Can Whole-body MRI Replace CT in Management of Metastatic Testicular Cancer? A Prospective, Non-inferiority Study.

Purpose Concerns of imaging-related radiation in young patients with high survival rates have increased the use of magnetic resonance imaging (MRI) in testicular cancer (TC) stage I. However, computed tomography (CT) is still preferred for metastatic TC. The purpose of this study was to compare whole-body MRI incl. diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) with contrast-enhanced, thoracoabdominal CT in metastatic TC.Methods A prospective, non-inferiority study of 84 consecutive patients (median age 33 years) with newly diagnosed metastatic TC (February 2018 - January 2021). Exclusion criteria were age <18 years, claustrophobia and MRI contraindications. Patients had both MRI and CT before and after treatment. Anonymised images were reviewed by experienced radiologists.Lesion malignancy was evaluated on a Likert scale (1 benign – 4 malignant). Sensitivity, specificity, positive predictive value, negative predictive value and accuracy were calculated on patient and lesion level. For non-inferiority testing, the difference in sensitivity between CT and MRI was calculated. The level of significance was set at 5%. ROC curves and interobserver agreement were calculated.Results On patient level, MRI had 98% sensitivity and 75% specificity compared to CT. On lesion level within each modality, MRI had 99% sensitivity and 78% specificity, whereas CT had 98% sensitivity and 88% specificity. MRI sensitivity was non-inferior to CT (difference 0.57% (95% CI -1.4-2.5%)). The interobserver agreement was substantial between CT and MRI. Conclusion MRI with DWIBS was non-inferior to contrast-enhanced CT in detecting metastatic TC disease. Trial registration www.clinicaltrials.gov NCT03436901, finished July 1st 2021.

Evaluation of Response to Immune Checkpoint Inhibitors Using a Radiomics, Lesion-Level Approach

Conventional methods to determine the response to immune checkpoint inhibitors (ICIs) are limited by the unique responses to an ICI. We performed a radiomics approach for all measurable lesions to identify radiomic variables that could distinguish hyperprogressive disease (HPD) on baseline CT scans and classify a dissociated response (DR). One hundred and ninety-six patients with advanced lung cancer, treated with ICI monotherapy, who underwent at least three CT scans, were retrospectively enrolled. For all 621 measurable lesions, HPDv was determined from baseline CT scans using the tumor growth kinetics (TGK) ratio, and radiomics features were extracted. Multivariable logistic regression analysis of radiomics features was performed to discriminate DR. Radiomics features that significantly discriminated HPDv on baseline CT differed according to organ. Of the 196 patients, 54 (27.6%) had a DR and 142 (72.4%) did not have a DR. Overall survival in the group with a DR was significantly inferior to that in the group without a DR (log rank test, p = 0.04). Our study shows that lesion-level analysis using radiomics features has great potential for discriminating HPDv and understanding heterogeneous tumor progression, including a DR, after ICI treatment.

Scope of care in the first four years of life for individuals born with myelomeningocele: A single institution experience1

PURPOSE: Children with myelomeningocele are known to be consumers of substantial healthcare resources, with many early hospital encounters. The purpose of this study was to survey the extent of medical and surgical care that patients with myelomeningocele receive during the first four years of life. METHODS: Clinical and demographic data were collected on newborn infants with open myelomeningocele from the Children’s of Alabama Spina Bifida Web Tracker, a prospective, comprehensive spina bifida database. Additional data pertaining to all hospital admissions, surgical procedures, and clinic visits were collected from the medical record. RESULTS: One hundred and fourteen subjects with a primary diagnosis of myelomeningocele between 2004 and 2015 were included. Males slightly predominated (55%), 72%were Caucasian, 11%Hispanic/Latino; 28%had a mid-lumbar functional lesion level. Over the first four years of life, 688 total surgical procedures were performed (an average of 86 per child): 438 in year 1, 100 in year 2, 84 in year 3, and 66 in year 4. The mean number of hospital visits was 40.5. Total average drive time per patient over 4 years being 103.8 hours. Average number of nights spent in the hospital was 51. CONCLUSION: Children with myelomeningocele need multiple hospitalizations, surgeries, and medical encounters in the first 4 years of life. These data will be valuable when counselling new parents and prospective parents of children with this condition.

Detection and Segmentation of Pelvic Bones Metastases in MRI Images for Patients With Prostate Cancer Based on Deep Learning

ObjectiveTo establish and evaluate the 3D U-Net model for automated segmentation and detection of pelvic bone metastases in patients with prostate cancer (PCa) using diffusion-weighted imaging (DWI) and T1 weighted imaging (T1WI) images.MethodsThe model consisted of two 3D U-Net algorithms. A total of 859 patients with clinically suspected or confirmed PCa between January 2017 and December 2020 were enrolled for the first 3D U-Net development of pelvic bony structure segmentation. Then, 334 PCa patients were selected for the model development of bone metastases segmentation. Additionally, 63 patients from January to May 2021 were recruited for the external evaluation of the network. The network was developed using DWI and T1WI images as input. Dice similarity coefficient (DSC), volumetric similarity (VS), and Hausdorff distance (HD) were used to evaluate the segmentation performance. Sensitivity, specificity, and area under the curve (AUC) were used to evaluate the detection performance at the patient level; recall, precision, and F1-score were assessed at the lesion level.ResultsThe pelvic bony structures segmentation on DWI and T1WI images had mean DSC and VS values above 0.85, and the HD values were &lt;15 mm. In the testing set, the AUC of the metastases detection at the patient level were 0.85 and 0.80 on DWI and T1WI images. At the lesion level, the F1-score achieved 87.6% and 87.8% concerning metastases detection on DWI and T1WI images, respectively. In the external dataset, the AUC of the model for M-staging was 0.94 and 0.89 on DWI and T1WI images.ConclusionThe deep learning-based 3D U-Net network yields accurate detection and segmentation of pelvic bone metastases for PCa patients on DWI and T1WI images, which lays a foundation for the whole-body skeletal metastases assessment.

A prospective study on inter-operator variability in semi-robotic software-based MRI/TRUS-fusion targeted prostate biopsies

Purpose Magnetic resonance imaging (MRI)/ultrasound-fusion prostate biopsy (FB) comprises multiple steps each of which can cause alterations in targeted biopsy (TB) accuracy leading to false-negative results. The aim was to assess the inter-operator variability of software-based fusion TB by targeting the same MRI-lesions by different urologists. Methods In this prospective study, 142 patients eligible for analysis underwent software-based FB. TB of all lesions (n = 172) were carried out by two different urologists per patient (n = 31 urologists). We analyzed the number of mismatches [overall prostate cancer (PCa), clinically significant PCa (csPCa) and non-significant PCa (nsPCa)] between both performed TB per patient. In addition we evaluated factors contributing to inter-operator variability by uni- and multivariable analyses. Results In 11.6% of all MRI-lesions (10.6% of all patients) there was a mismatch between TB1 and TB2 in terms of overall prostate cancer (PCa detection. Regarding csPCa, patient-based mismatch occurred in 14.8% (n = 21). Overall PCa and csPCa detection rate of TB1 and TB2 did not differ significantly on a per-patient and per-lesion level. Analyses revealed a smaller lesion size as predictive for mismatches (OR 9.19, 95% CI 2.02–41.83, p < 0.001). Conclusion Reproducibility and precision of targeting particularly small lesions is still limited although using software-based FB. Further improvements in image-fusion, segmentation, needle-guidance, and automatization are necessary.

Segmentation of Cerebral Small Vessel Diseases-White Matter Hyperintensities Based on a Deep Learning System

Objective: Reliable quantification of white matter hyperintensities (WHMs) resulting from cerebral small vessel diseases (CSVD) is essential for understanding their clinical impact. We aim to develop and clinically validate a deep learning system for automatic segmentation of CSVD-WMH from fluid-attenuated inversion recovery (FLAIR) imaging using large multicenter data.Method: A FLAIR imaging dataset of 1,156 patients diagnosed with CSVD associated WMH (median age, 54 years; 653 males) obtained between September 2018 and September 2019 from Beijing Tiantan Hospital was retrospectively analyzed in this study. Locations of CSVD-WMH on the FLAIR scans were manually marked by two experienced neurologists. Using the manually labeled data of 996 patients (development set), a U-shaped novel 2D convolutional neural network (CNN) architecture was trained for automatic segmentation of CSVD-WMH. The segmentation performance of the network was evaluated with per pixel and lesion level dice scores using an independent internal test set (n = 160) and a multi-center external test set (n = 90, three medical centers). The clinical suitability of the segmentation results, classified as acceptable, acceptable with minor revision, acceptable with major revision, and not acceptable, was analyzed by three independent neuroradiologists. The inter-neuroradiologists agreement rate was assessed by the Kendall-W test.Results: On the internal and external test sets, the proposed CNN architecture achieved per pixel and lesion level dice scores of 0.72 (external test set), and they were significantly better than the state-of-the-art deep learning architectures proposed for WMH segmentation. In the clinical evaluation, neuroradiologists observed the segmentation results for 95% of the patients were acceptable or acceptable with a minor revision.Conclusions: A deep learning system can be used for automated, objective, and clinically meaningful segmentation of CSVD-WMH with high accuracy.

Research of the biostability of organic bases of paints for wood

The biostability of organic film-formers of paints and varnishes intended for staining wood to the action of the fungus Aspergillus niger was studied. It was found that in Sabouraud's environment on days 7, 14 and 21 from the beginning of infection, the epoxy hardener is characterized by the minimum level of damage, respectively, 1, 1.6 and 2.4 points; alkyd film former has 2 points, and in subsequent time intervals 3.7 points; epoxy resin on day 7 is characterized by a lesion level of 1.7 points, on the following days of exposure – 4 points; pentaphthalic film former, respectively, 2.7, 3.7 and 4 points. According to the degree of resistance in the Sabouraud environment, organic film-formers of wood paints can be ranked as follows: epoxy (hardener)>alkyd>epoxy resin>pentaphthalic>organosilicon. It is shown that in the environment of Czapek on 7, 14 and 21 days from the beginning of infection, the minimum level of damage is characterized by an epoxy hardener, respectively, 2, 2.3 and 3 points; pentaphthalic film former, respectively, 2 and 3 points; alkyd film former, respectively, 2.4, 3.7 and 4 points; epoxy resin on day 7 is characterized by a lesion level of 3 points, on the following days of exposure – 4 points. According to the degree of resistance in the environment of Czapek, organic film-forming agents for wood paints can be ranked as follows: epoxy (hardener)>pentaphthalic>alkyd>epoxy resin>organosilicon. Organosilicon film-formers were most intensively affected by the fungus both 7 days after exposure and at a later time, reaching the maximum values of the lesions – 4 points. During the test period, no zones of mycelium growth inhibition were observed in the studied organic bases

Radiotherapy-Induced Digestive Injury: Diagnosis, Treatment and Mechanisms

Radiotherapy is one of the main therapeutic methods for treating cancer. The digestive system consists of the gastrointestinal tract and the accessory organs of digestion (the tongue, salivary glands, pancreas, liver and gallbladder). The digestive system is easily impaired during radiotherapy, especially in thoracic and abdominal radiotherapy. In this review, we introduce the physical classification, basic pathogenesis, clinical characteristics, predictive/diagnostic factors, and possible treatment targets of radiotherapy-induced digestive injury. Radiotherapy-induced digestive injury complies with the dose-volume effect and has a radiation-based organ correlation. Computed tomography (CT), MRI (magnetic resonance imaging), ultrasound (US) and endoscopy can help diagnose and evaluate the radiation-induced lesion level. The latest treatment approaches include improvement in radiotherapy (such as shielding, hydrogel spacers and dose distribution), stem cell transplantation and drug administration. Gut microbiota modulation may become a novel approach to relieving radiogenic gastrointestinal syndrome. Finally, we summarized the possible mechanisms involved in treatment, but they remain varied. Radionuclide-labeled targeting molecules (RLTMs) are promising for more precise radiotherapy. These advances contribute to our understanding of the assessment and treatment of radiation-induced digestive injury.

Evaluation of the Efficiency of Supinator Tendon Transfer to Wrist Extensor in Brachial Plexus Injuries at C7-T1, A Case Study Based on OpenSIM Modelling Approach

BackgroundThe incidence of brachial plexus injuries (BPI) is increasing due to improvement in transportation technology. Those with BPI have upper limb performance limitation depends on the type of injury. Various surgical treatments have been used in this group of the subjects to restore their performance. The aim of this study was to evaluate the efficiency of supinator transferred to wrist extensors in those with lesion level at C7-T1 based on OpenSim modelling approach.MethodThe motions of the upper limb during vertical reaching, transverse reaching and wrist motion of a normal subject were achieved by use of motion analysis system. The ranges of motion of the upper limb joints were evaluated by inverse kinematic. OpenSim software was used to determine the muscles forces during aforementioned tasks. Tendon of supinator was transferred to extensors in modified models of OpenSim. Forward dynamic approach was used to determine the range of motion in tendon transferred condition. ResultsThe range of wrist motion in normal condition (extensors intake) were 85, 103 and 140 degrees for the first task (transverse reaching), the second task (vertical reaching) and the third task (only flexion/extension of wrist), respectively. Although the force of supinator was significantly less than that of wrist extensors, the pattern of its force is the same as wrist extensors.