast could be distinguished from the microspheres. The ability to separate iodine from bismuth may enhance the diagnostic information acquired on follow-up CT, identifying the distribution of the embolic beads separately from the contrast. Furthermore, with sequential use of iodine- and bismuth-based beads, the two radiopaque beads could be spatially distinguished on imaging, which may enable the development of dual drug delivery and dual tracking.

This review provides an overview of the currently available computed tomography (CT) techniques for myocardial tissue characterization in ischemic heart disease, including CT perfusion and late iodine enhancement. CT myocardial perfusion imaging can be performed with static and dynamic protocols for the detection of ischemia and infarction using either single- or dual-energy CT modes. Late iodine enhancement may be used for the analysis of myocardial infarction. The accuracy of these CT techniques is highly dependent on the imaging protocol, including acquisition timing and contrast administration. Additionally, the options for qualitative and quantitative analysis and the accuracy of each technique are discussed.

Background and Purpose In patients with severe emphysema, dynamic hyperinflation is superimposed on top of already existing static hyperinflation. Static hyperinflation reduces significantly after bronchoscopic lung volume reduction (BLVR). In this study, we investigated the effect of BLVR compared to standard of care (SoC) on dynamic hyperinflation. Methods Dynamic hyperinflation was induced by a manually paced tachypnea test (MPT) and was defined by change in inspiratory capacity (IC) measured before and after MPT. Static and dynamic hyperinflation measurements were performed both at baseline and 6 months after BLVR with endobronchial valves or coils (treatment group) or SoC (control group). Results Eighteen patients underwent BLVR (78% female, 57 (43–67) years, FEV1 25(18–37) %predicted, residual volume 231 (182–376) %predicted). Thirteen patients received SoC (100% female, 59 (44–74) years, FEV1 25 (19–37) %predicted, residual volume 225 (152–279) %predicted. The 6 months median change in dynamic hyperinflation in the treatment group was: + 225 ml (range − 113 to + 803) (p p = 0.422). An increase in dynamic hyperinflation was significantly associated with a decrease in residual volume (r = − 0.439, p Conclusion Bronchoscopic lung volume reduction increases the ability for dynamic hyperinflation in patients with severe emphysema. We propose this is a consequence of improved static hyperinflation.

Spatial understanding of osteoarticular deformities of the foot and ankle is vital to correct diagnosis and therapeutic decision making. Poor reproducibility in conventional standing radiography in three orthogonal views has driven the development of weight-bearing computed tomography (WBCT) technology over the last decade. We analyzed the available literature on WBCT imaging in patients with foot and ankle disorders by performing a literature review of relevant clinical studies in multiple databases including PubMed, MedLine, and Scopus from January 1999 to October 2017. WBCT imaging allows correct evaluation of foot and ankle anatomy with the patient in a standing position, providing images with high spatial resolution, short image acquisition time, low dose of radiation, and costs which are similar to other available imaging technologies. This diagnostic tool can be used for decision making in the treatment of deformities of the ankle, hindfoot, midfoot, and forefoot. Level of Evidence III; Systematic review of level III studies. RESUMO Na topografia do tornozelo e do pé é fundamental o entendimento espacial das deformidades osteoarticulares para correto diagnóstico e decisão terapêutica. A dificuldade de reprodução da avaliação com radiografias convencionais em posição ortostática em três dimensões impulsionou, na última década, o desenvolvimento da tecnologia de tomografia computadoriza com carga. Analisamos a literatura relacionada com o tema tomografia computadorizada com carga em pacientes com distúrbios do pé e do tornozelo. Para fazer isso, realizamos uma revisão da literatura de estudos clínicos relevantes nas bases de bancos eletrônicos, incluindo PubMed, MedLine e Scopus, de janeiro de 1999 a outubro de 2017. A tomografia computadorizada com carga permite a avaliação da anatomia na posição ortostática fisiológica, com imagens de alta resolução espacial, pequeno tempo de aquisição de imagens, baixa dose de radiação e custos similares a outras tecnologias atualmente disponíveis. Ela pode ser usada para tomada de decisão terapêutica em deformidades do tornozelo, retropé, mesopé e antepé. Nível de Evidência III; Revisão sistemática de estudos de nível III.

Chronic obstructive pulmonary disease (COPD) is a lung disease which can be quantified using chest computed tomography (CT) scans. Recent studies have shown that COPD can be automatically diagnosed using weakly supervised learning of intensity and texture distributions. However, up till now such classifiers have only been evaluated on scans from a single domain, and it is unclear whether they would generalize across domains, such as different scanners or scanning protocols. To address this problem, we investigate classification of COPD in a multi-center dataset with a total of 803 scans from three different centers, four different scanners, with heterogenous subject distributions. Our method is based on Gaussian texture features, and a weighted logistic classifier, which increases the weights of samples similar to the test data. We show that Gaussian texture features outperform intensity features previously used in multi-center classification tasks. We also show that a weighting strategy based on a classifier that is trained to discriminate between scans from different domains, can further improve the results. To encourage further research into transfer learning methods for classification of COPD, upon acceptance of the paper we will release two feature datasets used in this study on http://bigr.nl/research/projects/copd, Comment: Accepted at Journal of Biomedical and Health Informatics

OBJECTIVE: To determine the accuracy of iodine quantification with dual energy computed tomography (DECT) in two high-end CT systems with different spectral imaging techniques.METHODS: Five tubes with different iodine concentrations (0, 5, 10, 15, 20 mg/ml) were analysed in an anthropomorphic thoracic phantom. Adding two phantom rings simulated increased patient size. For third-generation dual source CT (DSCT), tube voltage combinations of 150Sn and 70, 80, 90, 100 kVp were analysed. For dual layer CT (DLCT), 120 and 140 kVp were used. Scans were repeated three times. Median normalized values and interquartile ranges (IQRs) were calculated for all kVp settings and phantom sizes.RESULTS: Correlation between measured and known iodine concentrations was excellent for both systems (R = 0.999-1.000, p CONCLUSION: Iodine concentration can be accurately quantified with state-of-the-art DECT systems from two vendors. The lowest absolute errors were found for DSCT using the 150Sn/70 kVp or 150Sn/80 kVp combinations, which was slightly more accurate than 140 kVp in DLCT.KEY POINTS: • High-end CT scanners allow accurate iodine quantification using different DECT techniques. • Lowest measurement error was found in scans with largest photon energy separation. • Dual-source CT quantified iodine slightly more accurately than dual layer CT.

Fractures of the distal section of the radius (Colles’ fractures) occur earlier in life than other osteoporotic fractures. Therefore, they can be interpreted as a warning signal for later, more deleterious fractures of vertebral bodies or the femoral neck. In the past decade, the advent of HR-pQCT allowed a detailed architectural analysis of the distal radius and an automated but time-consuming estimation of its strength with linear micro-finite element (μFE) analysis. Recently, a second generation of HR-pQCT scanner (XtremeCT II, SCANCO Medical, Switzerland) with a resolution beyond 61 μm became available for even more refined biomechanical investigations in vivo. This raises the question how biomechanical outcome variables compare between the original (LR) and the new (HR) scanner resolution. Accordingly, the aim of this work was to validate experimentally a patient-specific homogenized finite element (hFE) analysis of the distal section of the human radius for the fast prediction of Colles’ fracture load based on the last generation HR-pQCT. Fourteen pairs of fresh frozen forearms (mean age = 77.5±9) were scanned intact using the high (61 μm) and the low (82 μm) resolution protocols that correspond to the new and original HR-pQCT systems. From each forearm, the 20 mm most distal section of the radius were dissected out, scanned with μCT at 16.4 μm and tested experimentally under compression up to failure for assessment of stiffness and ultimate load. Linear and nonlinear hFE models together with linear micro finite element (μFE) models were then generated based on the μCT and HR-pQCT reconstructions to predict the aforementioned mechanical properties of 24 sections. Precision errors of the short term reproducibility of the FE analyses were measured based on the repeated scans of 12 sections. The calculated failure loads correlated strongly with those measured in the experiments: accounting for donor as a random factor, the nonlinear hFE provided a marginal coefficient of determination (Rm 2) of 0.957 for the high resolution (HR) and 0.948 for the low resolution (LR) protocols, the linear hFE with Rm 2 of 0.957 for the HR and 0.947 for the LR protocols. Linear μFE predictions of the ultimate load were similar with an Rm 2 of 0.950 for the HR and 0.954 for the LR protocols, respectively. Nonlinear hFE strength computation led to precision errors of 2.2 and 2.3% which were higher than the ones calculated based on the linear hFE (1.6 and 1.9%) and linear μFE (1.2 and 1.6%) for the HR and LR protocols respectively. Computation of the fracture load with nonlinear hFE demanded in average 6 h of CPU time which was 3 times faster than with linear μFE, while computation with linear hFE took only a few minutes. This study delivers an extensive experimental and numerical validation for the application of an accurate and fast hFE diagnostic tool to help in identifying individuals who may be at risk of an osteoporotic wrist fracture and to follow up pharmacological and other treatments in such patients.

International audience; BACKGROUND: Patients who have had a stroke with unknown time of onset have been previously excluded from thrombolysis. We aimed to establish whether intravenous alteplase is safe and effective in such patients when salvageable tissue has been identified with imaging biomarkers. METHODS: We did a systematic review and meta-analysis of individual patient data for trials published before Sept 21, 2020. Randomised trials of intravenous alteplase versus standard of care or placebo in adults with stroke with unknown time of onset with perfusion-diffusion MRI, perfusion CT, or MRI with diffusion weighted imaging-fluid attenuated inversion recovery (DWI-FLAIR) mismatch were eligible. The primary outcome was favourable functional outcome (score of 0-1 on the modified Rankin Scale [mRS]) at 90 days indicating no disability using an unconditional mixed-effect logistic-regression model fitted to estimate the treatment effect. Secondary outcomes were mRS shift towards a better functional outcome and independent outcome (mRS 0-2) at 90 days. Safety outcomes included death, severe disability or death (mRS score 4-6), and symptomatic intracranial haemorrhage. This study is registered with PROSPERO, CRD42020166903. FINDINGS: Of 249 identified abstracts, four trials met our eligibility criteria for inclusion: WAKE-UP, EXTEND, THAWS, and ECASS-4. The four trials provided individual patient data for 843 individuals, of whom 429 (51%) were assigned to alteplase and 414 (49%) to placebo or standard care. A favourable outcome occurred in 199 (47%) of 420 patients with alteplase and in 160 (39%) of 409 patients among controls (adjusted odds ratio [OR] 1·49 [95% CI 1·10-2·03]; p=0·011), with low heterogeneity across studies (I(2)=27%). Alteplase was associated with a significant shift towards better functional outcome (adjusted common OR 1·38 [95% CI 1·05-1·80]; p=0·019), and a higher odds of independent outcome (adjusted OR 1·50 [1·06-2·12]; p=0·022). In the alteplase group, 90 (21%) patients were severely disabled or died (mRS score 4-6), compared with 102 (25%) patients in the control group (adjusted OR 0·76 [0·52-1·11]; p=0·15). 27 (6%) patients died in the alteplase group and 14 (3%) patients died among controls (adjusted OR 2·06 [1·03-4·09]; p=0·040). The prevalence of symptomatic intracranial haemorrhage was higher in the alteplase group than among controls (11 [3%] vs two [\textless1%], adjusted OR 5·58 [1·22-25·50]; p=0·024). INTERPRETATION: In patients who have had a stroke with unknown time of onset with a DWI-FLAIR or perfusion mismatch, intravenous alteplase resulted in better functional outcome at 90 days than placebo or standard care. A net benefit was observed for all functional outcomes despite an increased risk of symptomatic intracranial haemorrhage. Although there were more deaths with alteplase than placebo, there were fewer cases of severe disability or death. FUNDING: None.

We evaluated the association between prevalent vertebral fractures and bone micro-architecture and strength measured using HR-pQCT in postmenopausal women with a recent non-vertebral fracture visiting the Fracture Liaison Service. The presence and severity of prevalent vertebral fracture reflect generalized bone deterioration. Introduction We evaluated the association between prevalent vertebral fractures (VFs) and bone micro-architecture and strength measured using HR-pQCT in postmenopausal women visiting the Fracture Liaison Service. Methods In this cross-sectional study in women aged 50-90 with a recent non-vertebral fracture (NVF), VFs were identified on lateral spine images by dual-energy X-ray absorptiometry. Bone micro-architecture and strength were measured at the non-dominant distal radius and distal tibia using HR-pQCT. Linear regression analyses were used to estimate the association between prevalent VFs and HR-pQCT parameters. Results We included 338 women of whom 74 (21.9%) women had at least one prevalent VF. After adjustment for femoral neck aBMD (FN aBMD) and other parameters, women with at least one prevalent vertebral fracture had significantly lower total and trabecular vBMD and trabecular number (beta - 16.7, - 11.8, and - 7.8 in the radius and - 21.4, - 16.6, and - 7.2 in the tibia, respectively), higher trabecular separation at the radius and tibia (beta 9.0 and 9.3, respectively), and lower cortical thickness and calculated ultimate failure load and compressive bone strength at the tibia (beta - 5.9, - 0.6, and - 10.9, respectively) as compared with those without prevalent VFs. Furthermore, more severe prevalent VFs were associated with even lower total and trabecular vBMD and lower ultimate failure load and compressive stiffness at the radius and tibia, and lower trabecular number and higher trabecular separation at the radius. Conclusion This study indicates that the presence and severity of prevalent VFs reflect generalized bone deterioration in women with a recent NVF, independently of FN aBMD. This study was supported by funding of the Weijerhorst Foundation.

Interstitial lung disease (ILD) is highly prevalent in collagen vascular diseases and reduction of ILD is an important therapeutic target. To that end, reliable quantification of pulmonary disease severity is of great significance. This study systematically reviewed the literature on automated computed tomography (CT) quantification methods for assessing ILD in collagen vascular diseases. PRISMA-DTA guidelines for systematic reviews were used and 19 original research articles up to January 2018 were included based on a MEDLINE/Pubmed and Embase search. Quantitative CT methods were categorized as histogram assessment (12 studies) or pattern/texture recognition (7 studies). R 2 for correlation with visual ILD scoring ranged from 0.143 (p < 0.01) to 0.687 (p < 0.0001), for FVC from 0.048 (p < 0.0001) to 0.504 (p < 0.0001) and for DLCO from 0.015 (p = 0.61) to 0.449 (p < 0.0001). Automated CT methods are independent of reader's expertise and are a promising tool in the quantification of ILD in collagen vascular disease patients.

Purpose To assess the radiation dose associated with always-on dual-energy acquisitions in clinical practice over a broad range of clinical protocols using a dual-layer detector CT (DLCT; IQon spectral CT, Philips Healthcare) as compared to an otherwise technically equivalent single-layer detector CT (SLCT; Brilliance iCT, Philips healthcare). Materials and Methods Dose-length-product data for consecutive examinations over a six-month period acquired with DLCT were retrospectively collected and compared to consecutive examinations from an SLCT. Imaging protocols were optimized for diagnostic image quality for each system prior to data collection. Dose reports of CT protocols that were used at least 50 times on both systems were collected. After exclusion of statistical outliers, protocols were evaluated with regard to reported dose levels. Results In total, 4536 dose reports for DLCT and 5783 reports for SLCT were collected. All DLCT examinations were acquired at 120 kVp, enabling dual-energy analysis. With SLCT, 79% of examinations were acquired at 120 kVp, and 21% at 100/80 kVp. Protocols for 15 indications were used more than 50 times on both scanners. For seven protocols there was no significant difference between the two scanners (p > 0.05), whereas seven protocols were acquired with higher dose levels on SLCT compared to the DLCT (p

Image registration, the process of aligning two or more images, is the core technique of many (semi-)automatic medical image analysis tasks. Recent studies have shown that deep learning methods, notably convolutional neural networks (ConvNets), can be used for image registration. Thus far training of ConvNets for registration was supervised using predefined example registrations. However, obtaining example registrations is not trivial. To circumvent the need for predefined examples, and thereby to increase convenience of training ConvNets for image registration, we propose the Deep Learning Image Registration (DLIR) framework for \textit{unsupervised} affine and deformable image registration. In the DLIR framework ConvNets are trained for image registration by exploiting image similarity analogous to conventional intensity-based image registration. After a ConvNet has been trained with the DLIR framework, it can be used to register pairs of unseen images in one shot. We propose flexible ConvNets designs for affine image registration and for deformable image registration. By stacking multiple of these ConvNets into a larger architecture, we are able to perform coarse-to-fine image registration. We show for registration of cardiac cine MRI and registration of chest CT that performance of the DLIR framework is comparable to conventional image registration while being several orders of magnitude faster., Comment: Accepted: Medical Image Analysis - Elsevier

This review provides an overview of the currently available computed tomography (CT) techniques for myocardial tissue characterization in ischemic heart disease, including CT perfusion and late iodine enhancement. CT myocardial perfusion imaging can be performed with static and dynamic protocols for the detection of ischemia and infarction using either single- or dual-energy CT modes. Late iodine enhancement may be used for the analysis of myocardial infarction. The accuracy of these CT techniques is highly dependent on the imaging protocol, including acquisition timing and contrast administration. Additionally, the options for qualitative and quantitative analysis and the accuracy of each technique are discussed.

Distinguishing between kidney stones and phleboliths can constitute a diagnostic challenge in patients undergoing unenhanced low-dose CT (LDCT) for acute flank pain. We sought to investigate the accuracy of radiomics and a machine-learning classifier in differentiating between kidney stones and phleboliths on LDCT. Radiomics features were extracted following a semi-automatic segmentation of kidney stones and phleboliths for two independent consecutive cohorts of patients undergoing LDCT for acute flank pain. Radiomics features from the first cohort of patients (n = 369) were ultimately used to train a machine-learning model designed to distinguish kidney stones (n = 211) from phleboliths (n = 201). Classification performance was assessed on the second independent cohort (i.e., testing set) (kidney stones n = 24; phleboliths n = 23) using positive and negative predictive values (PPV and NPV), area under the receiver operating curves (AUC), and permutation testing. Our machine-learning classification model trained on radiomics features achieved an overall accuracy of 85.1% on the independent testing set, with an AUC of 0.902, PPV of 81.5%, and NPV of 90.0%. Classification accuracy was significantly better than chance on permutation testing (p

Objectives: To study the relationship between structural damage and inflammatory features on magnetic resonance imaging (MRI) or radiography and other risk factors [anti-citrullinated protein antibody (ACPA) and/or rheumatoid factor (RF) seropositivity, hand dominance, disease duration] and the presence or number of cortical interruptions in finger joints on high-resolution peripheral quantitative computed tomography (HR-pQCT). Method: Finger joints of 38 healthy subjects and 39 patients with rheumatoid arthritis (RA) were examined through radiographs, MRI, and HR-pQCT. Radiographs were scored according to the Sharp/van der Heijde (SvH) method; MRI for the presence of cortical interruptions, bone marrow oedema (BMO), and synovitis; and HR-pQCT images for cortical interruptions. Descriptive statistics were calculated and associations examined using generalized estimating equations. Results: Cortical interruptions were found in healthy subjects and patients with RA on HR-pQCT (mean +/- sd 0.33 +/- 0.63 vs 0.38 +/- 0.64 per joint quadrant, respectively, p < 0.01). Structural damage on MRI (cortical interruptions) or radiographs (SvH >= 1) was associated with the presence of cortical interruptions on HR-pQCT [odds ratio (OR) 12.4, 95% confidence interval (CI) 7.5-21.4, p < 0.01 and OR 4.8, 95% CI 1.9-11.7, respectively, p < 0.01]. The presence of BMO or synovitis was associated with more cortical interruptions on HR-pQCT (beta 0.47, 95% CI 0.4-0.6, p < 0.01 and beta 1.9, 95% CI 0.6-3.1, p < 0.01). In patients with RA, ACPA, and/or RF seropositivity, hand dominance and disease duration were not associated with more cortical interruptions on HR-pQCT. Conclusion: Structural damage and inflammatory features on MRI and radiographs are associated with cortical interruptions on HR-pQCT. No association between other risk factors and cortical interruptions was demonstrated. This study was funded by an unrestricted grant from Pfizer and the Weijerhorst Foundation.