Aortic Dissection Auxiliary Diagnosis Model and Applied Research Based on Ensemble Learning

Aortic dissection (AD), a dangerous disease threatening to human beings, has a hidden onset and rapid progression and has few effective methods in its early diagnosis. At present, although CT angiography acts as the gold standard on AD diagnosis, it is so expensive and time-consuming that it can hardly offer practical help to patients. Meanwhile, the artificial intelligence technology may provide a cheap but effective approach to building an auxiliary diagnosis model for improving the early AD diagnosis rate by taking advantage of the data of the general conditions of AD patients, such as the data about the basic inspection information. Therefore, this study proposes to hybrid five types of machine learning operators into an integrated diagnosis model, as an auxiliary diagnostic approach, to cooperate with the AD-clinical analysis. To improve the diagnose accuracy, the participating rate of each operator in the proposed model may adjust adaptively according to the result of the data learning. After a set of experimental evaluations, the proposed model, acting as the preliminary AD-discriminant, has reached an accuracy of over 80%, which provides a promising instance for medical colleagues.

Integration of Post-Fracturing Spectral Noise Log, Temperature Modeling, and Production Log Diagnoses Water Production and Resolves Uncertainties in Openhole Multistage Fracturing

Hydrocarbon development from tight gas sandstone reservoirs is revolutionizing the current oil and gas market. The most effective development strategy for ultralow- to low-permeability reservoirs involves multistage fracturing. A cemented casing or liner completed with the plug-and-perf method allows nearly full control of fracture initiation depth. In uncemented completions equipped with fracturing sleeves and packers, clearly identifying the fracture initiation points is difficult due to lack of visibility behind the completion and long openhole intervals between packers. Also, the number of fractures initiated in each treatment is uncertain. A lateral was completed with access to 3,190 ft of openhole section across five fracturing stages in a high-temperature and high-pressure tight-gas interval. All stages were successfully stimulated, fracture cleanup flowback was conducted, and entry ports were milled out. A high-definition spectral noise log (SNL) was then conducted along with numerical temperature modeling. Additional logging was done with a set of conventional multiphase sensors. A multi-array production log suite was also performed. Finally, the bottom four stages were isolated with a high-temperature isolation plug based on the integrated diagnosis. The SNL helped to analyze the isolation packer integrity behind the liner. The initiation of multiple fractures was observed, with as many as nine fractures seen in a single-stage interval. A correlation was found between the openhole interval length and the number of fractures. A correlation of fracture gradient (FG) and initiation depths was made for the lateral in a strike-slip fault regime. The fractures were initiated at depths with low calculated FG, confirming the conventional understanding and increasing confidence in rock property calculations from openhole log data. SNL and temperature modeling aided quantitative assessment of flowing fractures and stagewise production behind the liner. Multi-array production logging results quantified the flow and flow profile inside the horizontal liner. The production flow assessments from both techniques were in good agreement. The integration of several datasets was conducted in a single run, which provided a comprehensive understanding of well completion and production. High water producing intervals were isolated. Downstream separator setup after the isolation showed a water cut reduction by 95%. The integration of the post-fracturing logs with the openhole logs and fracturing data is unique. The high-resolution SNL provided valuable insight on fracture initiation points and the integrity of completion packers. Fracturing efficiency, compared to the proppant placed, provides treatment optimization for similar completions in the future.

MPC-17 2021 WHO Classification of Tumors of the CNS, 5th ed

The grading of gliomas based on histological features has been a subject of debate for several decades. While the traditional grading system has failed to stratify the risk of IDH-mutant astrocytoma, canonical histological and proliferative markers may be applicable to the risk stratification of IDH-wildtype astrocytoma. Numerous studies have examined molecular markers to obtain more clinically relevant information that will improve the risk stratification of gliomas. The CDKN2A/B homozygous deletion for IDH-mutant astrocytoma and the following three criteria for IDH-wildtype astrocytoma: the concurrent gain of whole chromosome 7 and loss of whole chromosome 10, TERT promoter mutations, and EGFR amplification, were identified as independent molecular markers of the worst clinical outcomes. Therefore, the 2021 World Health Organization (WHO) Classification of Tumors of the Central Nervous System adopted these molecular markers into the revised grading criteria of IDH-mutant and -wildtype astrocytoma respectively, as a grading system within tumor types. For diffuse gliomas in children, molecular alteration-based classification was adopted, dividing low-grade and high-grade subcategories. New tumor types and subtypes were introduced, some based on DNA methylation profiling. To achieve this novel classification in a resource-limited setting, an integrated diagnosis combining clinical, histological, and molecular information became more important.

Clinical, Morphological, and Molecular Study of Diffuse WHO Grade II and III Astrocytomas: A Retrospective Analysis from a Single Tertiary Care Institute

Introduction Astrocytomas are the most common gliomas, classified on the basis of grade and IDH mutation status according to the World Health Organization (WHO) 2016 update. IDH mutations are seen in 70 to 80% of diffuse grade II and III astrocytomas and are associated with better outcome. They serve as predictive biomarker in IDH-targeted therapies such as small-molecule inhibitors or vaccines. Objective The aim of this study was to analyze the clinical, morphological, immunohistochemical, and molecular genetic characteristics of diffuse astrocytoma (DA: grades II and III). The IDH mutant and wild-type tumors are compared and contrasted with survival analysis on follow-up. Materials and Methods This was a retrospective study conducted on surgically resected tumor specimens. The hematoxylin and eosin-stained slides were examined for histologic features. Immunohistochemistry (IHC) was performed using IDH1R132H, ATRX, p53, and Ki67. All cases of negative immunohistochemical expression of IDH1R132H were subjected to IDH1 mutation analysis by Sanger sequencing. Overall survival was estimated by the Kaplan-Meier method using the log-rank (Mantel–Cox) test. Results The study included 51 cases of DA in the age of 17 to 66 years, mean ± standard deviation was 35.5 ± 9.7 years, and male:female ratio was 2:1.The IDH1R132H cytoplasmic immunopositivity was seen in 36 cases (70.5%), of which 63.6% were of grade II and 72.5% were of grade III. ATRX showed loss of expression in 50 cases (98%), and p53 showed diffuse strong immunohistochemical expression in all the cases of IDH mutant tumors. The difference in the age at presentation for IDH mutant (32.5 years) and wild type tumors (38 years) was statistically significant. Median survival was 55.3 months and 22.2 months in of IDH mutant and wild type cases, respectively. Conclusion IHC and sequencing for IDH mutations is helpful in making an integrated diagnosis and classifying definite molecular subgroups of astrocytic tumors. Mutations in IDH core-elate with survival. IDH mutant tumors showed longer survival duration and are good prognostic indicators.

ET-1 Translational research platform for malignant brain tumors

Introduction: The standard therapy for malignant brain tumors includes surgery and combination therapy with radiation and chemotherapy, but to provide individualized treatment based on the biological and molecular genetic background of the tumor, integrate genetic information with various functional data are required. In this study, we present an overview of our integrated approaches for translational research and clinical management. Methods: In glioma, pre-and intra-operative clinical information, including intraoperative genetic diagnosis, and intraoperative rapid immunohistochemistry is obtained, then a multidisciplinary treatment approach is started based on these integrated data. Specimens collected intraoperatively are cryopreserved for future analysis, and primary cultured cells are routinely collected. The cultured cells are transplanted into the brain of immunodeficient mice to establish patient-derived xenograft model (PDX). Genetic screening, such as IDH, TERT, BRAF, H3F3A mutation and MGMT methylation analysis are routinely assessed within a few days after surgery and used as information for integrated diagnosis. In case of PDX establishment or recurrence, we perform whole exon sequencing or comprehensive genomic assessment to identify genetic abnormalities. If genomic alterations for possible molecular targeted therapy are identified, we assess drug sensitivity test in vitro and in vivo, which are utilized for research to develop optimal molecular targeted therapy. The results, such as the therapeutic effects of molecular targeted drugs, are used for clinical applications. Results: Since the platform was established, we have treated a total of 286 patients, including 189 gliomas and 37 central nervous system lymphomas based on the integrated information. We are currently collecting clinical data to examine if this integrated approach could provide clinical benefit.Conclusion: The translational research system for malignant brain tumors plays an important role in the promotion of clinical and basic research.

PATH-47. THE 2016 WHO CLASSIFICATION AND IT'S CLINICAL IMPACT: THE LEEDS TEACHING HOSPITALS NHS TRUST EXPERIENCE

INTRODUCTION In 2016 the WHO Classification of Tumours of the Central Nervous System was updated to include molecular testing, in addition to the previous standard histological methods; producing a final integrated diagnosis. Although molecular information can guide treatment and aid in prognostication, it adds a significant workload to pathology and genetic testing services. Delayed diagnosis can also add anxiety to patients, at an already traumatic time. AIMS: To determine if final integrated diagnoses, for patients undergoing neurosurgery for CNS tumours, is being provided in an appropriate time frame, and whether it changes clinical management. METHODS All patients >16 years at the time of surgery with a histopathologically-confirmed CNS tumour were identified from 2016-2020. A retrospective analysis of the time taken to produce an integrated histological diagnosis took place, using the date of surgery and date of verified final integrated report being the first and last data points respectively. Data were collected by accessing electronic and paper health records, and local databases. Changes in clinical management between the initial histology result and the final integrated diagnosis were classified as no change or a major change. RESULTS 1390 surgical procedures for CNS pathology were identified between 2016-2020, producing 361 final integrated diagnosis reports. 64 (18%) of these reports resulted in a major change in clinical management when compared to the initial histology report. The turn-around time for initial histology from date of surgery was a mean of 9 days and a mean of 34 days for the final integrated diagnosis. CONCLUSIONS The integrated diagnosis is essential for providing the gold standard of treatment for patients, although for the majority of patients it does not change their clinical management. Further study and discussion is required about the role of the final integrated diagnosis in the management of patients with CNS tumours.

PATH-48. RAPID-CNS2: RAPID COMPREHENSIVE ADAPTIVE NANOPORE-SEQUENCING OF CNS TUMORS, A PROOF OF CONCEPT STUDY

BACKGROUND The WHO classification 2021 includes multiple molecular markers for routine diagnostics in addition to histology. Sequencing setup for complete molecular profiling requires considerable investment, while batching samples for sequencing and methylation profiling can delay turnaround time. We introduce RAPID-CNS2, a nanopore adaptive sequencing pipeline that enables comprehensive mutational, methylation and copy number profiling of CNS tumours with a single third generation sequencing assay. It can be run for single samples and offers highly flexible target selection requiring no additional library preparation. METHODS Utilising ReadFish, a toolkit enabling targeted nanopore sequencing, we sequenced DNA from 22 diffuse glioma patient samples on a MinION device. Target regions comprised our Heidelberg brain tumour NGS panel and pre-selected CpG sites for methylation classification by an adapted random forest classifier. Pathognomonic alterations, copy number profiles, and methylation classes were called using a custom bioinformatics pipeline. Results were compared to their corresponding NGS panel-seq and EPIC array outputs. RESULTS Complete concordance with the EPIC array was found for copy number profiles from RAPID-CNS2. 94% pathognomonic mutations were congruent with NGS panel-seq. MGMT promoter status was correctly identified in all samples. Methylation families were detected with 96% congruence. Among the alterations decisive for rendering a classification-compatible integrated diagnosis, 97% of the alterations were consistent over the entire cohort (completely congruent in 19/22 cases and sufficient for unequivocal diagnosis in all). CONCLUSIONS RAPID-CNS2 provides a swift and highly flexible alternative to conventional NGS and array- based methods for SNV/Indel analysis, detection of copy number alterations and methylation classification. The turnaround time of ~4 days can be further shortened to < 12h by altering target sizes. It offers a low-capital approach that would be cost-efficient for low throughput settings and invaluable in cases requiring immediate diagnoses.

Molecular Stratification of Childhood Ependymomas as a Basis for Personalized Diagnostics and Treatment

Ependymomas are among the most enigmatic tumors of the central nervous system, posing enormous challenges for pathologists and clinicians. Despite the efforts made, the treatment options are still limited to surgical resection and radiation therapy, while none of conventional chemotherapies is beneficial. While being histologically similar, ependymomas show considerable clinical and molecular diversity. Their histopathological evaluation alone is not sufficient for reliable diagnostics, prognosis, and choice of treatment strategy. The importance of integrated diagnosis for ependymomas is underscored in the recommendations of Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy. These updated recommendations were adopted and implemented by WHO experts. This minireview highlights recent advances in comprehensive molecular-genetic characterization of ependymomas. Strong emphasis is made on the use of molecular approaches for verification and specification of histological diagnoses, as well as identification of prognostic markers for ependymomas in children.

Metachronous oligodendroglial tumours with different IDH mutational profile in a young patient

Aims Oligodendroglioma is molecularly defined by mutation of isocitrate dehydrogenase (IDH) and 1p19q codeletion. IDH mutation is an early driver of tumorigenesis, via its oncometabolite 2-hydroxyglutarate, regardless of the exact mutational subtype in homologues IDH1 or IDH2. IDH mutant cells then acquire 1p19q codeletion, with haploinsufficiency likely to contribute to oncogenesis by reduced expression of genes on 1p and 19q, as well as mutations in TERT, FUBP1 (on 1p31.1) in ~30% and CIC (on 19q13.2) in ~>60% of 1p19q-codeleted gliomas. We present a case of a young patient with metachronous oligodendroglial tumours, initially thought to represent contralateral recurrence of the same disease. However, IDH mutation analysis in each tumour revealed distinct types of mutations, involving both IDH1 and IDH2, indicating different cellular lineages of tumorigenesis. We aim to present this unusual combination by illustrating the histology and molecular profile, and review the literature with regards to multifocal but molecularly distinct glioma. Method Case: The patient is a 33 year old man initially presenting with seizures, who was found to have a frontal lobe lesion (hence called tumour 1) with focal radiological enhancement, followed by a contralateral lesion in the parietal lobe 6 months later (hence designated as tumour 2). He underwent separate surgical debulking, and each time, tumour tissue was histologically and genetically examined. Testing included targeted mutation screening by immunohistochemistry and PCR based methods, pyrosequencing for MGMT methylation analysis, FISH for chromosomal LOH analysis of 1p and 19q, immunohistochemistry for mismatch repair enzymes and next generation sequencing. Results Histology of tumour 1 revealed a neoplasm with uniform cells, round nuclei and oligodendroglioma-like clear cell change, without mitoses, microvascular proliferation or necrosis. Immunohistochemistry showed absence of IDH1 R132H mutation, retained expression of ATRX and no altered p53 staining. The ki-67 index reached 6%. Sequencing of IDH1/2 mutations revealed a rare IDH2 mutation (non-/R172K). FISH confirmed codeletion of 1p19q, and the integrated diagnosis was oligodendroglioma, IDH mutant and 1p19q codeleted, WHO grade II. Histology of tumour 2 demonstrated oligodendroglioma morphology in areas, but more cellular and nuclear pleomorphism and focally brisk mitotic activity (7 mitoses in 10 hpf; ki67 index 20%), while both microvascular proliferation and necrosis were absent. Immunohistochemistry showed IDH1 R132H mutation and retained ATRX, while p53 was not expressed. FISH studies confirmed codeletion of 1p19q, and the integrated diagnosis was anaplastic oligodendroglioma, IDH mutant and 1p19q codeleted, WHO-2016 grade III. NGS data and MMR results are compared. Conclusion We present a patient with two histologically similar, but molecularly distinct oligodendroglial tumours affecting both cerebral hemispheres. Apart from the grade, the important difference is the presence of different IDH mutations, 1) a rare IDH2 mutation (non-R172K) and 2) the common IDH1 (R132H) mutation. While both types of IDH mutations identified are known to occur in oligodendroglioma, the difference clearly indicates two distinct lineages of tumorigenesis, especially as IDH mutation is considered an early event in gliomagenesis. IDH2 mutations are often associated with oligodendrogliomas, while IDH1 R132H is recognised to be frequent in both diffuse oligodendroglial and astroglial neoplasms. Multifocal divergent gliomas have been described previously but oligodendrogliomas with differing IDH mutations in the same patient have not knowingly been reported yet. Importantly, though therapeutically irrelevant here, multicentric gliomas do not automatically imply relatedness. However, a common origin or predisposition (here, even predating IDH mutation) may not be ruled out.

P07.04 Rapid-CNS2: Rapid comprehensive adaptive nanopore-sequencing of CNS tumors, a proof of concept study

BACKGROUND The WHO classification 2021 includes multiple molecular markers for routine diagnostics in addition to histology. Sequencing setup for complete molecular profiling requires considerable investment, while batching samples for sequencing and methylation profiling can delay turnaround time. We introduce RAPID-CNS2, a nanopore adaptive sequencing pipeline that enables comprehensive mutational, methylation and copy number profiling of CNS tumours with a single third generation sequencing assay. It can be run for single samples and offers highly flexible target selection requiring no additional library preparation. MATERIAL AND METHODS Utilising ReadFish, a toolkit enabling targeted nanopore sequencing, we sequenced DNA from 22 diffuse glioma patient samples on a MinION device. Target regions comprised our Heidelberg brain tumour NGS panel and pre-selected CpG sites for methylation classification by an adapted random forest classifier. Pathognomonic alterations, copy number profiles, and methylation classes were called using a custom bioinformatics pipeline. Results were compared to their corresponding NGS panel-seq and EPIC array outputs. RESULTS Complete concordance with the EPIC array was found for copy number profiles from RAPID-CNS2. 94% pathognomonic mutations were congruent with NGS panel-seq. MGMT promoter status was correctly identified in all samples. Methylation families were detected with 96% congruence. Among the alterations decisive for rendering a classification-compatible integrated diagnosis, 97% of the alterations were consistent over the entire cohort (completely congruent in 19/22 cases and sufficient for unequivocal diagnosis in all). CONCLUSION RAPID-CNS2 provides a swift and highly flexible alternative to conventional NGS and array-based methods for SNV/Indel analysis, detection of copy number alterations and methylation classification. The turnaround time of ~4 days can be further shortened to <12h by altering target sizes. It offers a low-capital approach that would be cost-efficient for low throughput settings and invaluable in cases requiring immediate diagnoses.