Accuracy of preoperative MRI in the diagnosis of subscapularis tears.

INTRODUCTION: The subscapularis has received little attention in the orthopedic literature, although such lesions are evident in up to 40 % of arthroscopies. An accurate diagnosis is important in clinical practice, as it affects both patient prognosis and surgical planning. The aim of this study was to evaluate the accuracy of preoperative MRI for the identification of subscapularis tears. Our secondary aim involved the identification of factors that may be predictive for the presence of subscapularis tears. MATERIALS AND METHODS: This retrospective case series included patients undergoing shoulder arthroscopy due to rotator cuff injury. MRI was performed using a 1.5 T unit, and the results were assessed by a musculoskeletal radiologist. The findings were compared to those of arthroscopic inspection. RESULTS: A total of 93 shoulders were analyzed. The overall accuracy was 82 %, with values of 79 % for partial tears and 89 % for full-thickness tears. Tears requiring repair demonstrated an accuracy of 88 %. Infraspinatus tears, fatty degeneration of the subscapularis, biceps instability and age were identified as predictive factors for the presence of injury. CONCLUSIONS: MRI of the shoulder demonstrated an accuracy of 82 % for the diagnosis of subscapularis tears. The accuracy values for partial and full-thickness tears were 79 and 89 %, respectively. LEVEL DE EVIDENCE: III, development of diagnostic criteria with universally applied reference-nonconsecutive patients.

MRI T2 mapping assessment of T2 relaxation time in desmoid tumors as a quantitative imaging biomarker of tumor response: preliminary results.

Objectives: Because size-based imaging criteria poorly capture biologic response in desmoid-type fibromatosis (DF), changes in MRI T2 signal intensity are frequently used as a response surrogate, but remain qualitative. We hypothesized that absolute quantification of DF T2 relaxation time derived from parametric T2 maps would be a feasible and effective imaging biomarker of disease activity. Methods: This IRB-approved retrospective study included 11 patients with DF, managed by observation or systemic therapy, assessed by 3T MRI. Tumor maximum diameter, volume, and T2-weighted signal intensity were derived from manual tumor segmentations. Tumor:muscle T2 signal ratios were recorded. Two readers measured tumor T2 relaxation times using a commercial T2 scanning sequence, manual ROI delineation and commercial calculation software enabling estimation of reader reliability. Objective response rates based on RECIST1.1 and best responses were compared between size-based and signal-based parameters. Results: Median patient age was 52.6 years; 8 subjects were female (73%). Nine patients with longitudinal assessments were followed for an average of 314 days. Median baseline tumor diameter was 7.2 cm (range 4.4 - 18.2 cm). Median baseline T2 was 65.1 ms (range 40.4 - 94.8 ms, n=11); median at last follow-up was 44.3 ms (-32% from baseline; range 29.3 - 94.7 ms, n=9). T2 relaxation times correlated with tumor:muscle T2 signal ratios, Spearman p=0.78 (p<0.001). T2 mapping showed high inter-reader reliability, ICC=0.84. The best response as a percentage change in T2 values was statistically significant (mean -17.9%, p=0.05, paired t-test) while change in diameter was not (mean -8.9%, p=0.12). Conclusions: Analysis of T2 relaxation time maps of DF may offer a feasible quantitative biomarker for assessing the extent of response to treatment. This approach may have high inter-reader reliability.

Influence of seasonality on the aerosol microbiome of the Amazon rainforest.

The Amazon rainforest is the world's largest tropical forest, and this biome may be a significant contributor to primary biological aerosol (PBA) emissions on a global scale. These aerosols also play a pivotal role in modulating ecosystem dynamics, dispersing biological material over geographic barriers and influencing climate through radiation absorption, light scattering, or acting as cloud condensation nuclei. Despite their importance, there are limited studies investigating the effect of environmental variables on the bioaerosol composition in the Amazon rainforest. Here we present a 16S rRNA gene-based amplicon sequencing approach to investigate the bacterial microbiome in aerosols of the Amazon rainforest during distinct seasons and at different heights above the ground. Our data revealed that seasonal changes in temperature, relative humidity, and precipitation are the primary drivers of compositional changes in the Amazon rainforest aerosol microbiome. Interestingly, no significant differences were observed in the bacterial community composition of aerosols collected at ground and canopy levels. The core airborne bacterial families present in Amazon aerosol were Enterobacteriaceae, Beijerinckiaceae, Polyangiaceae, Bacillaceae and Ktedonobacteraceae. By correlating the bacterial taxa identified in the aerosol with literature data, we speculate that the phyllosphere may be one possible source of airborne bacteria in the Amazon rainforest. Results of this study indicate that the aerosol microbiota of the Amazon Rainforest are fairly diverse and principally impacted by seasonal changes in temperature and humidity.

Uncovering prokaryotic biodiversity within aerosols of the pristine Amazon forest.

Biological aerosols (bioaerosol) are atmospheric particles that act as a dispersion unit of living organisms across the globe thereby affecting the biogeographic distribution of organisms. Despite their importance, there is virtually no knowledge about bioaerosols emitted by pristine forests. Here we provide the very first survey of the prokaryotic community of a bioaerosol collected inside pristine Amazon forest at 2 m above ground. Total atmospheric particles were collected at the Amazon Tall Tower Observatory, subjected to metagenomic DNA extraction and the prokaryotic diversity was determined by 16S rRNA gene amplicon sequencing. A total of 271,577 reads of 250 bp of the 16S rRNA gene amplicon were obtained. Only 27% of the reads could be classified using the 16S SILVA database. Most belonged to Proteobacteria, Actinobacteria and Firmicutes which is in good agreement with other bioaerosol studies. Further inspection of the reads using Blast searches and the 18S SILVA database revealed that most of the dataset was composed of Fungi sequences. The identified microbes suggest that the atmosphere may act as an important gateway to interchange bacteria between plants, soil and water ecosystems.

Accuracy of preoperative MRI in the diagnosis of disorders of the long head of the biceps tendon.

OBJETIVES: To evaluate the accuracy of magnetic resonance imaging (MRI) in the detection of disorders of the long head of the biceps tendon (LHBT). The secondary objective was to investigate predictive factors for tears and instability. METHODS: This retrospective case series involved patients undergoing shoulder arthroscopy due to rotator cuff injury. MRI was performed in a 1.5T scanner and was evaluated by a musculoskeletal radiologist. The findings were compared with those of arthroscopic inspection. RESULTS: A total of 90 shoulders were analyzed. Regarding tears, there was 67% sensitivity and 98% specificity. Regarding instabilities, the values were 53% and 72%, respectively. Tears and fatty degeneration of the infraspinatus are predictive factors for tears of the LHBT. Tears of the subscapularis and infraspinatus, retraction of the supraspinatus and infraspinatus equal to or greater than 30mm, and fatty degeneration of the infraspinatus and subscapularis are predictive factors for instability. CONCLUSION: Compared to arthroscopy, the shoulder MRI has a sensitivity of 67% and a specificity of 98% for the detection of complete tears of the LHBT. For instability, the values are 53% and 72%, respectively.