RESUMO
The clinical application of heart valve scaffolds is hindered by complications associated with the activation of valvular interstitial cell-like (VIC-like) cells and their transdifferentiation into myofibroblasts. This study aimed to examine several molecular pathway(s) that may trigger the overactive myofibroblast phenotypes in the implanted scaffolds. So, we investigated the influence of three molecular pathways - macrophage-induced inflammation, the TGF-ß1-SMAD2, and WNT/ß-catenin ß on VIC-like cells during tissue engineering of heart valve scaffolds. We implanted electrospun heart valve scaffolds in adult sheep for up to 6 months in the right ventricular outflow tract (RVOT) and analyzed biomolecular (gene and protein) expression associated with the above three pathways by the scaffold infiltrating cells. The results showed a gradual increase in gene and protein expression of markers related to the activation of VIC-like cells and the myofibroblast phenotypes over 6 months of scaffold implantation. Conversely, there was a gradual increase in macrophage activity for the first three months after scaffold implantation. However, a decrease in macrophage activity from three to six months of scaffold tissue engineering suggested that immunological signal factors were not the primary cause of myofibroblast phenotype. Similarly, the gene and protein expression of factors associated with the TGF-ß1-SMAD2 pathway in the cells increased in the first three months but declined in the next three months. Contrastingly, the gene and protein expression of factors associated with the WNT/ß-catenin pathway increased significantly over the six-month study. Thus, the WNT/ß-catenin pathway could be the predominant mechanism in activating VIC-like cells and subsequent myofibroblast phenotype.
RESUMO
Preclinical in vivo evaluation is an essential step in the progression of new cardiac devices into patient use, with studies predominantly performed in the domestic sheep model. A growing area of interest in cardiac device development is transcatheter mitral valve replacement (TMVR). Clinically, multimodal imaging, or computed tomography (CT) and echocardiography (echo) are used extensively to preoperatively determine mitral valve morphology prior to an intervention, but there is no description on how these modalities can be implemented to support preclinical studies. The purpose of this study is to apply clinically relevant CT and echo acquisition and assessment techniques to a large group of naive research sheep in order to analyze and report modality-related effects on mitral valve dimensional reference intervals in the sheep model. To this end, fifty-five adult domestic sheep underwent preoperative CT and echo exams and resultant images were analyzed using a landmark-based multiplanar measurement protocol and compiled into a master dataset for statistical analysis. We found moderate agreement between CT and echo-derived measurements of the mitral valve in sheep and propose the first clinically-relevant dimensional indices for the sheep's naive mitral valve which can be used to guide future studies evaluating novel TMVR devices. This study is the first of its kind in proposing a reproducible method for detailed examination of the mitral valve in the sheep model using clinically-relevant multimodal imaging. As in patients, CT and echo can reveal accurate native mitral valve dimensions in the sheep prior to preclinical TMVR studies.
Assuntos
Ecocardiografia , Implante de Prótese de Valva Cardíaca , Valva Mitral , Imagem Multimodal , Tomografia Computadorizada por Raios X , Animais , Valva Mitral/diagnóstico por imagem , Valva Mitral/cirurgia , Ovinos , Implante de Prótese de Valva Cardíaca/métodos , Ecocardiografia/métodos , Tomografia Computadorizada por Raios X/métodos , Imagem Multimodal/métodos , Carneiro Doméstico , Cateterismo Cardíaco/métodosRESUMO
BACKGROUND: Pathologic antibody mediated rejection (pAMR) remains a major driver of graft failure in cardiac transplant patients. The endomyocardial biopsy remains the primary diagnostic tool but presents with challenges, particularly in distinguishing the histologic component (pAMR-H) defined by 1) intravascular macrophage accumulation in capillaries and 2) activated endothelial cells that expand the cytoplasm to narrow or occlude the vascular lumen. Frequently, pAMR-H is difficult to distinguish from acute cellular rejection (ACR) and healing injury. With the advent of digital slide scanning and advances in machine deep learning, artificial intelligence technology is widely under investigation in the areas of oncologic pathology, but in its infancy in transplant pathology. For the first time, we determined if a machine learning algorithm could distinguish pAMR-H from normal myocardium, healing injury and ACR. MATERIALS AND METHODS: A total of 4,212 annotations (1,053 regions of normal, 1,053 pAMR-H, 1,053 healing injury and 1,053 ACR) were completed from 300 hematoxylin and eosin slides scanned using a Leica Aperio GT450 digital whole slide scanner at 40X magnification. All regions of pAMR-H were annotated from patients confirmed with a previous diagnosis of pAMR2 (>50% positive C4d immunofluorescence and/or >10% CD68 positive intravascular macrophages). Annotations were imported into a Python 3.7 development environment using the OpenSlide™ package and a convolutional neural network approach utilizing transfer learning was performed. RESULTS: The machine learning algorithm showed 98% overall validation accuracy and pAMR-H was correctly distinguished from specific categories with the following accuracies: normal myocardium (99.2%), healing injury (99.5%) and ACR (99.5%). CONCLUSION: Our novel deep learning algorithm can reach acceptable, and possibly surpass, performance of current diagnostic standards of identifying pAMR-H. Such a tool may serve as an adjunct diagnostic aid for improving the pathologist's accuracy and reproducibility, especially in difficult cases with high inter-observer variability. This is one of the first studies that provides evidence that an artificial intelligence machine learning algorithm can be trained and validated to diagnose pAMR-H in cardiac transplant patients. Ongoing studies include multi-institutional verification testing to ensure generalizability.
Assuntos
Rejeição de Enxerto , Transplante de Coração , Miocárdio , Valor Preditivo dos Testes , Humanos , Transplante de Coração/efeitos adversos , Rejeição de Enxerto/imunologia , Rejeição de Enxerto/patologia , Rejeição de Enxerto/diagnóstico , Biópsia , Miocárdio/patologia , Miocárdio/imunologia , Reprodutibilidade dos Testes , Interpretação de Imagem Assistida por Computador/métodos , Resultado do Tratamento , Aprendizado de Máquina , Aprendizado Profundo , Macrófagos/imunologia , Macrófagos/patologia , Estudos RetrospectivosAssuntos
Mesotelioma , Humanos , Mesotelioma/epidemiologia , Mesotelioma/induzido quimicamente , AmiantoRESUMO
BACKGROUND: The diagnosis of mesothelioma may be challenging. We investigated a large database of cases in order to determine the frequency with which a diagnosis of mesothelioma was made incorrectly and the most frequent causes of error. DESIGN: A database including more than 4000 consultation cases of histologically confirmed mesothelioma was examined to identify cases in which mesothelioma was diagnosed by at least one pathologist when the available information pointed towards a different diagnosis. RESULTS: There were 311 cases misdiagnosed as mesothelioma. The most common category was metastatic carcinoma to the pleura or peritoneum (129 cases: 73 lung carcinomas, 15 renal cell carcinomas). The next most common category was primary lung cancer (111 cases: 55 sarcomatoid carcinoma, 56 pseudomesotheliomatous carcinoma). The third most common category was primary malignancies arising from or near the serosal membranes (33 cases). The fourth most common category was fibrous pleurisy (38 cases). The most common errors were failure to consider important radiographic information regarding the gross distribution of tumor, lack of awareness or consideration of another malignancy, overreliance on certain immunohistochemical results, and failure to perform certain diagnostic histochemical, immunohistochemical, or ultrastructural studies. CONCLUSIONS: There are a number of diagnostic pitfalls that can lead to the over diagnosis of mesothelioma. Careful attention to clinical and radiographic information as well as performance of appropriate ancillary tests can help to prevent such misdiagnoses. Detailed examples will be presented to assist in the avoidance of these pitfalls with emphasis on the most commonly observed errors.
Assuntos
Carcinoma , Neoplasias Pulmonares , Mesotelioma Maligno , Mesotelioma , Neoplasias Pleurais , Humanos , Sobrediagnóstico , Neoplasias Pleurais/diagnóstico , Neoplasias Pleurais/metabolismo , Neoplasias Pleurais/patologia , Biomarcadores Tumorais/análise , Mesotelioma/diagnóstico , Mesotelioma/patologia , Mesotelioma Maligno/diagnóstico , Carcinoma/patologia , Neoplasias Pulmonares/diagnóstico , Neoplasias Pulmonares/patologia , Diagnóstico DiferencialRESUMO
Asbestosis, defined as diffuse pulmonary fibrosis caused by inhalation of asbestos fibers, occurs after heavy exposures to asbestos dust over several decades. Because workplace exposures have been significantly curtailed since the banning of asbestos in insulation products, we were interested in examining the clinicopathological characteristics of cases diagnosed in the 21st century. The consultation files of one of the authors (VLR) were reviewed for cases of asbestosis diagnosed since 1/1/2001. 102 cases were identified, with a median age of 75 years (range: 45-89). There were 100 men and 2 women. The women were from Turkey and Brazil (none from the United States). Malignancies were present in 78 cases, including 38 lung cancers, 29 pleural mesotheliomas, and 8 peritoneal mesotheliomas. The grade of asbestosis was available in 88 cases (median severity of 2; scale: 1-4). Pleural plaque was present in 94% of cases. The most common exposure categories were insulators (39), shipyard workers (16), asbestos manufacturing (9), boiler workers (8) and pipefitter/welders (6). The median duration of exposure was 33 years (range: 2-49 years). Lung fiber burden analysis was performed in 34 cases, with amosite being the predominant fiber type. Results were compared with similar information for 475 cases diagnosed prior to 1/1/2001.
Assuntos
Amianto , Asbestose , Neoplasias Pulmonares , Mesotelioma Maligno , Mesotelioma , Exposição Ocupacional , Masculino , Humanos , Feminino , Pessoa de Meia-Idade , Idoso , Idoso de 80 Anos ou mais , Asbestose/patologia , Pulmão/patologia , Mesotelioma/complicações , Mesotelioma/patologia , Amianto Amosita , Neoplasias Pulmonares/patologiaRESUMO
The objective of this study was to determine if physicians are compensated equally for the treatment of femoral neck fractures based on fixation method in a propensity score matched cohort of patients. The American College of Surgeons' National Surgical Quality Improvement Project (ACS NSQIP) database was queried for patients undergoing open reduction internal fixation (ORIF), hemiarthroplasty (HA), and total hip arthroplasty (THA) for femoral neck fractures. Exact matching was used to account for differences in patient-specific variables and underlying medical comorbidities. Total relative value units (RVU), operative time, RVU/minute, and reimbursement/minute were compared between the three procedures after exact matching to assess relative valuation. Propensity score matching resulted in a total of 4,581 patients eligible for final data analysis (1,527 patients in each treatment group). The groups were very well matched for age, sex, BMI, comorbidities, and American Society of Anesthesiologists (ASA) class (p > 0.99 for all). When dividing compensation by case duration, ORIF generated the most RVUs per minute (0.31 ± 0.19 or $11.01 ± 7.02) followed by THA (0.27 ± 0.14 or $9.86 ± 5.15) and HA (0.25 ± 0.1 or $8.99 ± 3.75; p<0.001 for all). This study shows that orthopaedic surgeons are compensated the most for ORIF followed by THA and HA for fixation of femoral neck fractures. (Journal of Surgical Orthopaedic Advances 32(3):164-168, 2023).