Pneumothorax risk reduction during CT-guided lung biopsy - Effect of fluid application to the pleura before lung puncture and the gravitational effect of pleural pressure.

PURPOSE: This study investigated strategies to reduce pneumothorax risk in CT-guided lung biopsy. The approach involved administering 10 ml of 1 % lidocaine fluid in the subpleural or pleural space before lung puncture and utilizing the gravitational effect of pleural pressure with specific patient positioning. METHOD: We retrospectively analyzed 72 percutaneous CT-guided lung biopsies performed at a single center between January 2020 and April 2023. These were grouped based on fluid administration during the biopsy and whether the biopsies were conducted in dependent or non-dependent lung regions. Confounding factors like patient demographics, lesion characteristics, and procedural details were assessed. Patient characteristics and the occurrence of pneumothoraces were compared using a Kurskal-Wallis test for continuous variables and a Fisher's exact test for categorical variables. Multivariable logistic regression was used to identify potential confounders. RESULTS: Subpleural or pleural fluid administration and performing biopsies in dependent lung areas were significantly linked to lower peri-interventional pneumothorax incidence (n = 15; 65 % without fluid in non-dependent areas, n = 5; 42 % without fluid in dependent areas, n = 5; 36 % with fluid in non-dependent areas,n = 0; 0 % with fluid in dependent areas; p = .001). Even after adjusting for various factors, biopsy in dependent areas and fluid administration remained independently associated with reduced pneumothorax risk (OR 0.071, p<=.01 for lesions with fluid administration; OR 0.077, p = .016 for lesions in dependent areas). CONCLUSIONS: Pre-puncture fluid administration to the pleura and consideration of gravitational effects during patient positioning can effectively decrease pneumothorax occurrences in CT-guided lung biopsy.

MRI Extracellular Volume Fraction in Liver Fibrosis-A Comparison of Different Time Points and Blood Pool Measurements.

BACKGROUND: Extracellular volume (ECV) correlates with the degree of liver fibrosis. PURPOSE: To analyze the performance of liver MRI-based ECV evaluations with different blood pool measurements at different time points. STUDY TYPE: Prospective. SAMPLE: 73 consecutive patients (n = 31 females, mean age 56 years) with histopathology-proven liver fibrosis. FIELD STRENGTH/SEQUENCE: 3T acquisition within 90 days of biopsy, including shortened modified look-locker inversion recovery T1 mapping. ASSESSMENT: Polygonal regions of interest were manually drawn in the liver, aorta, vena cava, and in the main, left and right portal vein on four slices before and after Gd-DOTA administration at 5/10/15 minutes. ECV was calculated 1) on one single slice on portal bifurcation level, and 2) averaged over all four slices. STATISTICAL TESTS: Parameters were compared between patients with fibrosis grades F0-2 and F3-F4 with the Mann-Whitney U and fishers exact test. ROC analysis was used to assess the performance of the parameters to predict F3-4 fibrosis. A P-value <0.05 was considered statistically significant. RESULTS: ECV was significantly higher in F3-4 fibrosis (35.4% [33.1%-37.6%], 36.1% [34.2%-37.5%], and 37.0% [34.8%-39.2%] at 5/10/15 minutes) than in patients with F0-2 fibrosis (33.3% [30.8%-34.8%], 33.7% [31.6%-34.7%] and 34.9% [32.2%-36.0%]; AUC = 0.72-0.75). Blood pool T1 relaxation times in the aorta and vena cava were longer on the upper vs. lower slices at 5 minutes, but not at 10/15 minutes. AUC values were similar when measured on a single slice (AUC = 0.69-0.72) or based on blood pool measurements in the cava or portal vein (AUC = 0.63-0.67 and AUC = 0.65-0.70). DATA CONCLUSION: Liver ECV is significantly higher in F3-4 fibrosis compared to F0-2 fibrosis with blood pool measurements performed in the aorta, inferior vena cava, and portal vein at 5, 10, and 15 minutes. However, a smaller variability was observed for blood pool measurements between slices at 15 minutes. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

Erectile dysfunction: role of computed tomography cavernosography in the diagnosis and treatment planning of venous leak.

BACKGROUND: Venous leak appears to be the most common cause of vasculogenic erectile dysfunction (ED), which can be treated with venous embolization. Traditionally, conventional cavernosography was used for the diagnosis and treatment planning of venous leak. Recently, computed tomography (CT) cavernosography was introduced as a novel cross-sectional imaging method proposed to be advantageous over conventional cavernosography. We created a novel management algorithm for diagnosing venous leak including CT cavernosography as an imaging modality. In order to provide a broader basis for our management algorithm, a systematic literature review was conducted. MAIN BODY: In this article we systematically review relevant literature on using CT cavernosography for the diagnosis and treatment planning in ED patients with venous leak following the PRISMA selection process. Nine full-text articles were included in the review and assigned a level of evidence grade (all grade II). Two studies (2/9) compared the results of conventional cavernosography with those of CT cavernosography which was superior for site-specific venous leak identification (19.4% vs. 100%, respectively). CT cavernosography is a more detailed imaging method that is faster to perform, exposes the patient to less radiation, and requires less contrast material. In one study (1/9), CT cavernosography was used for diagnostic purposes only. Eight studies (8/9) cover both, diagnostic imaging and treatment planning including embolization (1/9) and sclerotherapy (2/9) of venous leak in patients with venogenic ED. Three studies (3/9) describe anatomical venous leak classifications that were established based on CT cavernosography findings for accurate mapping of superficial and/or deep venous leak and identification of mixed or more complex forms of venous leak present in up to 84% of patients. In addition to treatment planning, one study (1/9) used CT cavernosography also for follow-up imaging post treatment. CONCLUSION: CT cavernosography is superior to conventional cavernosography for diagnosis and treatment planning in patients with ED caused by venous leak (grade II levels of evidence). Consequently, CT cavernosography should be included in management algorithms for ED patients with suspected venous leak.

Influence of CT dose reduction on AI-driven malignancy estimation of incidental pulmonary nodules.

OBJECTIVES: The purpose of this study was to determine the influence of dose reduction on a commercially available lung cancer prediction convolutional neuronal network (LCP-CNN). METHODS: CT scans from a cohort provided by the local lung cancer center (n = 218) with confirmed pulmonary malignancies and their corresponding reduced dose simulations (25% and 5% dose) were subjected to the LCP-CNN. The resulting LCP scores (scale 1-10, increasing malignancy risk) and the proportion of correctly classified nodules were compared. The cohort was divided into a low-, medium-, and high-risk group based on the respective LCP scores; shifts between the groups were studied to evaluate the potential impact on nodule management. Two different malignancy risk score thresholds were analyzed: a higher threshold of ≥ 9 ("rule-in" approach) and a lower threshold of > 4 ("rule-out" approach). RESULTS: In total, 169 patients with 196 nodules could be included (mean age ± SD, 64.5 ± 9.2 year; 49% females). Mean LCP scores for original, 25% and 5% dose levels were 8.5 ± 1.7, 8.4 ± 1.7 (p > 0.05 vs. original dose) and 8.2 ± 1.9 (p < 0.05 vs. original dose), respectively. The proportion of correctly classified nodules with the "rule-in" approach decreased with simulated dose reduction from 58.2 to 56.1% (p = 0.34) and to 52.0% for the respective dose levels (p = 0.01). For the "rule-out" approach the respective values were 95.9%, 96.4%, and 94.4% (p = 0.12). When reducing the original dose to 25%/5%, eight/twenty-two nodules shifted to a lower, five/seven nodules to a higher malignancy risk group. CONCLUSION: CT dose reduction may affect the analyzed LCP-CNN regarding the classification of pulmonary malignancies and potentially alter pulmonary nodule management. CLINICAL RELEVANCE STATEMENT: Utilization of a "rule-out" approach with a lower malignancy risk threshold prevents underestimation of the nodule malignancy risk for the analyzed software, especially in high-risk cohorts. KEY POINTS: • LCP-CNN may be affected by CT image parameters such as noise resulting from low-dose CT acquisitions. • CT dose reduction can alter pulmonary nodule management recommendations by affecting the outcome of the LCP-CNN. • Utilization of a lower malignancy risk threshold prevents underestimation of pulmonary malignancies in high-risk cohorts.

Automated liver segmental volume ratio quantification on non-contrast T1-Vibe Dixon liver MRI using deep learning.

PURPOSE: To evaluate the effectiveness of automated liver segmental volume quantification and calculation of the liver segmental volume ratio (LSVR) on a non-contrast T1-vibe Dixon liver MRI sequence using a deep learning segmentation pipeline. METHOD: A dataset of 200 liver MRI with a non-contrast 3 mm T1-vibe Dixon sequence was manually labeledslice-by-sliceby an expert for Couinaud liver segments, while portal and hepatic veins were labeled separately. A convolutional neural networkwas trainedusing 170 liver MRI for training and 30 for evaluation. Liver segmental volumes without liver vessels were retrieved and LSVR was calculated as the liver segmental volumes I-III divided by the liver segmental volumes IV-VIII. LSVR was compared with the expert manual LSVR calculation and the LSVR calculated on CT scans in 30 patients with CT and MRI within 6 months. RESULTS: Theconvolutional neural networkclassified the Couinaud segments I-VIII with an average Dice score of 0.770 ± 0.03, ranging between 0.726 ± 0.13 (segment IVb) and 0.810 ± 0.09 (segment V). The calculated mean LSVR with liver MRI unseen by the model was 0.32 ± 0.14, as compared with manually quantified LSVR of 0.33 ± 0.15, resulting in a mean absolute error (MAE) of 0.02. A comparable LSVR of 0.35 ± 0.14 with a MAE of 0.04 resulted with the LSRV retrieved from the CT scans. The automated LSVR showed significant correlation with the manual MRI LSVR (Spearman r = 0.97, p < 0.001) and CT LSVR (Spearman r = 0.95, p < 0.001). CONCLUSIONS: A convolutional neural network allowed for accurate automated liver segmental volume quantification and calculation of LSVR based on a non-contrast T1-vibe Dixon sequence.

Artificial intelligence for reducing the radiation burden of medical imaging for the diagnosis of coronavirus disease.

Medical imaging has been intensively employed in screening, diagnosis and monitoring during the COVID-19 pandemic. With the improvement of RT-PCR and rapid inspection technologies, the diagnostic references have shifted. Current recommendations tend to limit the application of medical imaging in the acute setting. Nevertheless, efficient and complementary values of medical imaging have been recognized at the beginning of the pandemic when facing unknown infectious diseases and a lack of sufficient diagnostic tools. Optimizing medical imaging for pandemics may still have encouraging implications for future public health, especially for long-lasting post-COVID-19 syndrome theranostics. A critical concern for the application of medical imaging is the increased radiation burden, particularly when medical imaging is used for screening and rapid containment purposes. Emerging artificial intelligence (AI) technology provides the opportunity to reduce the radiation burden while maintaining diagnostic quality. This review summarizes the current AI research on dose reduction for medical imaging, and the retrospective identification of their potential in COVID-19 may still have positive implications for future public health.

Artificial Intelligence and Interstitial Lung Disease: Diagnosis and Prognosis.

ABSTRACT: Interstitial lung disease (ILD) is now diagnosed by an ILD-board consisting of radiologists, pulmonologists, and pathologists. They discuss the combination of computed tomography (CT) images, pulmonary function tests, demographic information, and histology and then agree on one of the 200 ILD diagnoses. Recent approaches employ computer-aided diagnostic tools to improve detection of disease, monitoring, and accurate prognostication. Methods based on artificial intelligence (AI) may be used in computational medicine, especially in image-based specialties such as radiology. This review summarises and highlights the strengths and weaknesses of the latest and most significant published methods that could lead to a holistic system for ILD diagnosis. We explore current AI methods and the data use to predict the prognosis and progression of ILDs. It is then essential to highlight the data that holds the most information related to risk factors for progression, e.g., CT scans and pulmonary function tests. This review aims to identify potential gaps, highlight areas that require further research, and identify the methods that could be combined to yield more promising results in future studies.

Hydrochlorothiazide and Prevention of Kidney-Stone Recurrence.

BACKGROUND: Nephrolithiasis is one of the most common conditions affecting the kidney and is characterized by a high risk of recurrence. Thiazide diuretic agents are widely used for prevention of the recurrence of kidney stones, but data regarding the efficacy of such agents as compared with placebo are limited. Furthermore, dose-response data are also limited. METHODS: In this double-blind trial, we randomly assigned patients with recurrent calcium-containing kidney stones to receive hydrochlorothiazide at a dose of 12.5 mg, 25 mg, or 50 mg once daily or placebo once daily. The main objective was to investigate the dose-response effect for the primary end point, a composite of symptomatic or radiologic recurrence of kidney stones. Radiologic recurrence was defined as the appearance of new stones on imaging or the enlargement of preexisting stones that had been observed on the baseline image. Safety was also assessed. RESULTS: In all, 416 patients underwent randomization and were followed for a median of 2.9 years. A primary end-point event occurred in 60 of 102 patients (59%) in the placebo group, in 62 of 105 patients (59%) in the 12.5-mg hydrochlorothiazide group (rate ratio vs. placebo, 1.33; 95% confidence interval [CI], 0.92 to 1.93), in 61 of 108 patients (56%) in the 25-mg group (rate ratio, 1.24; 95% CI, 0.86 to 1.79), and in 49 of 101 patients (49%) in the 50-mg group (rate ratio, 0.92; 95% CI, 0.63 to 1.36). There was no relation between the hydrochlorothiazide dose and the occurrence of a primary end-point event (P = 0.66). Hypokalemia, gout, new-onset diabetes mellitus, skin allergy, and a plasma creatinine level exceeding 150% of the baseline level were more common among patients who received hydrochlorothiazide than among those who received placebo. CONCLUSIONS: Among patients with recurrent kidney stones, the incidence of recurrence did not appear to differ substantially among patients receiving hydrochlorothiazide once daily at a dose of 12.5 mg, 25 mg, or 50 mg or placebo once daily. (Funded by the Swiss National Science Foundation and Inselspital; NOSTONE ClinicalTrials.gov number, NCT03057431.).

"Will I change nodule management recommendations if I change my CAD system?"-impact of volumetric deviation between different CAD systems on lesion management.

OBJECTIVES: To evaluate and compare the measurement accuracy of two different computer-aided diagnosis (CAD) systems regarding artificial pulmonary nodules and assess the clinical impact of volumetric inaccuracies in a phantom study. METHODS: In this phantom study, 59 different phantom arrangements with 326 artificial nodules (178 solid, 148 ground-glass) were scanned at 80 kV, 100 kV, and 120 kV. Four different nodule diameters were used: 5 mm, 8 mm, 10 mm, and 12 mm. Scans were analyzed by a deep-learning (DL)-based CAD and a standard CAD system. Relative volumetric errors (RVE) of each system vs. ground truth and the relative volume difference (RVD) DL-based vs. standard CAD were calculated. The Bland-Altman method was used to define the limits of agreement (LOA). The hypothetical impact on LungRADS classification was assessed for both systems. RESULTS: There was no difference between the three voltage groups regarding nodule volumetry. Regarding the solid nodules, the RVE of the 5-mm-, 8-mm-, 10-mm-, and 12-mm-size groups for the DL CAD/standard CAD were 12.2/2.8%, 1.3/ - 2.8%, - 3.6/1.5%, and - 12.2/ - 0.3%, respectively. The corresponding values for the ground-glass nodules (GGN) were 25.6%/81.0%, 9.0%/28.0%, 7.6/20.6%, and 6.8/21.2%. The mean RVD for solid nodules/GGN was 1.3/ - 15.2%. Regarding the LungRADS classification, 88.5% and 79.8% of all solid nodules were correctly assigned by the DL CAD and the standard CAD, respectively. 14.9% of the nodules were assigned differently between the systems. CONCLUSIONS: Patient management may be affected by the volumetric inaccuracy of the CAD systems and hence demands supervision and/or manual correction by a radiologist. KEY POINTS: • The DL-based CAD system was more accurate in the volumetry of GGN and less accurate regarding solid nodules than the standard CAD system. • Nodule size and attenuation have an effect on the measurement accuracy of both systems; tube voltage has no effect on measurement accuracy. • Measurement inaccuracies of CAD systems can have an impact on patient management, which demands supervision by radiologists.

Myocardial scar detection in free-breathing Dixon-based fat- and water-separated 3D inversion recovery late-gadolinium enhancement whole heart MRI.

The aim of this study was to investigate the diagnostic accuracy and reader confidence for late-gadolinium enhancement (LGE) detection of a novel free-breathing, image-based navigated 3D whole-heart LGE sequence with fat-water separation, compared to a free-breathing motion-corrected 2D LGE sequence in patients with ischemic and non-ischemic cardiomyopathy. Cardiac MRI patients including the respective sequences were retrospectively included. Two independent, blinded readers rated image quality, depiction of segmental LGE and documented acquisition time, SNR, CNR and amount of LGE. Results were compared using the Friedman or the Kruskal-Wallis test. For LGE rating, a jackknife free-response receiver operating characteristic analysis was performed with a figure of merit (FOM) calculation. Forty-two patients were included, thirty-two were examined with a 1.5 T-scanner and ten patients with a 3 T-scanner. The mean acquisition time of the 2D sequence was significantly shorter compared to the 3D sequence (07:12 min vs. 09:24 min; p < 0.001). The 3D scan time was significantly shorter when performed at 3 T compared to 1.5 T (07:47 min vs. 09:50 min; p < 0.001). There were no differences regarding SNR, CNR or amount of LGE. 3D imaging had a significantly higher FOM (0.89 vs. 0.78; p < 0.001). Overall image quality ratings were similar, but 3D sequence ratings were higher for fine anatomical structures. Free-breathing motion-corrected 3D LGE with high isotropic resolution results in enhanced LGE-detection with higher confidence and better delineation of fine structures. The acquisition time for 3D imaging was longer, but may be reduced by performing on a 3 T-scanner.

Quantitative CT analysis of lung parenchyma to improve malignancy risk estimation in incidental pulmonary nodules.

OBJECTIVES: To assess the value of quantitative computed tomography (QCT) of the whole lung and nodule-bearing lobe regarding pulmonary nodule malignancy risk estimation. METHODS: A total of 251 subjects (median [IQR] age, 65 (57-73) years; 37% females) with pulmonary nodules on non-enhanced thin-section CT were retrospectively included. Twenty percent of the nodules were malignant, the remainder benign either histologically or at least 1-year follow-up. CT scans were subjected to in-house software, computing parameters such as mean lung density (MLD) or peripheral emphysema index (pEI). QCT variable selection was performed using logistic regression; selected variables were integrated into the Mayo Clinic and the parsimonious Brock Model. RESULTS: Whole-lung analysis revealed differences between benign vs. malignant nodule groups in several parameters, e.g. the MLD (-766 vs. -790 HU) or the pEI (40.1 vs. 44.7 %). The proposed QCT model had an area-under-the-curve (AUC) of 0.69 (95%-CI, 0.62-0.76) based on all available data. After integrating MLD and pEI into the Mayo Clinic and Brock Model, the AUC of both clinical models improved (AUC, 0.91 to 0.93 and 0.88 to 0.91, respectively). The lobe-specific analysis revealed that the nodule-bearing lobes had less emphysema than the rest of the lung regarding benign (EI, 0.5 vs. 0.7 %; p < 0.001) and malignant nodules (EI, 1.2 vs. 1.7 %; p = 0.001). CONCLUSIONS: Nodules in subjects with higher whole-lung metrics of emphysema and less fibrosis are more likely to be malignant; hereby the nodule-bearing lobes have less emphysema. QCT variables could improve the risk assessment of incidental pulmonary nodules. KEY POINTS: • Nodules in subjects with higher whole-lung metrics of emphysema and less fibrosis are more likely to be malignant. • The nodule-bearing lobes have less emphysema compared to the rest of the lung. • QCT variables could improve the risk assessment of incidental pulmonary nodules.

Pulmonary Recovery 12 Months after Non-Severe and Severe COVID-19: The Prospective Swiss COVID-19 Lung Study.

BACKGROUND: Lung function impairment persists in some patients for months after acute coronavirus disease 2019 (COVID-19). Long-term lung function, radiological features, and their association remain to be clarified. OBJECTIVES: We aimed to prospectively investigate lung function and radiological abnormalities over 12 months after severe and non-severe COVID-19. METHODS: 584 patients were included in the Swiss COVID-19 lung study. We assessed lung function at 3, 6, and 12 months after acute COVID-19 and compared chest computed tomography (CT) imaging to lung functional abnormalities. RESULTS: At 12 months, diffusion capacity for carbon monoxide (DLCOcorr) was lower after severe COVID-19 compared to non-severe COVID-19 (74.9% vs. 85.2% predicted, p < 0.001). Similarly, minimal oxygen saturation on 6-min walk test and total lung capacity were lower after severe COVID-19 (89.6% vs. 92.2%, p = 0.004, respectively, 88.2% vs. 95.1% predicted, p = 0.011). The difference for forced vital capacity (91.6% vs. 96.3% predicted, p = 0.082) was not statistically significant. Between 3 and 12 months, lung function improved in both groups and differences in DLCO between non-severe and severe COVID-19 patients decreased. In patients with chest CT scans at 12 months, we observed a correlation between radiological abnormalities and reduced lung function. While the overall extent of radiological abnormalities diminished over time, the frequency of mosaic attenuation and curvilinear patterns increased. CONCLUSIONS: In this prospective cohort study, patients who had severe COVID-19 had diminished lung function over the first year compared to those after non-severe COVID-19, albeit with a greater extent of recovery in the severe disease group.

Influence of Lung Reconstruction Algorithms on Interstitial Lung Pattern Recognition on CT.

Despite current recommendations, there is no recent scientific study comparing the influence of CT reconstruction kernels on lung pattern recognition in interstitial lung disease (ILD).To evaluate the sensitivity of lung (i70) and soft (i30) CT kernel algorithms for the diagnosis of ILD patterns.We retrospectively extracted between 15-25 pattern annotations per case (1 annotation = 15 slices of 1 mm) from 23 subjects resulting in 408 annotation stacks per lung kernel and soft kernel reconstructions. Two subspecialized chest radiologists defined the ground truth in consensus. 4 residents, 2 fellows, and 2 general consultants in radiology with 3 to 13 years of experience in chest imaging performed a blinded readout. In order to account for data clustering, a generalized linear mixed model (GLMM) with random intercept for reader and nested for patient and image and a kernel/experience interaction term was used to analyze the results.The results of the GLMM indicated, that the odds of correct pattern recognition is 12 % lower with lung kernel compared to soft kernel; however, this was not statistically significant (OR 0.88; 95%-CI, 0.73-1.06; p = 0.187). Furthermore, the consultants' odds of correct pattern recognition was 78 % higher than the residents' odds, although this finding did not reach statistical significance either (OR 1.78; 95%-CI, 0.62-5.06; p = 0.283). There was no significant interaction between the two fixed terms kernel and experience. Intra-rater agreement between lung and soft kernel was substantial (κ = 0.63 ±â€Š0.19). The mean inter-rater agreement for lung/soft kernel was κ = 0.37 ±â€Š0.17/κ = 0.38 ±â€Š0.17.There is no significant difference between lung and soft kernel reconstructed CT images for the correct pattern recognition in ILD. There are non-significant trends indicating that the use of soft kernels and a higher level of experience lead to a higher probability of correct pattern identification. · There is no significant difference between lung and soft kernel reconstructed CT images for the correct pattern recognition in interstitial lung disease.. · There are even non-significant tendencies that the use of soft kernels lead to a higher probability of correct pattern identification.. · These results challenge the current recommendations and the routinely performed separate lung kernel reconstructions for lung parenchyma analysis.. CITATION FORMAT: · Klaus JB, Christodoulidis S, Peters AA et al. Influence of Lung Reconstruction Algorithms on Interstitial Lung Pattern Recognition on CT. Fortschr Röntgenstr 2023; 195: 47 - 54.

The Impact of Blood Morphological Parameters on Treatment Outcomes in Tennis Elbow Patients Receiving Platelet-Rich Plasma (PRP) Therapy: A Prospective Study.

Platelet-rich plasma (PRP) therapy holds substantial promise for the treatment of tennis elbow, a complex and challenging musculoskeletal condition. The aim of the study was to assess whether there are correlations between the levels of individual morphotic elements determined in whole blood and the outcomes of tennis elbow treatment with PRP injection, as measured using patient-reported outcome measures (PROMs) such as the Visual Analog Scale (VAS), Quick Disabilities of the Arm, Shoulder, and Hand (QDASH), and Patient-Rated Tennis Elbow Evaluation (PRTEE). A prospective analysis was conducted on 107 patients (132 elbows) undergoing lateral epicondylitis treatment with (PRP) injections. Patients completed VAS, PRTEE, and QDASH questionnaires on the day of PRP administration and at established checkpoints (2, 4, 8, 12, 24, 52, and 104 weeks). Minimal clinically important difference (MCID) was employed to assess the treatment effects. Then, correlations were measured within each PROM, and the impact of the concentration of individual blood parameters on the MCID outcomes was assessed. Analyzing the relationships between the MCID+ and MCID- groups, significant correlations for the VAS and QDASH scales were observed. The level of individual morphotic elements in the blood may have influenced the treatment outcome, as measured using specific patient-reported outcome measures (PROMs). Regarding the VAS scale, factors favoring a positive treatment outcome included higher values of eosinophils (EOS) and basophils (BASO). For the QDASH scale, these factors were a lower value of mean corpuscular volume (MCV) and a higher mean corpuscular hemoglobin (MCH). The levels of certain blood parameters, such as EOS and BASO, in the current study influenced the classification of patients into MCID+ or MCID- groups, based on the VAS and QDASH scales.

Correlation of Patellofemoral Chondromalacia and Body Mass Index (BMI) in Relation to Sex and Age Analysis of 1.5T and 3.0T Magnetic Resonance (MR) Images Using the Outerbridge Scale.

BACKGROUND Cartilage disease (chondromalacia) is most commonly found in the patellofemoral joint. Non-invasive magnetic resonance imaging methods are used to assess the severity of chondromalacia. The available literature lacks papers describing the predilection of chondromalacia changes to BMI assessed on the basis of geometric data that can be assessed by 1.5T and 3.0T MRI. The aim of this study was to assess the relationship between the severity of chondromalacia of the patellofemoral joint and age, sex, and BMI assessed on the 1.5T and 3.0T MRI scanners. MATERIAL AND METHODS The study involved 324 patients, including 159 (49%) women and 165 (51%) men, aged 8-87 years (mean age: 45.1±20.9). The studied group had a BMI in the range of 14.3-47.3 (M: 27.7±5.02). A 1.5T and 3.0T MRI scanner were used in the study. To assess the cartilage of the patellofemoral joint, Outerbridge scales were used. RESULTS The age of the patients showed a significant correlation (Spearman's rank, P<0.0001) with Outterbridge grade for each surface of patellofemoral joint. Higher correlation between BMI and Outerbridge grade was noted in the patella (rho=0.4139) than in the femur (rho=0.2890). There were no significant differences between women and men in the Outerbridge assessment of the knee joint (P>0.05).  Significant more degeneration was found at the 1.5T scanner compared to the 3.0T MRI (P<0.0025). CONCLUSIONS The severity of chondromalacia significantly depends on age and BMI level. There is a stronger correlation between the degree of chondromalacia and BMI in women than in men.

Convolutional neural network for automated segmentation of the liver and its vessels on non-contrast T1 vibe Dixon acquisitions.

We evaluated the effectiveness of automated segmentation of the liver and its vessels with a convolutional neural network on non-contrast T1 vibe Dixon acquisitions. A dataset of non-contrast T1 vibe Dixon liver magnetic resonance images was labelled slice-by-slice for the outer liver border, portal, and hepatic veins by an expert. A 3D U-Net convolutional neural network was trained with different combinations of Dixon in-phase, opposed-phase, water, and fat reconstructions. The neural network trained with the single-modal in-phase reconstructions achieved a high performance for liver parenchyma (Dice 0.936 ± 0.02), portal veins (0.634 ± 0.09), and hepatic veins (0.532 ± 0.12) segmentation. No benefit of using multi-modal input was observed (p = 1.0 for all experiments), combining in-phase, opposed-phase, fat, and water reconstruction. Accuracy for differentiation between portal and hepatic veins was 99% for portal veins and 97% for hepatic veins in the central region and slightly lower in the peripheral region (91% for portal veins, 80% for hepatic veins). In conclusion, deep learning-based automated segmentation of the liver and its vessels on non-contrast T1 vibe Dixon was highly effective. The single-modal in-phase input achieved the best performance in segmentation and differentiation between portal and hepatic veins.

Relationship between Outerbridge Scale and Chondropathy Femorotibial Joint in Relation to Gender and Age-The Use of 1.5T and 3.0T MRI Scanners.

Background and Objective: Magnetic resonance imaging (MRI) enables the effective evaluation of chondromalacia of the knee joint. Cartilage disease is affected by many factors, including gender, age, and body mass index (BMI). The aim of this study was to check the relationship between the severity of chondromalacia of the femoro-tibial joint and age, gender, and BMI assessed with 1.5T and 3.0T MRI scanners. Materials and Methods: The cross-observational study included 324 patients­159 (49%) females and 165 (51%) males aged 8−87 (45.1 ± 20.9). The BMI of study group was between 14.3 and 47.3 (27.7 ± 5.02). 1.5T and 3.0T MRI scanners were used in the study. The articular cartilage of the knee joint was assessed using the Outerbridge scale. Results: The age of the patients showed a significant correlation with Outerbrige for each compartment of the femorotibial joint (Spearman's rank correlation rho: 0.69−0.74, p < 0.0001). A higher correlation between BMI and Outerbridge was noted in the femur medial (rho = 0.45, p < 0.001) and the tibia medial (rho = 0.43, p < 0.001) than in the femur lateral (rho = 0.29, p < 0.001) and the tibia lateral compartment (rho = 0.34, p < 0.001). Conclusions: The severity of chondromalacia significantly depends on age and BMI level, regardless of gender.

Shoulder Dislocation Incidence and Risk Factors-Rural vs. Urban Populations of Poland.

(1) Background: The aim of this study was to analyze the incidence of shoulder dislocation and to estimate non-modifiable risk factors in rural and urban subgroups in Poland. (2) Methods: The study covered the entire Polish population, divided into urban and rural subgroups and observed between 1 January 2014 and 31 December 2014. The study population consisted of Polish patients with a diagnosis of shoulder dislocation (S43.0) in accordance with the International Statistical Classification of Diseases and Related Health Problems (ICD-10). Records were obtained from the public health care provider National Health Found (Narodowy Fundusz Zdrowia, NFZ). Based on these data, we assessed shoulder dislocation incidence and risk rates, stratifying the study sample by sex, age and place of residence (rural or urban) using the Central Statistical Office (GUS) personal territorial code (TERYT). (3) The incidence was 25.97/100,000 person-years in rural areas and 25.62/100,000 person-years in urban areas. We did not find significant differences in the incidence between the two subgroups. The highest incidence (75.12/100,000 person-years) and the highest risk for shoulder dislocation were found among subjects 80+ years old living in urban areas. Furthermore, men in the third decade of their life living in urban areas showed the highest risk (OR = 7.8, 95% CI; 6.44-9.45, p < 0.001). In both subgroups, the likelihood of shoulder dislocation was significantly lower for the female sex and among children ≤9 years old. However, girls living in rural areas presented with a significantly higher likelihood for dislocation compared with their peers living in urban environments. (4) Conclusions: No significant difference in the incidence rate of shoulder dislocation between Polish residents living in rural and urban areas emerged. The highest incidence was observed among female subjects 80+ years old living in urban environments. The highest risk was found among men in the third decade of their life living in urban areas. In addition, girls in the first decade of their life living in rural areas had more shoulder dislocations than girls living in urban environments. Shoulder dislocation is dominant in female subjects aged 70-79 living in rural areas and in females 80+ years old living in urban areas.

Knee Diameter and Cross-Section Area Measurements in MRI as New Promising Methods of Chondromalacia Diagnosis-Pilot Study.

Background and Objectives: Chondromalacia often affects the knee joint. Risk factors for the development of cartilage degenerative changes include overweight, female sex and age. The use of radiological parameters to assess the knee joint is rarely reported in the literature. Materials and Methods: The study involved 324 patients, including 159 (49%) women and 165 (51%) men, with an age range between 8−87 years (mean: 45.1 ± 20.9). The studied group had a body mass index (BMI) in the range of 14.3−47.3 (mean: 27.7 ± 5.02). A 1.5 Tesla and 3.0 Tesla (T) MRI scanner was used to assess the cartilage of the knee joint using the Outerbridge scale. The radiological parameters analyzed were the Insall−Salvati index, knee surface area, knee AP (antero-posterior) maximal diameter and knee SD (sinistro-dexter) maximal diameter. Results: Parameters such as the knee surface area, knee AP maximal diameter and knee SD maximal diameter showed a significant correlation with Outerbridge Scale (p < 0.014). The age of the patients showed a significant correlation with each knee parameter (p < 0.004). Results of knee AP and SD maximal diameter measurements strongly depended on BMI level. Conclusions: A significant relationship was found between the knee surface area, knee AP maximal diameter and knee SD maximal diameter and the advancement of chondromalacic changes in the knee joint, age and BMI.