RODRIGO CARUSO CHATE
Índice h a partir de 2011
7
Projetos de Pesquisa
Unidades Organizacionais
Instituto do Coração, Hospital das Clínicas, Faculdade de Medicina - Médico
LIM/65, Hospital das Clínicas, Faculdade de Medicina
LIM/65, Hospital das Clínicas, Faculdade de Medicina
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- Computed tomography in hypersensitivity pneumonitis: main findings, differential diagnosis and pitfalls(2018) DIAS, Olivia Meira; BALDI, Bruno Guedes; PENNATI, Francesca; ALIVERTI, Andrea; CHATE, Rodrigo Caruso; SAWAMURA, Marcio Valente Yamada; CARVALHO, Carlos Roberto Ribeiro de; ALBUQUERQUE, Andre Luis Pereira deIntroduction: Hypersensitivity pneumonitis (HP) is a disease with variable clinical presentation in which inflammation in the lung parenchyma is caused by the inhalation of specific organic antigens or low molecular weight substances in genetically susceptible individuals. Alterations of the acute, subacute and chronic forms may eventually overlap, and the diagnosis based on temporality and presence of fibrosis (acute/inflammatory HP vs. chronic HP) seems to be more feasible and useful in clinical practice. Differential diagnosis of chronic HP with other interstitial fibrotic diseases is challenging due to the overlap of the clinical history, and the functional and imaging findings of these pathologies in the terminal stages.Areas covered: This article reviews the essential features of HP with emphasis on imaging features. Moreover, the main methodological limitations of high-resolution computed tomography (HRCT) interpretation are discussed, as well as new perspectives with volumetric quantitative CT analysis as a useful tool for retrieving detailed and accurate information from the lung parenchyma.Expert commentary: Mosaic attenuation is a prominent feature of this disease, but air trapping in chronic HP seems overestimated. Quantitative analysis has the potential to estimate the involvement of the pulmonary parenchyma more accurately and could correlate better with pulmonary function results.
- Texture-based classification of lung disease patterns in chronic hypersensitivity pneumonitis and comparison to clinical outcomes(2021) PENNATI, F.; ALIBONI, L.; ANTONIAZZA, A.; BERETTA, D.; DIAS, O.; BALDI, B. G.; SAWAMURA, M.; CHATE, R. C.; CARVALHO, C. R. R. De; ALBUQUERQUE, A.; ALIVERTI, A.Computer-aided detection algorithms applied to CT lung imaging have the potential to objectively quantify pulmonary pathology. We aim to develop an automatic classification method based on textural features able to classify healthy and pathological patterns on CT lung images and to quantify the extent of each disease pattern in a group of patients with chronic hypersensitivity pneumonitis (cHP), in comparison to pulmonary function tests (PFTs). 27 cHP patients were scanned via high resolution CT (HRCT) at full-inspiration. Regions of interest (ROIs) were extracted and labeled as normal (NOR), ground glass opacity (GGO), reticulation (RET), consolidation (C), honeycombing (HB) and air trapping (AT). For each ROI, statistical, morphological and fractal parameters were computed. For automatic classification, we compared two classification methods (Bayesian and Support Vector Machine) and three ROI sizes. The classifier was therefore applied to the overall CT images and the extent of each class was calculated and compared to PFTs. Better classification accuracy was found for the Bayesian classifier and the 16x16 ROI size: 92.1 +/- 2.7%. The extent of GGO, HB and NOR significantly correlated with forced vital capacity (FVC) and the extent of NOR with carbon monoxide diffusing capacity (DLCO).
- A textural approach for quantitative CT in chronic hypersensitivity pneumonitis (cHP)(2019) PENNATI, Francesca; DIAS, Olivia; ANTONIAZZA, Alessio; BERETTA, Davide; ALIBONI, Lorenzo; BALDI, Bruno Guedes; SAWAMURA, Marcio; CHATE, Rodrigo Caruso; CARVALHO, Carlos Roberto Ribeiro De; ALBUQUERQUE, Andre; ALIVERTI, Andrea
- Chronic lung lesions in COVID-19 survivors: predictive clinical model(2022) CARVALHO, Carlos Roberto Ribeiro; CHATE, Rodrigo Caruso; SAWAMURA, Marcio Valente Yamada; GARCIA, Michelle Louvaes; LAMAS, Celina Almeida; CARDENAS, Diego Armando Cardona; LIMA, Daniel Mario; SCUDELLER, Paula Gobi; SALGE, Joao Marcos; NOMURA, Cesar Higa; GUTIERREZ, Marco AntonioObjective This study aimed to propose a simple, accessible and low-cost predictive clinical model to detect lung lesions due to COVID-19 infection. Design This prospective cohort study included COVID-19 survivors hospitalised between 30 March 2020 and 31 August 2020 followed-up 6 months after hospital discharge. The pulmonary function was assessed using the modified Medical Research Council (mMRC) dyspnoea scale, oximetry (SpO(2)), spirometry (forced vital capacity (FVC)) and chest X-ray (CXR) during an in-person consultation. Patients with abnormalities in at least one of these parameters underwent chest CT. mMRC scale, SpO(2), FVC and CXR findings were used to build a machine learning model for lung lesion detection on CT. Setting A tertiary hospital in Sao Paulo, Brazil. Participants 749 eligible RT-PCR-confirmed SARS-CoV-2-infected patients aged >= 18 years. Primary outcome measure A predictive clinical model for lung lesion detection on chest CT. Results There were 470 patients (63%) that had at least one sign of pulmonary involvement and were eligible for CT. Almost half of them (48%) had significant pulmonary abnormalities, including ground-glass opacities, parenchymal bands, reticulation, traction bronchiectasis and architectural distortion. The machine learning model, including the results of 257 patients with complete data on mMRC, SpO(2), FVC, CXR and CT, accurately detected pulmonary lesions by the joint data of CXR, mMRC scale, SpO(2) and FVC (sensitivity, 0.85 +/- 0.08; specificity, 0.70 +/- 0.06; F1-score, 0.79 +/- 0.06 and area under the curve, 0.80 +/- 0.07). Conclusion A predictive clinical model based on CXR, mMRC, oximetry and spirometry data can accurately screen patients with lung lesions after SARS-CoV-2 infection. Given that these examinations are highly accessible and low cost, this protocol can be automated and implemented in different countries for early detection of COVID-19 sequelae.
- Long-term respiratory follow-up of ICU hospitalized COVID-19 patients: Prospective cohort study(2023) CARVALHO, Carlos Roberto Ribeiro; LAMAS, Celina Almeida; CHATE, Rodrigo Caruso; SALGE, Joao Marcos; SAWAMURA, Marcio Valente Yamada; ALBUQUERQUE, Andre L. P. de; JR, Carlos Toufen; LIMA, Daniel Mario; GARCIA, Michelle Louvaes; SCUDELLER, Paula Gobi; NOMURA, Cesar Higa; GUTIERREZ, Marco Antonio; BALDI, Bruno GuedesBackgroundCoronavirus disease (COVID-19) survivors exhibit multisystemic alterations after hospitalization. Little is known about long-term imaging and pulmonary function of hospitalized patients intensive care unit (ICU) who survive COVID-19. We aimed to investigate long-term consequences of COVID-19 on the respiratory system of patients discharged from hospital ICU and identify risk factors associated with chest computed tomography (CT) lesion severity. MethodsA prospective cohort study of COVID-19 patients admitted to a tertiary hospital ICU in Brazil (March-August/2020), and followed-up six-twelve months after hospital admission. Initial assessment included: modified Medical Research Council dyspnea scale, SpO(2) evaluation, forced vital capacity, and chest X-Ray. Patients with alterations in at least one of these examinations were eligible for CT and pulmonary function tests (PFTs) approximately 16 months after hospital admission. Primary outcome: CT lesion severity (fibrotic-like or non-fibrotic-like). Baseline clinical variables were used to build a machine learning model (ML) to predict the severity of CT lesion. ResultsIn total, 326 patients (72%) were eligible for CT and PFTs. COVID-19 CT lesions were identified in 81.8% of patients, and half of them showed mild restrictive lung impairment and impaired lung diffusion capacity. Patients with COVID-19 CT findings were stratified into two categories of lesion severity: non-fibrotic-like (50.8%-ground-glass opacities/reticulations) and fibrotic-like (49.2%-traction bronchiectasis/architectural distortion). No association between CT feature severity and altered lung diffusion or functional restrictive/obstructive patterns was found. The ML detected that male sex, ICU and invasive mechanic ventilation (IMV) period, tracheostomy and vasoactive drug need during hospitalization were predictors of CT lesion severity(sensitivity,0.78 +/- 0.02;specificity,0.79 +/- 0.01;F1-score,0.78 +/- 0.02;positive predictive rate,0.78 +/- 0.02; accuracy,0.78 +/- 0.02; and area under the curve,0.83 +/- 0.01). ConclusionICU hospitalization due to COVID-19 led to respiratory system alterations six-twelve months after hospital admission. Male sex and critical disease acute phase, characterized by a longer ICU and IMV period, and need for tracheostomy and vasoactive drugs, were risk factors for severe CT lesions six-twelve months after hospital admission.
- Forced Oscillation Technique and Small Airway Involvement in Chronic Hypersensitivity Pneumonitis(2019) DIAS, Olivia Meira; BALDI, Bruno Guedes; CHATE, Rodrigo Caruso; CARVALHO, Carlos Roberto Ribeiro de; DELLACA, Raffaele L.; MILESI, Ilaria; ALBUQUERQUE, Andre Luis Pereira deObjective: Hypersensitivity pneumonitis (HP) is an interstitial lung disease caused by the inhalation of specific organic antigens or low-molecular weight substances in genetically susceptible individuals. Although small airway involvement is prominent in patients with chronic HP, conventional pulmonary function tests (PFTs) are relatively insensitive to identify it. Thus, the authors aimed to evaluate resistance (R5) and reactance (X5) values at 5 Hz on inspiration, expiration, and whole breath, as well as small airway resistance (R5-19) values using a forced oscillation technique (FOT) in patients with chronic HP, and their responses after bronchodilator. In addition, R5 and X5 values according to the presence or absence of mosaic attenuation on computed tomography (CT) were compared. Methods: PFTs with plethysmography, diffusing capacity of the lungs for carbon monoxide (DLco) and FOT measurements were performed pre-bronchodilator and post-bronchodilator. High-resolution CT was performed at the same visit, and classified according to the presence or absence of mosaic attenuation. R5 and X5 values were then compared according to the presence or absence of mosaic attenuation on CT. Results: Twenty-eight patients with chronic HP (57.1% female; mean age, 56 +/- 11.5 years; mean forced vital capacity 57 +/- 17% predicted) were evaluated. All patients had low X5 values, reflecting lower lung compliance, and only three (8%) demonstrated elevated R5 (whole-breath) values. No patients exhibited bronchodilator response in R5, X5 and R5_19 values. In patients who exhibited greater extension of mosaic attenuation (n =11), R5 and X5 values could not discriminate those with a greater presence of these areas on CT. Conclusions: The results suggest that FOT does not help to additionally characterise concomitant small airway involvement in patients with chronic fibrotic HP who demonstrate restrictive ventilatory pattern in conventional PFTs. Nevertheless, FOT appeared to better characterise decreased lung compliance due to fibrosis through X5. Bronchodilator therapy did not appear to induce an acute response in chronic HP patients with restrictive disease. The precise role of FOT in subacute HP and obstructive chronic HP, therefore, must be evaluated.
- Quantitative CT Analysis in Chronic Hypersensitivity Pneumonitis: A Convolutional Neural Network Approach(2022) ALIBONI, Lorenzo; DIAS, Olivia Meira; PENNATI, Francesca; BALDI, Bruno Guedes; SAWAMURA, Marcio Valente Yamada; CHATE, Rodrigo Caruso; CARVALHO, Carlos Roberto Ribeiro; ALBUQUERQUE, Andre Luis Pereira de; ALIVERTI, AndreaRationale and Objectives: Chronic hypersensitivity pneumonitis (cHP) is a heterogeneous condition, where both small airway involvement and fibrosis may simultaneously occur. Computer-aided analysis of CT lung imaging is increasingly used to improve tissue characterization in interstitial lung diseases (ILD), quantifying disease extension, and progression. We aimed to quantify via a convolutional neural network (CNN) method the extent of different pathological classes in cHP, and to determine their correlation to pulmonary function tests (PFTs) and mosaic attenuation pattern. Materials and Methods: The extension of six textural features, including consolidation (C), ground glass opacity (GGO), fibrosis (F), low attenuation areas (LAA), reticulation (R) and healthy regions (H), was quantified in 27 cHP patients (age: 56 +/- 11.5 years, forced vital capacity [FVC]% = 57 +/- 17) acquired at full-inspiration via HRCT. Each class extent was correlated to PFTs and to mosaic attenuation pattern. Results: H showed a positive correlation with FVC%, FEV1% (forced expiratory volume), total lung capacity%, and diffusion of carbon monoxide (DLCO)% (r = 0.74, r = 0.78, r = 0.73, and r = 0.60, respectively, p < 0.001). GGO, R and C negatively correlated with FVC% and FEV1% with the highest correlations found for R (r = -0.44, and r = -0.46 respectively, p < 0.05); F negatively correlated with DLCO% (r = -0.42, p < 0.05). Patients with mosaic attenuation pattern had significantly more H (p = 0.04) and lower R (p = 0.02) and C (p = 0.0009) areas, and more preserved lung function indices (higher FVC%; p = 0.04 and DLCO%; p = 0.05), but did not show more air trapping in lung function tests. Conclusion: CNN quantification of pathological tissue extent in cHP improves its characterization and shows correlation with PFTs. LAA can be overestimated by visual, qualitative CT assessment and mosaic attenuation pattern areas in cHP represents patchy ILD rather than small-airways disease.
- A Convolutional Neural Network Approach to Quantify Lung Disease Progression in Patients with Fibrotic Hypersensitivity Pneumonitis (HP)(2022) ALIBONI, Lorenzo; DIAS, Olivia Meira; BALDI, Bruno Guedes; SAWAMURA, Marcio Valente Yamada; CHATE, Rodrigo Caruso; CARVALHO, Carlos Roberto Ribeiro; ALBUQUERQUE, Andre Luis Pereira de; ALIVERTI, Andrea; PENNATI, FrancescaRationale and Objectives To evaluate associations between longitudinal changes of quantitative CT parameters and spirometry in patients with fibrotic hypersensitivity pneumonitis (HP). Materials and Methods Serial CT images and spirometric data were retrospectively collected in a group of 25 fibrotic HP patients. Quantitative CT analysis included histogram parameters (median, interquartile range, skewness, and kurtosis) and a pretrained convolutional neural network (CNN)-based textural analysis, aimed at quantifying the extent of consolidation (C), fibrosis (F), ground-glass opacity (GGO), low attenuation areas (LAA) and healthy tissue (H). Results At baseline, Ric was 61(44-70) %pred. The median follow-up period was 1.4(0.8-3.2) years, with 3(2-4) visits per patient. Over the study, 8 patients (32%) showed a FVC decline of more than 5%, a significant worsening of all histogram parameters (p <= 0.015) and an increased extent of fibrosis via CNN (p=0.038). On histogram analysis, decreased skewness and kurtosis were the parameters most strongly associated with worsened FVC (respectively, r2=0.63 and r2=0.54, p<0.001). On CNN classification, increased extent of fibrosis and consolidation were the measures most strongly correlated with FVC decline (r2=0.54 and r2=0.44, p<0.001). Conclusion CT histogram and CNN measurements provide sensitive measures of functional changes in fibrotic HP patients over time. Increased fibrosis was associated with FVC decline, providing index of disease progression. CNN may help improve fibrotic HP follow-up, providing a sensitive tool for progressive interstitial changes, which can potentially contribute to clinical decisions for individualizing disease management.
- Convolutional neural network (CNN) for interstitial lung disease (ILD) patterns recognition(2019) ALIBONI, Lorenzo; PENNATI, Francesca; DIAS, Olivia; BALDI, Bruno; SAWAMURA, Marcio; CHATE, Rodrigo; CARVALHO, Carlos Roberto De; ALIVERTI, Andrea
- Clinical, tomographic and functional comparison of sporadic and tuberous sclerosis complex-associated forms of lymphangioleiomyomatosis: a retrospective cohort study(2024) OLIVEIRA, Martina Rodrigues; WANDERLEY, Mark; FREITAS, Carolina Salim Goncalves; KAIRALLA, Ronaldo Adib; CHATE, Rodrigo Caruso; AMARAL, Alexandre Franco; ARIMURA, Fabio Eiji; SAMORANO, Luciana Paula; WATANABE, Elieser Hitoshi; CARVALHO, Carlos Roberto Ribeiro; BALDI, Bruno GuedesBackground Lymphangioleiomyomatosis (LAM) is a rare disease that can occur sporadically (S-LAM) or associated with the tuberous sclerosis complex (TSC-LAM). The natural history of LAM is not completely understood, including whether there is a difference between the clinical courses of the two forms. This study aimed to compare the clinical, functional and tomographic features between S-LAM and TSC-LAM, and evaluate the annual rates of change in lung function. Methods This retrospective cohort study included patients with LAM followed up between 1994 and 2019. Clinical, functional and imaging variables were evaluated, and the lung cysts were automatically quantified. Quality of life and predictors of lung function impairment were accessed, and the annual rate of lung function decline was compared between S-LAM and TSC-LAM. Results Of the 107 patients included, 77 had S-LAM and 30 had TSC-LAM. Although patients with TSCLAM had a higher prevalence of renal angiomyolipomas and neurological and dermatological manifestations, pulmonary function tests were similar. Patients with S-LAM had a greater rate of forced expiratory volume in 1 s decline and a higher extent of cysts. Pneumothorax, desaturation in the 6-minute walking test and a higher extent of lung cysts were predictors of functional impairment. A greater impact on vitality and emotional health was observed in the TSC-LAM. Conclusion Greater functional decline and a higher cystic extension were found in patients with S-LAM. Our study provides a broad clinical, functional and tomographic characterisation of patients with LAM, adding valuable information to the existing evidence to better understand the two forms of the disease.