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Introduction. The identification of mitotic figures is essential for the diagnosis, grading, and classification of various different tumors. Despite its importance, there is a paucity of literature reporting the consistency in interpreting mitotic figures among pathologists. This study leverages publicly accessible datasets and social media to recruit an international group of pathologists to score an image database of more than 1000 mitotic figures collectively. Materials and Methods. Pathologists were instructed to randomly select a digital slide from The Cancer Genome Atlas (TCGA) datasets and annotate 10-20 mitotic figures within a 2 mm 2 area. The first 1010 submitted mitotic figures were used to create an image dataset, with each figure transformed into an individual tile at 40x magnification. The dataset was redistributed to all pathologists to review and determine whether each tile constituted a mitotic figure. Results. Overall pathologists had a median agreement rate of 80.2% (range 42.0%-95.7%). Individual mitotic figure tiles had a median agreement rate of 87.1% and a fair inter-rater agreement across all tiles (kappa = 0.284). Mitotic figures in prometaphase had lower percentage agreement rates compared to other phases of mitosis. Conclusion. This dataset stands as the largest international consensus study for mitotic figures to date and can be utilized as a training set for future studies. The agreement range reflects a spectrum of criteria that pathologists use to decide what constitutes a mitotic figure, which may have potential implications in tumor diagnostics and clinical management., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Introduction: Cancers are a major cause of childhood mortality worldwide especially in LMICs where underdiagnoses and lack of quality cancer data hampers effective cancer control efforts. This study aimed to document and describe the patterns and characteristics of childhood cancers in the North East geopolitical zone of Nigeria., Methods: This was a retrospective cross-sectional study that collected cancer data from 4 out of the 6 states in the North East of Nigeria. The data included all malignancies diagnosed in children aged 0-19 years between 2019 and 2022. The age-specific incidence rates were also calculated for the individual 5-year age groups (0-4 years, 5-9 years, 10-14 years, and 15-19 years). The crude incidence rates (CIR) were calculated as the weighted averages of the respective ASRs in each age range within 0-14 years and 0-19 years respectively. The cancers were grouped according to the International Incidence of Childhood Cancers, volume 3 (IICC3)., Results: Cancers in people <20 years accounted for 7.3% of all cancers diagnosed over the same period. The crude incidence rates (CIR) for cancers in children and adolescents were 20.9 per million children aged 0-19 years and 18.8 per million children aged 0-14 years respectively, while the age-standardized rates (ASR) were 1.80 and 1.63 per million person-years respectively. There was a variation in the most commonly diagnosed cancers across all age groups. However, lymphomas were the most commonly diagnosed cancers overall, while CNS tumors were overwhelmingly rare., Conclusion: Despite data limitations, this study provides useful insights into patterns of cancers in the region and will hopefully provide a basis for the strengthening of pediatric oncology care, childhood cancer control programs and population-based cancer registries., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Suleiman, Adamu, Ezenkwa, Yusuf, Lawan, Dachi, Bwala, Liman, Kabir, Adamu, Kolomi, Jimoh, Garba, Abdullahi and Audu.)

Background: The advancement in non-invasive methods for diagnosing and characterizing liver disease has achieved significant success. One such methods, FibroScan, combines non-invasiveness, rapidity, painlessness, and reproducibility. However, its accuracy and value are limited in many clinical settings. The liver biopsy, the gold standard for assessing liver fibrosis offers direct visualization and provides extensive information through histology and ancillary investigations a noticeable gap of Fibroscan and other non-invasive methods., Aim and Objective: To determine the rate of histology requests by gastroenterologists and surgeons at the Jos University Teaching Hospital during the pre-FibroScan era and the FibroScan era in the Jos metropolis., Methodology: Patient biodemographic information and histologic diagnoses, along with the category of the requesting physician (gastroenterologist or surgeon) for liver biopsies, were extracted from hospital records. Data were collated for the pre-FibroScan era (2004-2010) and the FibroScan era (2011-2023), spanning 20 years. All patients with liver biopsies submitted for histologic analyses were included while those with inadequate biodemographic data, histologic diagnoses, and category of requesting physician were excluded., Results: Two hundred and eighteen (218) liver biopsies were received during the study of the period. Of these, two hundred and eight (95.4%) met the study criteria, with 111 (53.4%) from the pre-FibroScan era and 97 (46.6%) from the FibroScan era. In the pre-Fibroscan era,110(99.09%) 1(0.01%) histology requested were by gastroenterologist and surgeons respectively, while in the Fibroscan era the respective requests by these specialties were 36(37.11%) and 97(62.89%). The first year of the Fibroscan era (2011) accounted for 22(61.11%) of the 36(100.00%) cases liver biopsies requested by gastroenterologist, with a corresponding value of 11(16.67%) of 66(100.00%) for surgeons. The significance concerning the requesting physician's specialty with p-value of 0.003., Conclusion: For the foreseeable future, the FibroScan cannot replace the value of direct tissue histological assessment, especially where molecular studies and other ancillary investigations are crucial for targeted therapy and research. Histology remains the gold standard for the aforementioned reasons and probably will until the non-invasive investigations can provide the myriads of valuable information it avails., Competing Interests: The Authors declare that no competing interest exists., (Copyright © 2024 by West African Journal of Medicine.)

Introduction: Sub-Saharan Africa (SSA) is plagued by myriads of diseases, mostly infectious; but cancer disease burden is rising among non-communicable diseases. Nigeria has a high burden of cancer, however its remote underserved culturally-conserved populations have been understudied, a gap this study sought to fill., Methods: This was a cross-sectional multi-institutional descriptive study of histologically diagnosed cancers over a four-year period (January 2019-December 2022) archived in the Departments of Pathology and Cancer Registries of six tertiary hospitals in the northeast of Nigeria. Data obtained included age at diagnosis, gender, tumor site and available cancer care infrastructure. Population data of the study region and its demographics was obtained from the National Population Commission and used to calculate incident rates for the population studied., Results: A total of 4,681 incident cancer cases from 2,770 females and 1,911 males were identified. The median age at diagnosis for females was 45 years (range 1-95yrs), and 56 years (range 1-99yrs) for males. Observed age-specific incidence rates (ASR) increased steadily for both genders reaching peaks in the age group 80 years and above with the highest ASR seen among males (321/100,000 persons) compared to females (215.5/100,000 persons). Breast, cervical, prostatic, colorectal and skin cancers were the five most common incident cancers. In females, breast, cervical, skin, ovarian and colorectal cancers were the top five malignancies; while prostate, haematolymphoid, skin, colorectal and urinary bladder cancers predominated in men., Conclusion: Remote SSA communities are witnessing rising cancer disease burden. Proactive control programs inclusive of advocacy, vaccination, screening, and improved diagnostics are needed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Ezenkwa, Lawan, Garbati, Suleiman, Katagum, Kabir, Adamu, Modu, Olanrewaju, Dachi, Abdullahi, Alkali, Bojude, Usman, Omotoso, Schlumbrecht, George and Audu.)

Background: Ocular surface squamous neoplasia (OSSN) is a heterogeneous group of proliferative squamous lesions on the ocular surface with varying biologic behaviours. This study aims to report the clinical profile and pathological characteristics of cases of OSSN seen at a tertiary referral centre in North West Nigeria., Methods: A retrospective review of all cases of OSSN diagnosed over a 10-year period was done., Results: OSSN accounted for 68 out of 91 ocular surface lesions affecting twice as many males as females and a peak incidence in the 30-39 years age group. They frequently presented as higher-grade and higher-stage lesions with invasive squamous cell carcinoma being the most frequently diagnosed OSSN. They also frequently showed an association with HIV infection and a relatively long duration of symptoms before presentation., Conclusion: OSSN occurs in a relatively young age group in our environment. Certain clinical and epidemiological features appear to predict the occurrence of higher-grade lesions, and this may help in the clinical prediction of likely pathologic grade and/or biologic behaviour of these lesions., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)

Objective: Ovarian cancer in Black women is common in many West African countries but is relatively rare in North America. Black women have worse survival outcomes when compared to White women. Ovarian cancer histotype, diagnosis, and age at presentation are known prognostic factors for outcome. We sought to conduct a preliminary comparative assessment of these factors across the African diaspora., Methods: Patients diagnosed with ovarian cancer (all histologies) between June 2016-December 2019 in Departments of Pathology at 25 participating sites in Nigeria were identified. Comparative population-based data, inclusive of Caribbean-born Blacks (CBB) and US-born Blacks (USB), were additionally captured from the International Agency for Research on Cancer and Florida Cancer Data Systems. Histology, country of birth, and age at diagnosis data were collected and evaluated across the three subgroups: USB, CBB and Nigerians. Statistical analyses were done using chi-square and student's t-test with significance set at p<0.05., Results: Nigerians had the highest proportion of germ cell tumor (GCT, 11.5%) and sex-cord stromal (SCST, 16.2%) ovarian cancers relative to CBB and USB (p=0.001). CBB (79.4%) and USB (77.3%) women were diagnosed with a larger proportion of serous ovarian cancer than Nigerians (60.4%) (p<0.0001). Nigerians were diagnosed with epithelial ovarian cancers at the youngest age (51.7± 12.8 years) relative to USB (58.9 ± 15.0) and CBB (59.0± 13.0,p<0.001). Black women [CBB (25.2 ± 15.0), Nigerians (29.5 ± 15.1), and USB (33.9 ± 17.9)] were diagnosed with GCT younger than White women (35.4 ± 20.5, p=0.011). Black women [Nigerians (47.5 ± 15.9), USB (50.9 ± 18.3) and CBB (50.9 ± 18.3)] were also diagnosed with SCST younger than White women (55.6 ± 16.5, p<0.01)., Conclusion: There is significant variation in age of diagnosis and distribution of ovarian cancer histotype/diagnosis across the African diaspora. The etiology of these findings requires further investigation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 George, Omotoso, Pinto, Mustapha, Sanchez-Covarrubias, Umar, Umar, Oluwasola, Okolo, Anthony, Ukekwe, Bakari, Dahiru, Abdullahi, Abimiku, Abdurrahman, Usman, Ahmed, Usman, Kabir, Eleje, Chiemeka, Nzeribe, Nweke, Kadas, Suleiman, Ekanem, Uche, Paul, Agwu, Edegbe, Anorlu, Banjo, Ajenifuja, Fawole, Kazeem, Magaji, Silas, Athanasius, Tamunomie, Bassey, Abudu, Ango, Abdullahi, Lawal, Kabir, Ekanem, Ezeanochie, Yahaya, Castillo, Bahall, Chatrani, Brambury, Bowe, Halliday, Bruney, Butler, Ragin, Odedina, Chamala, Schlumbrecht and Audu.)

Pathologists are responsible for rapidly providing a diagnosis on critical health issues. Challenging cases benefit from additional opinions of pathologist colleagues. In addition to on-site colleagues, there is an active worldwide community of pathologists on social media for complementary opinions. Such access to pathologists worldwide has the capacity to improve diagnostic accuracy and generate broader consensus on next steps in patient care. From Twitter we curate 13,626 images from 6,351 tweets from 25 pathologists from 13 countries. We supplement the Twitter data with 113,161 images from 1,074,484 PubMed articles. We develop machine learning and deep learning models to (i) accurately identify histopathology stains, (ii) discriminate between tissues, and (iii) differentiate disease states. Area Under Receiver Operating Characteristic (AUROC) is 0.805-0.996 for these tasks. We repurpose the disease classifier to search for similar disease states given an image and clinical covariates. We report precision@k = 1 = 0.7618 ± 0.0018 (chance 0.397 ± 0.004, mean ±stdev ). The classifiers find that texture and tissue are important clinico-visual features of disease. Deep features trained only on natural images (e.g., cats and dogs) substantially improved search performance, while pathology-specific deep features and cell nuclei features further improved search to a lesser extent. We implement a social media bot (@pathobot on Twitter) to use the trained classifiers to aid pathologists in obtaining real-time feedback on challenging cases. If a social media post containing pathology text and images mentions the bot, the bot generates quantitative predictions of disease state (normal/artifact/infection/injury/nontumor, preneoplastic/benign/low-grade-malignant-potential, or malignant) and lists similar cases across social media and PubMed. Our project has become a globally distributed expert system that facilitates pathological diagnosis and brings expertise to underserved regions or hospitals with less expertise in a particular disease. This is the first pan-tissue pan-disease (i.e., from infection to malignancy) method for prediction and search on social media, and the first pathology study prospectively tested in public on social media. We will share data through http://pathobotology.org . We expect our project to cultivate a more connected world of physicians and improve patient care worldwide.