JOAO MANOEL MIRANDA MAGALHAES SANTOS
Índice h a partir de 2011
6
Projetos de Pesquisa
Unidades Organizacionais
LIM/65, Hospital das Clínicas, Faculdade de Medicina
4 resultados
Resultados de Busca
Agora exibindo 1 - 4 de 4
- MRI-based radiomic score increased mrTRG accuracy in predicting rectal cancer response to neoadjuvant therapy(2023) MIRANDA, Joao; HORVAT, Natally; ASSUNCAO JR., Antonildes N.; MACHADO, Felipe Augusto de M.; CHAKRABORTY, Jayasree; PANDINI, Rafael Vaz; SARAIVA, Samya; NAHAS, Caio Sergio Rizkallah; NAHAS, Sergio Carlos; NOMURA, Cesar HigaPurpose To develop a magnetic resonance imaging (MRI)-based radiomics score, i.e., ""rad-score,"" and to investigate the performance of rad-score alone and combined with mrTRG in predicting pathologic complete response (pCR) in patients with locally advanced rectal cancer following neoadjuvant chemoradiation therapy. Methods This retrospective study included consecutive patients with LARC who underwent neoadjuvant chemoradiotherapy followed by surgery from between July 2011 to November 2015. Volumes of interest of the entire tumor on baseline rectal MRI and of the tumor bed on restaging rectal MRI were manually segmented on T2-weighted images. The radiologist also provided the ymrTRG score on the restaging MRI. Radiomic score (rad-score) was calculated and optimal cut-off points for both mrTRG and rad-score to predict pCR were selected using Youden's J statistic. Results Of 180 patients (mean age = 63 years; 60% men), 33/180 (18%) achieved pCR. High rad-score (> - 1.49) yielded an area under the curve (AUC) of 0.758, comparable to ymrTRG 1-2 which yielded an AUC of 0.759. The combination of high rad-score and ymrTRG 1-2 yielded a significantly higher AUC of 0.836 compared with ymrTRG 1-2 and high rad-score alone (p < 0.001). A logistic regression model incorporating both high rad-score and mrTRG 1-2 was built to calculate adjusted odds ratios for pCR, which was 4.85 (p < 0.001). Conclusion Our study demonstrates that a rectal restaging MRI-based rad-score had comparable diagnostic performance to ymrTRG. Moreover, the combined rad-score and ymrTRG model yielded a significant better diagnostic performance for predicting pCR.
- Rectal MRI radiomics for predicting pathological complete response: Where we are(2022) MIRANDA, Joao; TAN, Gary Xia Vern; FERNANDES, Maria Clara; YILDIRIM, Onur; SIMS, John A.; ARAUJO-FILHO, Jose De Arimateia Batista; MACHADO, Felipe Augusto de M.; ASSUNCAO-JR, Antonildes N.; NOMURA, Cesar Higa; HORVAT, NatallyRadiomics using rectal MRI radiomics has emerged as a promising approach in predicting pathological complete response. In this study, we present a typical pipeline of a radiomics analysis and review recent studies, exploring applications, development of radiomics methodologies and model construction in pCR prediction. Finally, we will offer our opinion about the future and discuss the next steps of rectal MRI radiomics for predicting pCR.
- Abdominal gastrointestinal imaging findings on computed tomography in patients with COVID-19 and correlation with clinical outcomes(2021) HORVAT, Natally; PINTO, Paulo Victor Alves; ARAUJO-FILHO, Jose De Arimateia Batista; SANTOS, Joao Manoel Miranda Magalhaes; DIAS, Adriano Basso; MIRANDA, Julia Azevedo; OLIVEIRA, Camila Vilela de; BARBOSA, Camila Silva; MORAIS, Thamara Carvalho; ASSUNCAO-JR, Antonildes N.; NOMURA, Cesar Higa; VIANA, Publio Cesar CavalcantePurpose: Pulmonary imaging finding of Coronavirus disease 2019 (COVID-19) has been widely described, but until now few studies have been published about abdominal radiological presentation. The aim of this study was to provide an overview of abdominal imaging findings in patients with COVID-19 in a multicenter study and correlate them with worse clinical outcomes. Materials and methods: This retrospective study included adult COVID-positive patients with abdominal CT performed from 4/1/2020 to 5/1/2020 from two institutions. Demographic, laboratory and clinical data were recorded, including clinical outcomes. Results: Of 81 COVID-positive patients, the average age was 61 years, 42 (52%) women and 45 (55%) had positive abdominopelvic findings. The most common abdominal imaging features were intestinal imaging findings (20/81, 24%), including colorectal (4/81, 5%) and small bowel thickening (10/81, 12%), intestinal distension (15/81, 18%), pneumatosis (1/81, 1%) and intestinal perforation (1/81, 1%). On multivariate analysis, intestinal imaging findings were associated with higher risk of worse outcome (death or invasive mechanical ventilation) (RR = 2.6, p = 0.04) and higher risk of invasive mechanical ventilation alone (RR = 6.2, p = 0.05). Conclusion: Intestinal abnormalities were common findings in COVID-19 patients who underwent abdominal CT and were significantly correlated to worse outcomes in the clinical follow-up.
- Current status and future perspectives of radiomics in hepatocellular carcinoma(2023) MIRANDA, Joao; HORVAT, Natally; FONSECA, Gilton Marques; ARAUJO-FILHO, Jose de Arimateia Batista; FERNANDES, Maria Clara; CHARBEL, Charlotte; CHAKRABORTY, Jayasree; COELHO, Fabricio Ferreira; NOMURA, Cesar Higa; HERMAN, PauloGiven the frequent co-existence of an aggressive tumor and underlying chronic liver disease, the management of hepatocellular carcinoma (HCC) patients requires experienced multidisciplinary team discussion. Moreover, imaging plays a key role in the diagnosis, staging, restaging, and surveillance of HCC. Currently, imaging assessment of HCC entails the assessment of qualitative characteristics which are prone to inter-reader variability. Radiomics is an emerging field that extracts high-dimensional mineable quantitative features that cannot be assessed visually with the naked eye from medical imaging. The main potential applications of radiomic models in HCC are to predict histology, response to treatment, genetic signature, recurrence, and survival. Despite the encouraging results to date, there are challenges and limitations that need to be overcome before radiomics implementation in clinical practice. The purpose of this article is to review the main concepts and challenges pertaining to radiomics, and to review recent studies and potential applications of radiomics in HCC.