A cohort study among 402 patients with penile cancer in Maranhão, Northeast Brazil with the highest worldwide incidence.

OBJECTIVE: Maranhão State-Northeast Brazil-has the world's highest incidence of penile cancer. This study describes the epidemiological, histopathological and clinical profile of patients stricken across that Brazilian state. The study is aimed at providing new data on neoplasia. DATA DESCRIPTION: 402 men stricken with penile cancer were studied from January 2004 to December 2018. A retrospective stage was developed with collection of physical and electronic records. A prospective stage was performed with collection of clinical and epidemiological information through a questionnaire. The surgical material was looked into by a uropathologist, and the lesions were evaluated for macroscopic characteristics and various microscopic parameters. Three articles using this data have already been published.

Inflammatory lesions and brain tumors: is it possible to differentiate them based on texture features in magnetic resonance imaging?

BACKGROUND: Neuroimaging strategies are essential to locate, to elucidate the etiology, and to the follow up of brain disease patients. Magnetic resonance imaging (MRI) provides good cerebral soft-tissue contrast detection and diagnostic sensitivity. Inflammatory lesions and tumors are common brain diseases that may present a similar pattern of a cerebral ring enhancing lesion on MRI, and non-enhancing core (which may reflect cystic components or necrosis) leading to misdiagnosis. Texture analysis (TA) and machine learning approaches are computer-aided diagnostic tools that can be used to assist radiologists in such decisions. METHODS: In this study, we combined texture features with machine learning (ML) methods aiming to differentiate brain tumors from inflammatory lesions in magnetic resonance imaging. Retrospective examination of 67 patients, with a pattern of a cerebral ring enhancing lesion, 30 with inflammatory, and 37 with tumoral lesions were selected. Three different MRI sequences and textural features were extracted using gray level co-occurrence matrix and gray level run length. All diagnoses were confirmed by histopathology, laboratorial analysis or MRI. RESULTS: The features extracted were processed for the application of ML methods that performed the classification. T1-weighted images proved to be the best sequence for classification, in which the differentiation between inflammatory and tumoral lesions presented high accuracy (0.827), area under ROC curve (0.906), precision (0.837), and recall (0.912). CONCLUSION: The algorithm obtained textures capable of differentiating brain tumors from inflammatory lesions, on T1-weghted images without contrast medium using the Random Forest machine learning classifier.

Profile of patients with penile cancer in the region with the highest worldwide incidence.

To determine the epidemiological, histopathological, and clinical characteristics of patients diagnosed with penile cancer in the Brazilian state of Maranhão, the region with the highest incidence worldwide. One hundred and sixteen penile cancer patients were interviewed from July 2016 to October 2018. The majority of patients lived in a rural area (57%), worked in farming (58%), had a low level of schooling or no schooling (90%), and were married or in a stable relationship (74%). The mean age was 60.4 ± 16.51 years (range, 23-93 years). Phimosis (66%), poor/moderate genital hygiene (73%), history of sexually transmitted infections (55%), and zoophilia (60%) were found in the majority of patients. Most patients had their first sexual encounter at 16.2 ± 2.8 years (range, 10-25 years), and 75% had >6 sexual partners. The most common initial symptom was pruritus (37%), and most patients waited to seek treatment (average time to treatment, 18.9 months; range, 2-84 months). Human papillomavirus (HPV)-related histologies were observed in 62% of patients. Most patients had histological grades II or III (87%), stage ≥T2 disease (84%), and lymphadenopathy at admission (42%). Penectomy was performed in 96% of patients. The population with penile cancer in the region of highest incidence in the world is marked by low socioeconomic status, high prevalence of HPV infection, and phimosis. The delay in seeking treatment is related to a very high rate of advanced cancer and aggressive surgical treatment. The high prevalence of young patients was also a striking feature.

Inflammatory lesions and brain tumors: is it possible to differentiate them based on texture features in magnetic resonance imaging?

Neuroimaging strategies are essential to locate, to elucidate the etiology, and to the follow up of brain disease patients. Magnetic resonance imaging (MRI) provides good cerebral soft-tissue contrast detection and diagnostic sensitivity. Inflammatory lesions and tumors are common brain diseases that may present a similar pattern of a cerebral ring enhancing lesion on MRI, and non-enhancing core (which may reflect cystic components or necrosis) leading to misdiagnosis. Texture analysis (TA) and machine learning approaches are computer-aided diagnostic tools that can be used to assist radiologists in such decisions. Methods: In this study, we combined texture features with machine learning (ML) methods aiming to differentiate brain tumors from inflammatory lesions in magnetic resonance imaging. Retrospective examination of 67 patients, with a pattern of a cerebral ring enhancing lesion, 30 with inflammatory, and 37 with tumoral lesions were selected. Three different MRI sequences and textural features were extracted using gray level co-occurrence matrix and gray level run length. All diagnoses were confirmed by histopathology, laboratorial analysis or MRI. Results: The features extracted were processed for the application of ML methods that performed the classification. T1-weighted images proved to be the best sequence for classification, in which the differentiation between inflammatory and tumoral lesions presented high accuracy (0.827), area under ROC curve (0.906), precision (0.837), and recall (0.912). Conclusion: The algorithm obtained textures capable of differentiating brain tumors from inflammatory lesions, on T1-weghted images without contrast medium using the Random Forest machine learning classifier.(AU)

Penile cancer in Maranhão, Northeast Brazil: the highest incidence globally?

BACKGROUND: The objectives of this study were to determine the minimum incidence of penile cancer in the poorest Brazilian state, and to describe the epidemiologic and clinical characteristics of patients diagnosed with the disease. METHODS: A retrospective study of 392 patients diagnosed with penile cancer in the three most important referral center in the state was conducted during 2004-2014. RESULTS: The age-standardized incidence was 6.15 per 100,000 and the crude annual incidence was 1.18 per 100,000. More than half (61.1%) of the tumors were histological grades 2 and 3, and 66.4% of tumors were classified as at least stage T2. The average age of patients was 58.6 ± 15.7 years (range, 18 to 103 years), with 20.8% of patients ≤40 years of age at diagnosis. The vast majority underwent penectomy (93%). Only 41.8% underwent lymphadenectomy, 58 patients (14.8%) received chemotherapy, and 54 patients (13.8%) received radiotherapy. Stage 3/4 and vascular invasion were statically significant at disease-free survival analysis. CONCLUSION: The state of Maranhão has the highest incidence of penile cancer in Brazil and globally. Tumors are locally advanced and at the time of diagnosis, and there is a high frequency among young individuals. Patients have a low socioeconomic status, making it difficult to complete treatment and receive appropriate follow-up.

Rhinosporidiosis: the largest case series in Brazil.

INTRODUCTION: Rhinosporidiosis is a chronic infection of the mucous membrane and is caused by Rhinosporidium seeberi, an aquatic mesomycetozoan. The mode of infection is probably transepithelial penetration. The large number of rivers and lakes and the strong presence of riparian populations in the State of Maranhão are strong predisposing factors for rhinosporidiosis. METHODS: A 5-year retrospective study was conducted in a tertiary medical center situated in Maranhão, Northeast Brazil. Twenty-five Maranhense patients diagnosed with rhinosporidiosis were analyzed. RESULTS: Most of the patients were children, adolescents and young adults (age range: 7-24 years, mean age: 14 years). The majority of the participants were male (84%), brown (76%), and students (92%). All lesions involved the entire nasal cavity and presented with a vascular polypoid mass. All patients were treated by surgical excision of the lesions. CONCLUSIONS: Rhinosporidiosis affects younger age groups, especially students from the countryside and the outskirts of urban areas. This study will aid and guide physicians in diagnosing and treating this infection in endemic areas.

Rhinosporidiosis: the largest case series in Brazil

Abstract: INTRODUCTION: Rhinosporidiosis is a chronic infection of the mucous membrane and is caused by Rhinosporidium seeberi, an aquatic mesomycetozoan. The mode of infection is probably transepithelial penetration. The large number of rivers and lakes and the strong presence of riparian populations in the State of Maranhão are strong predisposing factors for rhinosporidiosis. METHODS: A 5-year retrospective study was conducted in a tertiary medical center situated in Maranhão, Northeast Brazil. Twenty-five Maranhense patients diagnosed with rhinosporidiosis were analyzed. RESULTS: Most of the patients were children, adolescents and young adults (age range: 7-24 years, mean age: 14 years). The majority of the participants were male (84%), brown (76%), and students (92%). All lesions involved the entire nasal cavity and presented with a vascular polypoid mass. All patients were treated by surgical excision of the lesions. CONCLUSIONS: Rhinosporidiosis affects younger age groups, especially students from the countryside and the outskirts of urban areas. This study will aid and guide physicians in diagnosing and treating this infection in endemic areas.