Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer

Tertiary lymphoid structures (TLS) are ectopic aggregates of lymphoid cells in inflamed, infected, or tumoral tissues that are easily recognized on an H&E histology slide as discrete entities, distinct from lymphocytes. TLS are associated with improved cancer prognosis but there is no standardised method available to quantify their presence. Previous studies have used immunohistochemistry to determine the presence of specific cells as a marker of the TLS. This has now been proven to be an underestimate of the true number of TLS. Thus, we propose a methodology for the automated identification and quantification of TLS, based on H&E slides. We subsequently determined the mathematical criteria defining a TLS. TLS regions were identified through a deep convolutional neural network and segmentation of lymphocytes was performed through an ellipsoidal model. This methodology had a 92.87% specificity at 95% sensitivity, 88.79% specificity at 98% sensitivity and 84.32% specificity at 99% sensitivity level based on 144 TLS annotated H&E slides implying that the automated approach was able to reproduce the histopathologists’ assessment with great accuracy. We showed that the minimum number of lymphocytes within TLS is 45 and the minimum TLS area is 6,245μm2. Furthermore, we have shown that the density of the lymphocytes is more than 3 times those outside of the TLS. The mean density and standard deviation of lymphocytes within a TLS area are 0.0128/μm2 and 0.0026/μm2 respectively compared to 0.004/μm2 and 0.001/μm2 in non-TLS regions. The proposed methodology shows great potential for automated identification and quantification of the TLS density on digital H&E slides

Management of subtrochanteric femur fractures with internal fixation and recombinant human bone morphogenetic protein-7 in a patient with osteopetrosis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Osteopetrosis is a group of conditions characterized by defects in the osteoclastic function of the bone resulting in defective bone resorption. Clinically, the condition is characterized by a dense, sclerotic, deformed bone which, despite an increased density observable by radiography, often results in an increased propensity to fracture and delayed union.</p> <p>Case Presentation</p> <p>We report the case of a 27-year-old Asian man presenting with bilateral subtrochanteric femur fractures. He had a displaced right subtrochanteric femur fracture after a low-energy fall, which was treated surgically. The second fracture that our patient endured was diagnosed as a stress fracture ten weeks later when he complained of pain in the contralateral left thigh. By that time, the right-sided fracture exhibited no radiographic evidence of healing, and when the left-sided stress fracture was being treated surgically, bone grafting with recombinant human bone morphogenetic protein-7 was also performed on the right side.</p> <p>Conclusion</p> <p>While there are no data supporting the use of bone morphogenic proteins in the management of delayed healing in patients with osteopetrosis, no other reliable osteoinductive grafting options are available to treat this condition. Both fractures in our patient healed, but based on the serial radiographic assessment it is uncertain to what degree the recombinant human bone morphogenetic protein-7 may have contributed to the successful outcome. It may have also contributed to the formation of heterotopic bone around the fracture site. Further investigation of the effectiveness and indications of bone morphogenic protein use for the management of delayed fracture healing in patients with osteopetrosis is warranted.</p

"T2-high" in severe asthma related to blood eosinophil, exhaled nitric oxide and serum periostin

BACKGROUND: Type-2 (T2) immune responses in airway epithelial cells (AECs) classifies mild-moderate asthma into a T2-high phenotype. We examined whether currently-available clinical biomarkers can predict AEC-defined T2-high phenotype within U-BIOPRED cohort. METHODS: The transcriptomic profile of AECs obtained from brushings of 103 patients with asthma and 44 healthy controls was obtained and gene set variation analysis used to determine the relative expression score of T2 asthma using a signature from IL-13-exposed AECs. RESULTS: 37% of asthmatics (45% non-smoking severe asthma, n=49, 33% of smoking or ex-smoking severe asthma, n=18 and 28% mild-moderate asthma, n=36) were T2-high using AEC gene expression. They were more symptomatic with higher levels of nitric oxide in exhaled breath (FeNO) and of blood and sputum eosinophils but not of serum IgE or periostin. Sputum eosinophilia correlated best with the T2-high signature. FeNO (≥30 ppb) and blood eosinophils (≥300/µL) gave a moderate prediction of T2-high asthma. Sputum IL-4, IL-5 and IL-13 protein levels did not correlate with gene expression. CONCLUSION: T2-high severe asthma can be predicted to some extent from raised levels of FeNO, blood and sputum eosinophil counts, but serum IgE or serum periostin were poor predictors. Better bedside biomarkers are needed to detect T2-high