Artificial intelligence approaches for early detection of neurocognitive disorders among older adults.

Introduction: Dementia is one of the major global health issues among the aging population, characterized clinically by a progressive decline in higher cognitive functions. This paper aims to apply various artificial intelligence (AI) approaches to detect patients with mild cognitive impairment (MCI) or dementia accurately. Methods: Quantitative research was conducted to address the objective of this study using randomly selected 343 Saudi patients. The Chi-square test was conducted to determine the association of the patient's cognitive function with various features, including demographical and medical history. Two widely used AI algorithms, logistic regression and support vector machine (SVM), were used for detecting cognitive decline. This study also assessed patients' cognitive function based on gender and developed the predicting models for males and females separately. Results: Fifty four percent of patients have normal cognitive function, 34% have MCI, and 12% have dementia. The prediction accuracies for all the developed models are greater than 71%, indicating good prediction capability. However, the developed SVM models performed the best, with an accuracy of 93.3% for all patients, 94.4% for males only, and 95.5% for females only. The top 10 significant predictors based on the developed SVM model are education, bedtime, taking pills for chronic pain, diabetes, stroke, gender, chronic pains, coronary artery diseases, and wake-up time. Conclusion: The results of this study emphasize the higher accuracy and reliability of the proposed methods in cognitive decline prediction that health practitioners can use for the early detection of dementia. This research can also stipulate substantial direction and supportive intuitions for scholars to enhance their understanding of crucial research, emerging trends, and new developments in future cognitive decline studies.

Primary Thymic Hodgkin Lymphoma Coexisting with Thymoma and Myasthenia Gravis: A Case Report.

BACKGROUND Myasthenia gravis is a neuromuscular disorder that is strongly associated with thymoma. Although the presence of myasthenia gravis with other tumors is uncommon, approximately 50% of patients with thymoma have myasthenia gravis. Thymic Hodgkin lymphoma should be considered due to the multiple reported cases of patients with myasthenia gravis and Hodgkin lymphoma. In this report, we present the case of 24-year-old woman with myasthenia gravis who was incidentally found to have coexisting thymoma with thymic Hodgkin lymphoma. CASE REPORT A 24-year-old woman with a known case of vitiligo presented with a 2-year history of diplopia and incidental anterior mediastinal mass. Following investigations, myasthenia gravis was diagnosed and managed by pyridostigmine, prednisolone, and azathioprine. Regarding the anterior mediastinal mass, thymoma was suspected based on the presence of myasthenia gravis and radiological findings. She underwent extended transsternal thymectomy. The final histopathological report of the dissected thymus disclosed Hodgkin lymphoma pathology coexisting with thymoma. After the diagnosis of Hodgkin lymphoma nodular sclerosis type IIA was confirmed, 6 cycles of chemotherapy were administered. Four years of follow-up revealed no evidence of Hodgkin lymphoma. However, her symptoms of myasthenia gravis persisted despite Hodgkin lymphoma remission. CONCLUSIONS There is an unclear association between myasthenia gravies and Hodgkin lymphoma. Prior reports revealed regression of myasthenia gravies following Hodgkin lymphoma management, which suggests that myasthenia could be a complication of Hodgkin lymphoma. However, in our case, myasthenia gravis persisted after Hodgkin lymphoma management; therefore, further studies are needed to explore this association.

Intradural extramedullary spinal cord meningioma with a rare extradural foraminal extension: A case report.

Background: Meningiomas are mostly benign and slow-growing neoplasms of the central nervous system. Spinal meningiomas account for up to 45% of all intradural spinal tumors in adults and up to 25%-45% of all spinal tumors. Spinal extradural meningiomas are rare and may be easily confused with malignant neoplasms. Case description: A 24-year-old woman was presented to our hospital with paraplegia and loss of sensation in the T7 dermatome and lower body. MRI findings showed T6-T7 right-sided intradural extramedullary and extradural lesion, measuring 1.4 cm × 1.5 cm × 3 cm, extending to the right foramen, compressing the spinal cord, and displacing it to the left. Hyperintense lesion on T2 and hypointense lesion on T1 were observed. The patient reported improvement after surgery and during follow-up. We recommend maximizing the decompression during surgery to achieve better clinical outcome. Extradural meningiomas represent 5% of all meningiomas; therefore, having an intradural on top of extradural meningioma with extraforaminal extensions makes this a unique and rare case. Conclusion: Meningiomas can be easily missed in diagnosis depending on imaging and the pathognomonic pattern it represents, which can mimic other pathologies, such as schwannomas. Therefore, surgeons should always suspect their patient having a meningioma even if the pattern is not typical. Moreover, preoperative preparation, such as navigation and defect closure, must be taken in case it turns out be a meningioma instead of the presumed pathology.

Compound computer vision workflow for efficient and automated immunohistochemical analysis of whole slide images.

AIMS: Immunohistochemistry (IHC) assessment of tissue is a central component of the modern pathology workflow, but quantification is challenged by subjective estimates by pathologists or manual steps in semi-automated digital tools. This study integrates various computer vision tools to develop a fully automated workflow for quantifying Ki-67, a standard IHC test used to assess cell proliferation on digital whole slide images (WSIs). METHODS: We create an automated nuclear segmentation strategy by deploying a Mask R-CNN classifier to recognise and count 3,3'-diaminobenzidine positive and negative nuclei. To further improve automation, we replaced manual selection of regions of interest (ROIs) by aligning Ki-67 WSIs with corresponding H&E-stained sections, using scale-invariant feature transform (SIFT) and a conventional histomorphological convolutional neural networks to define tumour-rich areas for quantification. RESULTS: The Mask R-CNN was tested on 147 images generated from 34 brain tumour Ki-67 WSIs and showed a high concordance with aggregate pathologists' estimates ([Formula: see text] assessors; [Formula: see text] r=0.9750). Concordance of each assessor's Ki-67 estimates was higher when compared with the Mask R-CNN than between individual assessors (ravg=0.9322 vs 0.8703; p=0.0213). Coupling the Mask R-CNN with SIFT-CNN workflow demonstrated ROIs can be automatically chosen and partially sampled to improve automation and dramatically decrease computational time (average: 88.55-19.28 min; p<0.0001). CONCLUSIONS: We show how innovations in computer vision can be serially compounded to automate and improve implementation in clinical workflows. Generalisation of this approach to other ancillary studies has significant implications for computational pathology.

Trends in AI-powered Classification of Thyroid Neoplasms Based on Histopathology Images - a Systematic Review.

Background: Assessment of thyroid nodules histopathology using AI is crucial for an accurate diagnosis. This systematic review analyzes recent works employing deep learning approaches for classifying thyroid nodules based on histopathology images, evaluating their performance, and identifying limitations. Methods: Eligibility criteria focused on peer-reviewed English papers published in the last 5 years, applying deep learning to categorize thyroid histopathology images. The PubMed database was searched using relevant keyword combinations. Results: Out of 103 articles, 11 studies met inclusion criteria. They used convolutional neural networks to classify thyroid neoplasm. Most studies aimed for basic tumor subtyping; however, 3 studies targeted the prediction of tumor-associated mutation. Accuracy ranged from 77% to 100%, with most over 90%. Discussion: The findings from our analysis reveal the effectiveness of deep learning in identifying discriminative morphological patterns from histopathology images, thus enhancing the accuracy of thyroid nodule histopathological classification. Key limitations were small sample sizes, subjective annotation, and limited dataset diversity. Further research with larger diverse datasets, model optimization, and real-world validation is essential to translate these tools into clinical practice.

Synchronous Malignant Peritoneal Mesothelioma and Sigmoid Adenocarcinoma: a Challenging Clinical Entity.

Background: Malignant peritoneal mesothelioma (MPM) represents a rare clinical entity. The synchronous existence of MPM with other malignancies as colonic adenocarcinoma have been rarely reported. Its diagnosis and management are challenging given its complexity and rarity. Objective: Herein, we report a case of epithelioid subtype of MPM occurring synchronously with sigmoid colonic adenocarcinoma, along with review of the literature. Case presentation: An elderly female patient was referred as case of rectosigmoid mass. She reported history of abdominal pain, per-rectal bleeding, anorexia, and significant weight loss. Her computed-tomography scan of the abdomen revealed a fistulizing sigmoid mass and multiple enlarged lymphnodes with omental nodulation. The colonoscopy revealed a large fungating mass and the endoscopic biopsies were reported as colonic adenocarcinoma. The patient was scheduled laparoscopic low anterior resection. However, the diagnostic laparoscopy revealed several nodules disseminated all over the peritoneum, suggestive of peritoneal mesothelioma. Therefore, the decision was changed to create transverse colostomy after examination obtaining multiple biopsies from the omental and peritoneal nodules. The histopathological revealed MPM and the final diagnosis was sigmoid adenocarcinoma with synchronous MPM. The patient was started on palliative chemotherapy (capecitabine) without active management of MPM because of her general condition. She was followed up with a good clinical course. Conclusion: MPM is an overlooked entity with vague clinical presentation. Synchronous MPM with colorectal cancer is rare with only few published case reports. Its diagnosis is challenging, and its management should be tailored according to the patient. This case is the first reported case in Saudi Arabia and the Middle East.

Integrating morphologic and molecular histopathological features through whole slide image registration and deep learning.

BACKGROUND: Modern molecular pathology workflows in neuro-oncology heavily rely on the integration of morphologic and immunohistochemical patterns for analysis, classification, and prognostication. However, despite the recent emergence of digital pathology platforms and artificial intelligence-driven computational image analysis tools, automating the integration of histomorphologic information found across these multiple studies is challenged by large files sizes of whole slide images (WSIs) and shifts/rotations in tissue sections introduced during slide preparation. METHODS: To address this, we develop a workflow that couples different computer vision tools including scale-invariant feature transform (SIFT) and deep learning to efficiently align and integrate histopathological information found across multiple independent studies. We highlight the utility and automation potential of this workflow in the molecular subclassification and discovery of previously unappreciated spatial patterns in diffuse gliomas. RESULTS: First, we show how a SIFT-driven computer vision workflow was effective at automated WSI alignment in a cohort of 107 randomly selected surgical neuropathology cases (97/107 (91%) showing appropriate matches, AUC = 0.96). This alignment allows our AI-driven diagnostic workflow to not only differentiate different brain tumor types, but also integrate and carry out molecular subclassification of diffuse gliomas using relevant immunohistochemical biomarkers (IDH1-R132H, ATRX). To highlight the discovery potential of this workflow, we also examined spatial distributions of tumors showing heterogenous expression of the proliferation marker MIB1 and Olig2. This analysis helped uncover an interesting and unappreciated association of Olig2 positive and proliferative areas in some gliomas (r = 0.62). CONCLUSION: This efficient neuropathologist-inspired workflow provides a generalizable approach to help automate a variety of advanced immunohistochemically compatible diagnostic and discovery exercises in surgical neuropathology and neuro-oncology.

Genomic predictors of response to PD-1 inhibition in children with germline DNA replication repair deficiency.

Cancers arising from germline DNA mismatch repair deficiency or polymerase proofreading deficiency (MMRD and PPD) in children harbour the highest mutational and microsatellite insertion-deletion (MS-indel) burden in humans. MMRD and PPD cancers are commonly lethal due to the inherent resistance to chemo-irradiation. Although immune checkpoint inhibitors (ICIs) have failed to benefit children in previous studies, we hypothesized that hypermutation caused by MMRD and PPD will improve outcomes following ICI treatment in these patients. Using an international consortium registry study, we report on the ICI treatment of 45 progressive or recurrent tumors from 38 patients. Durable objective responses were observed in most patients, culminating in a 3 year survival of 41.4%. High mutation burden predicted response for ultra-hypermutant cancers (>100 mutations per Mb) enriched for combined MMRD + PPD, while MS-indels predicted response in MMRD tumors with lower mutation burden (10-100 mutations per Mb). Furthermore, both mechanisms were associated with increased immune infiltration even in 'immunologically cold' tumors such as gliomas, contributing to the favorable response. Pseudo-progression (flare) was common and was associated with immune activation in the tumor microenvironment and systemically. Furthermore, patients with flare who continued ICI treatment achieved durable responses. This study demonstrates improved survival for patients with tumors not previously known to respond to ICI treatment, including central nervous system and synchronous cancers, and identifies the dual roles of mutation burden and MS-indels in predicting sustained response to immunotherapy.

Leukoencephalopathy with brain calcifications and cysts (Labrune syndrome) case report: diagnosis and management of a rare neurological disease.

BACKGROUND: Leukoencephalopathy with brain calcifications and cysts (LCC; also known as Labrune syndrome) is a rare genetic microangiopathy caused by biallelic mutations in SNORD118. The mechanisms by which loss-of-function mutations in SNORD118 lead to the phenotype of leukoencephalopathy, calcifications and intracranial cysts is unknown. CASE PRESENTATION: We present the histopathology of a 36-year-old woman with ataxia and neuroimaging findings of diffuse white matter abnormalities, cerebral calcifications, and parenchymal cysts, in whom the diagnosis of LCC was confirmed with genetic testing. Biopsy of frontal white matter revealed microangiopathy with small vessel occlusion and sclerosis associated with axonal loss within the white matter. CONCLUSIONS: These findings support that the white matter changes seen in LCC arise as a consequence of ischemia rather than demyelination.

The centrally restricted diffusion sign on MRI for assessment of radiation necrosis in metastases treated with stereotactic radiosurgery.

PURPOSE: Differentiation of radiation necrosis from tumor progression in brain metastases treated with stereotactic radiosurgery (SRS) is challenging. For this, we assessed the performance of the centrally restricted diffusion sign. METHODS: Patients with brain metastases treated with SRS who underwent a subsequent intervention (biopsy/resection) for a ring-enhancing lesion on preoperative MRI between 2000 and 2020 were included. Excluded were lesions containing increased susceptibility limiting assessment of DWI. Two neuroradiologists classified the location of the diffusion restriction with respect to the post-contrast T1 images as centrally within the ring-enhancement (the centrally restricted diffusion sign), peripherally correlating to the rim of contrast enhancement, both locations, or none. Measures of diagnostic accuracy and 95% CI were calculated for the centrally restricted diffusion sign. Cohen's kappa was calculated to identify the interobserver agreement. RESULTS: Fifty-nine patients (36 female; mean age 59, range 40 to 80) were included, 36 with tumor progression and 23 with radiation necrosis based on histopathology. Primary tumors included 34 lung, 12 breast, 5 melanoma, 3 colorectal, 2 esophagus, 1 head and neck, 1 endometrium, and 1 thyroid. The centrally restricted diffusion sign was seen in 19/23 radiation necrosis cases (sensitivity 83% (95% CI 63 to 93%), specificity 64% (95% CI 48 to 78%), PPV 59% (95% CI 42 to 74%), NPV 85% (95% CI 68 to 94%)) and 13/36 tumor progression cases (difference p < 0.001). Interobserver agreement was substantial, at 0.61 (95% CI 0.45 to 70.8). CONCLUSION: We found a low probability of radiation necrosis in the absence of the centrally restricted diffusion sign.

Cardiac Myxoma: Typical Presentation but Unusual Histology.

Cardiac myxoma, a benign heart tumor, is the most common primary tumor of the heart. Glandular differentiation within these tumors is rare, occurring in approximately 3% of all cardiac myxomas. Its presence can complicate the diagnostic process. A 43-year-old Saudi male was referred with a two-month history of progressively increasing shortness of breath. Cardiovascular examination demonstrated a soft first heart sound with a plopping sound in the mitral area and a mid-diastolic murmur. A transthoracic echocardiogram revealed a large mass attached to the interatrial septum. A diagnosis of cardiac myxoma was made, and the patient underwent en bloc resection of the mass. Microscopic evaluation of the resected mass showed a neoplastic lesion with two components: first, a typical myxoma consisting of stellate and spindle cells in a myxomatous/hemorrhagic background; second, a glandular component consisting of separate, fused, and cribriform acini embedded within the myxomatous component. The acini were lined by a single row of columnar epithelial cells with basal nuclei and apical mucin. Occasional goblet cells were also identified. The postoperative period was uneventful, and on his recent follow-up in the clinic (nine months after the surgery), the patient is doing well with no complications. Herein, we emphasize the importance of accurately diagnosing such an entity, as it can be easily confused for a metastatic adenocarcinoma, especially in patients with a history of malignancy.

A 37-Year-Old Saudi Man with a Calcified Intraventricular Astrocytoma.

BACKGROUND Pilocytic astrocytoma is a low-grade glioma that is common in children. Pilocytic astrocytoma is a slow-growing neoplasm that may calcify and occurs throughout the central nervous system, but it has a preference to be located infratentorial in children. CASE REPORT Herein, we report an unusual intraventricular location of pilocytic astrocytoma with extensive calcification in a 37-year-old Saudi man who mainly presented with a headache. Although pilocytic astrocytoma can arise throughout the central nervous system, it very rarely arises from the ventricles, especially the lateral ventricle. CONCLUSIONS The majority of intraventricular tumors arise within the third and fourth ventricles. The unusual intraventricular location and the unexpected age group are the main difficulties in diagnosing an adult with intraventricular pilocytic astrocytoma. Intraventricular pilocytic astrocytoma can be missed radiologically and misled pathologically; therefore, it should be considered within the differential diagnosis of intraventricular tumors. To the best of our knowledge, this is the first case to be reported in Saudi Arabia.

Gliosarcoma case report and review of the literature.

Gliosarcoma is an unusual subtype of glioblastoma multiforme. Its characteristic features are biphasic configuration, constituting a definite, separate glial and sarcomatous differentiation, on histological evaluation. Herein, we present a rare case of Gliosarcoma that had presented only once in our center in last 13 years. A 60 years old, diabetic, hypertensive male patient came to e emergency department with disturbed level of consciousness and right sided hemiplegia which was progressive over four days. On examination he was, conscious, unoriented in time, person or place, his mouth deviated to left and vitally stable. After initial evaluation, CT scan and MRI were advised. These showed a complex left parieto-occipital heterogeneous mass lesion with cystic and solid components, measuring approximately 5.2x4cm. The mass lesion was seen displacing the occipital horn anteriorly and inferiorly with probable extension into the lateral ventricular cavity. There was no associated midline shift or definite herniation. The lesion was diagnosed as highly suggestive of brain tumor with a differential diagnosis of glioblastoma multiforme or ependymoma. Blood picture revealed a rapidly increasing level of anemia. Surgical intervention comprising left parieto-occipital craniotomy and near total resection of the tumor was carried out. On histopathological and immunohistochemical evaluation the diagnosis of GS was established. A plan of a combination of adjuvant chemotherapy and radiation was formulated that was however, declined by the family. On regular follow up, the patients clinical state rapidly deteriorated with persistence of seizures and requirement of repeated blood transfusions. The patient finally passed away after eighth months.