Quadriceps muscle contraction causes medial patellofemoral ligament elongation by intermeshed fibers of vastus medialis oblique muscle.

The first aim of this study was to compare the medial patellofemoral length between contracted and relaxed quadriceps muscle and second to assess the importance of the intermeshed vastus medialis oblique fibers. After a priori power analysis (α = 0.05, power [1-ß] = 0.95), 35 healthy males aged 18-30 were prospectively examined with a 3.0-T magnetic resonance imaging (MRI) scanner in 10-15° of knee flexion. Two axial MRI sequences (25 s each) were made with relaxed and contracted quadriceps. Two blinded, independent raters measured twice medial patellofemoral ligament length (curved line) and attachment-to-attachment length (straight line). Mean medial patellofemoral ligament length and attachment-to-attachment length with relaxed quadriceps was: 65.5 mm (SD = 3.7), 59.7 mm (SD = 3.6), and after contraction, it increased to 68.7 mm (SD = 5.3), 61.2 mm (SD = 4.7); p < 0.01 and <0.001, respectively. Intraclass correlation coefficients for intra- and inter-rater reliabilities ranged from 0.55 (moderate) to 0.97 (excellent). Mean medial patellofemoral ligament length elongation after quadriceps contraction was significantly greater (3.2 mm, SD = 3.9) than mean attachment-to-attachment length elongation (1.6 mm, SD = 2.8); p < 0.001. Contraction of quadriceps muscle causes elongation of the medial patellofemoral ligament to the extent greater than the elongation of distance between its attachments. This confirms that medial patellofemoral ligament elongation after quadriceps contraction results not only from movement of its patellar attachment but also directly from intermeshed vastus medialis oblique fibers pulling medial patellofemoral ligament in a different direction creating a bow-like construct in agreement with the "pull-and-guide mechanism" proposed in the literature.

Artificial neural network based prediction of the lung tissue involvement as an independent in-hospital mortality and mechanical ventilation risk factor in COVID-19.

INTRODUCTION: During COVID-19 pandemic, artificial neural network (ANN) systems have been providing aid for clinical decisions. However, to achieve optimal results, these models should link multiple clinical data points to simple models. This study aimed to model the in-hospital mortality and mechanical ventilation risk using a two step approach combining clinical variables and ANN-analyzed lung inflammation data. METHODS: A data set of 4317 COVID-19 hospitalized patients, including 266 patients requiring mechanical ventilation, was analyzed. Demographic and clinical data (including the length of hospital stay and mortality) and chest computed tomography (CT) data were collected. Lung involvement was analyzed using a trained ANN. The combined data were then analyzed using unadjusted and multivariate Cox proportional hazards models. RESULTS: Overall in-hospital mortality associated with ANN-assigned percentage of the lung involvement (hazard ratio [HR]: 5.72, 95% confidence interval [CI]: 4.4-7.43, p < 0.001 for the patients with >50% of lung tissue affected by COVID-19 pneumonia), age category (HR: 5.34, 95% CI: 3.32-8.59 for cases >80 years, p < 0.001), procalcitonin (HR: 2.1, 95% CI: 1.59-2.76, p < 0.001, C-reactive protein level (CRP) (HR: 2.11, 95% CI: 1.25-3.56, p = 0.004), glomerular filtration rate (eGFR) (HR: 1.82, 95% CI: 1.37-2.42, p < 0.001) and troponin (HR: 2.14, 95% CI: 1.69-2.72, p < 0.001). Furthermore, the risk of mechanical ventilation is also associated with ANN-based percentage of lung inflammation (HR: 13.2, 95% CI: 8.65-20.4, p < 0.001 for patients with >50% involvement), age, procalcitonin (HR: 1.91, 95% CI: 1.14-3.2, p = 0.14, eGFR (HR: 1.82, 95% CI: 1.2-2.74, p = 0.004) and clinical variables, including diabetes (HR: 2.5, 95% CI: 1.91-3.27, p < 0.001), cardiovascular and cerebrovascular disease (HR: 3.16, 95% CI: 2.38-4.2, p < 0.001) and chronic pulmonary disease (HR: 2.31, 95% CI: 1.44-3.7, p < 0.001). CONCLUSIONS: ANN-based lung tissue involvement is the strongest predictor of unfavorable outcomes in COVID-19 and represents a valuable support tool for clinical decisions.

Images of Extremely Rare Cantrell Phenomenon.

We present a case of a neonate born with prenatal diagnosis of Cantrell syndrome and ectopia cordis. This extremely rare congenital disorder underscores the significant need for multimodality imaging to plan further management. The aim of the study was to present the thoracoabdominal syndrome using a three-dimensional computed tomography angiography. The CT scans confirmed complex intracardiac defects consisting of tetralogy of Fallot, total anomalous pulmonary venous return and persistent left superior vena cava. In conclusion, Cantrell syndrome necessitates a multidisciplinary approach, from the onset of the prenatal diagnosis followed by prompt medical imaging and surgical interventions after birth. The thoracoabdominal wall defect including complete ectopia cordis is an extremely rare disorder with a fatal outcome.

Differences in Brain Atrophy Pattern between People with Multiple Sclerosis and Systemic Diseases with Central Nervous System Involvement Based on Two-Dimensional Linear Measures.

Conventional brain magnetic resonance imaging (MRI) in systemic diseases with central nervous system involvement (SDCNS) may imitate MRI findings of multiple sclerosis (MS). In order to better describe the MRI characteristics of these conditions, in our study we assessed brain volume parameters in MS (n = 58) and SDCNS (n = 41) patients using two-dimensional linear measurements (2DLMs): bicaudate ratio (BCR), corpus callosum index (CCI) and width of third ventricle (W3V). In SDCNS patients, all 2DLMs were affected by age (CCI p = 0.005, BCR p < 0.001, W3V p < 0.001, respectively), whereas in MS patients only BCR and W3V were (p = 0.001 and p = 0.015, respectively). Contrary to SDCNS, in the MS cohort BCR and W3V were associated with T1 lesion volume (T1LV) (p = 0.020, p = 0.009, respectively) and T2 lesion volume (T2LV) (p = 0.015, p = 0.009, respectively). CCI was associated with T1LV in the MS cohort only (p = 0.015). Moreover, BCR was significantly higher in the SDCNS group (p = 0.01) and CCI was significantly lower in MS patients (p = 0.01). The best predictive model to distinguish MS and SDCNS encompassed gender, BCR and T2LV as the explanatory variables (sensitivity 0.91; specificity 0.68; AUC 0.86). Implementation of 2DLMs in the brain MRI analysis of MS and SDCNS patients allowed for the identification of diverse patterns of local brain atrophy in these clinical conditions.

Automated volumetric evaluation of intracranial compartments and cerebrospinal fluid distribution on emergency trauma head CT scans to quantify mass effect.

Background: Intracranial space is divided into three compartments by the falx cerebri and tentorium cerebelli. We assessed whether cerebrospinal fluid (CSF) distribution evaluated by a specifically developed deep-learning neural network (DLNN) could assist in quantifying mass effect. Methods: Head trauma CT scans from a high-volume emergency department between 2018 and 2020 were retrospectively analyzed. Manual segmentations of intracranial compartments and CSF served as the ground truth to develop a DLNN model to automate the segmentation process. Dice Similarity Coefficient (DSC) was used to evaluate the segmentation performance. Supratentorial CSF Ratio was calculated by dividing the volume of CSF on the side with reduced CSF reserve by the volume of CSF on the opposite side. Results: Two hundred and seventy-four patients (mean age, 61 years ± 18.6) after traumatic brain injury (TBI) who had an emergency head CT scan were included. The average DSC for training and validation datasets were respectively: 0.782 and 0.765. Lower DSC were observed in the segmentation of CSF, respectively 0.589, 0.615, and 0.572 for the right supratentorial, left supratentorial, and infratentorial CSF regions in the training dataset, and slightly lower values in the validation dataset, respectively 0.567, 0.574, and 0.556. Twenty-two patients (8%) had midline shift exceeding 5 mm, and 24 (8.8%) presented with high/mixed density lesion exceeding >25 ml. Fifty-five patients (20.1%) exhibited mass effect requiring neurosurgical treatment. They had lower supratentorial CSF volume and lower Supratentorial CSF Ratio (both p < 0.001). A Supratentorial CSF Ratio below 60% had a sensitivity of 74.5% and specificity of 87.7% (AUC 0.88, 95%CI 0.82-0.94) in identifying patients that require neurosurgical treatment for mass effect. On the other hand, patients with CSF constituting 10-20% of the intracranial space, with 80-90% of CSF specifically in the supratentorial compartment, and whose Supratentorial CSF Ratio exceeded 80% had minimal risk. Conclusion: CSF distribution may be presented as quantifiable ratios that help to predict surgery in patients after TBI. Automated segmentation of intracranial compartments using the DLNN model demonstrates a potential of artificial intelligence in quantifying mass effect. Further validation of the described method is necessary to confirm its efficacy in triaging patients and identifying those who require neurosurgical treatment.

Let's Play the fMRI-Advantages of Gamified Paradigm in Examining the Motor Cortex of Young Children.

Background: Performing functional magnetic resonance imaging (fMRI) examination is difficult when a child needs to stay awake and cooperate. Many techniques help to prepare them for the study but without modification of the examination protocol. The objective of this research was to prepare a gamified motor paradigm ("computer game") that will improve the fMRI examination of young children. Methods: After preparing a dedicated application the fMRI examination was performed on 60 healthy children (10 girls and 10 boys in each age group of 4, 5, and 6 years old). Each child performed the gamified and a standard motor paradigm, both based on squeezing a rubber bulb. The effectiveness of squeezing were compared. Results: With the application of the gamified paradigm children completed significantly more active blocks (3.3 ± 1.4) than for the standard paradigm (2.2 ± 1.6) (p < 0.0001). In mixed-effects Poisson regression, age (IRR = 1.9; 95%CI: 1.5−2.5) and application of gamified paradigm (IRR = 5.6; 95%CI: 1.1−28.0) were significantly associated with more completed blocks. Conclusions: The gamified motor paradigm performed better than a standard paradigm in the fMRI examination of children between 4 and 6 years old. It allowed a significant increase in the number of completed active blocks and also better squeezing effectiveness in each block.

Nutrition Trends in Patients Over the Long Term After Kidney Transplantation.

OBJECTIVES: Nutritional behaviors may exert important influence on morbidity and graft function in patients after kidney transplantation (KT). Nutritional status is closely related to potential risk factors of developing posttransplant complications, including diabetes mellitus, weight gain, and negative effects on immunosuppressive therapy. The aim of this study was to assess the dietary intake in patients after KT. DESIGN AND METHODS: Nutritional intake of 154 (61 women and 93 men) patients was assessed based on a questionnaire regarding food intake (proteins, fats, carbohydrates, cholesterol, sugar, phosphorus, calorific value) within 3 working days preceding the routine outpatient posttransplant visit. Patient medical history, concomitant medications, and estimated glomerular filtration rate (eGFR) was obtained from medical charts. RESULTS: The mean age (years) ± SD of patients was 51.9 ± 14.1. The patients were evaluated 94 ± 67 months after KT, with a median eGFR of 53 (range, 41.2-64.1) mL/min/1.73 m2. Sixty-two percent of patients had increased body mass index values. The mean total energy intake was 2159.4 ± 551.9 kcal/day. The patients reported elevated salt (8.5 ± 2.4 g per day) and fat intake (99.4 ± 3.2 g per day) including 57% saturated fatty acids. The patients consumed products containing high amounts of sugars (108.2 ± 107.0 g per day), carbohydrates (238.3 ± 64.3 g per day), and cholesterol (303.6 ± 11.1 mg per day). The diet among kidney recipients consisted predominantly of fats, meat, cured meat, and sweets. CONCLUSIONS: The nutritional behaviors of patients after KT are in most cases poor. Improvement of eating habits in these patients seems to be a simple method to preserve kidney function over the long term.