Effects of nandrolone decanoate on telomere length and clinical outcome in patients with telomeropathies: a prospective trial.

Androgens have been reported to elongate telomeres in retrospective and prospective trials with patients with telomeropathies, mainly with bone marrow failure. In our single-arm prospective clinical trial (clinicaltrials gov. Identifier: NCT02055456), 17 patients with short telomeres and/or germline pathogenic variants in telomere biology genes associated with at least one cytopenia and/or radiologic diagnosis of interstitial lung disease were treated with 5 mg/kg of intramuscular nandrolone decanoate every 15 days for 2 years. Ten of 13 evaluable patients (77%) showed telomere elongation at 12 months by flow-fluorescence in situ hybridization (average increase, 0.87 kb; 95% confidence interval: 0.20-1.55 kb; P=0.01). At 24 months, all ten evaluable patients showed telomere elongation (average increase, 0.49 kb; 95% confidence interval: 0.24-1.23 kb; P=0.18). Hematologic response was achieved in eight of 16 patients (50%) with marrow failure at 12 months, and in ten of 16 patients (63%) at 24 months. Seven patients had interstitial lung disease at baseline, and two and three had pulmonary response at 12 and 24 months, respectively. Two patients died due to pulmonary failure during treatment. In the remaining evaluable patients, the pulmonary function remained stable or improved, but showed consistent decline after cessation of treatment. Somatic mutations in myeloid neoplasm-related genes were present in a minority of patients and were mostly stable during drug treatment. The most common adverse events were elevations in liver function test levels in 88%, acne in 59%, and virilization in 59%. No adverse events grade ≥4 was observed. Our findings indicate that nandrolone decanoate elongates telomeres in patients with telomeropathies, which correlated with clinical improvement in some cases and tolerable adverse events.

Correlation among clinical, functional and morphological indexes of the respiratory system in non-cystic fibrosis bronchiectasis patients.

BACKGROUND: Non-cystic fibrosis bronchiectasis (NCFB) is a heterogeneous disease, which assessment and severity can't be defined by one particular instrument but using a multidimensional score. Thus, in additional to traditional methods, alternative tools have been developed to assist these patients' evaluation. OBJECTIVE: To correlate functional and morphological indexes with severity and dyspnea in NCFB patients, focusing on the correlation between the impulse oscillometry system (IOS) and the quantitative analysis of computed tomography (CT). METHODS: Clinically stable NCFB patients, between 18 and 80 years old were submitted to clinical, functional and morphological evaluations assessed by Bronchiectasis Severity Index (BSI) and Medical Research Council (MRC) scale; spirometry and IOS; and subjective and quantitative Chest CT scans analysis, respectively. RESULTS: This study included 38 patients. The best correlations obtained between functional and morphological airway indexes were: resistance at 5 Hz-R5 and the normalized thickness of bronchial walls-Pi10 (r = 0.57), and the mean forced expiratory flow (FEF25-75%) and CT score (r = -0.39). BSI as well as MRC showed higher correlations with the quantitative automated analysis of CT (BSI and Pi10: r = 0.41; MRC and Pi10: r = 0.35) than with subjective CT score (BSI and CT score: r = 0.41; MRC and CT score: r = 0.15); and moderate and weak correlations were obtained on both functional airway indexes (BSI and peripheral airways resistance - R5-R20: r = 0.53; BSI and forced expiratory volume at the first second-FEV1: R = -0,64; MRC and R5-R20: r = 0.42; and MRC and VEF1: r = -0.45). CONCLUSION: In NCFB patients, compartmentalized methods for assessing the respiratory system (IOS and the automated quantitative CT analysis) have a good correlation with severity and dyspnea.

SARS-Cov-2 pneumonia phenotyping on imaging exams of patients submitted to minimally invasive autopsy.

Background: Correlation between pathology and imaging of the new SARS-Cov-2 disease (COVID-19) is scarce. This study aimed to characterize SARS-Cov-2 pneumonia on imaging of patients submitted to minimally invasive autopsy (MIA). Methods: This unicentric retrospective observational study included 46 consecutive patients with confirmed COVID-19 who underwent MIA. All clinical chest images were reviewed and classified for the presence and grade of viral pneumonia, as well as disease evolution. On CT, phenotypes were described as consistent with mild, moderate, or severe viral pneumonia, with or without radiological signs of organizing pneumonia (OP). In severe pneumonia, CT could also be classified as diffuse progressive OP or radiological diffuse alveolar damage (DAD). Specific features on CT were noted, including fibroproliferative signs that could indicate potential or initial fibrosis. Results: MIA showed a heterogeneous panel of alterations, with a high prevalence of OP and acute fibrinous and organizing pneumonia (AFOP). Also, signs of interstitial fibrosis corresponded to the most prevalent pathological feature. Initial chest radiography (CXR) findings were mainly consistent with moderate or severe viral pneumonia. Most patients showed stability or improvement (reduction of opacities) on imaging. CTs were performed on 15 patients. Consolidations were found in most patients, frequently showing features consistent with an OP phenotype. Fibroproliferative changes were also prevalent on CT. Conclusions: In this study, SARS-Cov-2 pneumonia showed heterogeneous radiological and pathological patterns. Signs of organization and potential or initial fibrosis were prevalent on both imaging and pathology. Imaging phenotyping may help to predict post-infection fibrosing interstitial pneumonitis in COVID-19.

Electrocardiogram abnormalities in chronic Chagas cardiomyopathy correlate with scar mass and left ventricular dysfunction as assessed by cardiac magnetic resonance imaging.

Electrocardiographic (ECG) abnormalities are frequently identified in Chronic Chagas cardiomyopathy (CCC) patients and advanced abnormalities are related to a worse prognosis. Cardiac Magnetic Resonance (CMR) can precisely assess ventricular systolic dysfunction and quantify myocardial fibrosis (MF), both identified as prognostic factors. We sought to investigate if ECG abnormalities in CCC patients were associated with more severe myocardial involvement as evaluated by CMR. METHODS: CCC patients with 12­lead ECG and CMR closely obtained were included. ECG analysis evaluated rhythm, presence, and type of intraventricular conduction disturbances (IVCD) and, ventricular premature beats (VPB). CMR short-axis cine and late gadolinium enhancement images were evaluated to obtain left and right ventricular ejection fractions and MF mass, respectively. Statistical significance was set in 5%. RESULTS: 194 CCC patients (98 women, 56 ± 14 years) were evaluated, and no IVCD was detected in 71. The most common IVCD was the association of right bundle branch block and left anterior fascicular block (RBBB+LAFB) in 58 patients, followed by isolated RBBB in 34, isolated LAFB in 17, and left bundle branch block (LBBB) in 14 patients. Of patients with no IVCD, 63% had MF and the burden of fibrosis (no IVCD - 7.4 ± 8.6%; RBBB - 6.6 ± 6.5%; p = 1.00), as well as left ventricular ejection fraction (LVEF) (no IVCD - 52 ± 14%; RBBB - 55 ± 10%; p = 1.00) were similar to patients with isolated RBBB. Left conduction system impairment was associated with lower LVEF (LAFB - 39 ± 15%; RBBB+LAFB- 41 ± 15%; and LBBB - 35 ± 15%; p < 0.001) and more MF (RBBB+LAFB - 12.2 ± 10.4%; LBBB - 10.6 ± 7.5%; and LAFB - 12.0 ± 7.0%; p < 0.001). The univariable model showed that the presence of MF was related to RBBB+LAFB (OR 5.0; p = 0.001) and VPB (OR 6.3; p = 0.014). After adjustment for age, gender, and different risk factors in a multivariable model, the same findings were still significantly related to CMR myocardial fibrosis (RBBB+LAFB OR 5.0; p = 0.002 / VPB OR 6.9; p = 0.015). CONCLUSIONS: ECG without IVCD does not exclude serious cardiac abnormalities in CCC, and isolated RBBB seems to have a benign course. The presence of VPB and left branch conduction impairment, especially LAFB associated with RBBB, indicate a more severe cardiac involvement.

Long-Term Symptoms among COVID-19 Survivors in Prospective Cohort Study, Brazil.

We conducted a prospective cohort study in a population with diverse ethnic backgrounds from Brazil to assess clinically meaningful symptoms after surviving coronavirus disease. For most of the 175 patients in the study, clinically meaningful symptoms, including fatigue, dyspnea, cough, headache, and muscle weakness, persisted for >120 days after disease onset.

Cannabidiol for COVID-19 Patients with Mild to Moderate Symptoms (CANDIDATE Study): A Randomized, Double-Blind, Placebo-Controlled Clinical Trial.

Importance: Owing to its anti-inflammatory properties and antiviral "in vitro" effect against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), cannabidiol (CBD) has been proposed as a potential treatment for coronavirus disease 2019 (COVID-19). Objective: To investigate the safety and efficacy of CBD for treating patients with mild to moderate COVID-19. Design: Randomized, parallel-group, double-blind, placebo-controlled clinical trial conducted between July 7 and October 16, 2020, in two sites in Brazil. Setting: Patients were recruited in an emergency room. Participants: Block randomized patients (1:1 allocation ratio-by a researcher not directly involved in data collection) with mild and moderate COVID-19 living in Ribeirão Preto, Brazil, seeking medical consultation, and those who voluntarily agreed to participate in the study. Interventions: Patients received 300 mg of CBD or placebo added to standard symptomatic care during 14 days. Main Outcome and Measure: The primary outcome was reduction or prevention of the deterioration in clinical status from mild/moderate to severe/critical measured with the COVID-19 Scale or the natural course of the resolution of typical clinical symptoms. Primary study outcome was assessed on days 14, 21, and 28 after enrollment. Results: A total of 321 patients were recruited and assessed for eligibility, and 105 were randomly allocated either in CBD (n=49) or in placebo (n=42) group. Ninety-one participants were included in the analysis of efficacy. There were no baseline between-group differences regarding disease severity (χ2=0.025, p=0.988) and median time to symptom resolution (12 days [95% confidence interval, CI, 6.5-17.5] in the CBD group, 9 days [95% CI, 4.8-13.2] in the placebo group [χ2=1.6, p=0.205 by log-rank test]). By day 28, 83.3% in the CBD group and 90.2% in the placebo group had resolved symptoms. There were no between-group differences on secondary measures. CBD was well tolerated, producing mostly mild and transient side effects (e.g., somnolence, fatigue, changes in appetite, lethargy, nausea, diarrhea, and fever), with no significant differences between CBD and placebo treatment groups. Conclusions and Relevance: Daily administration of 300 mg CBD for 14 days failed to alter the clinical evolution of COVID-19. Further trials should explore the therapeutic effect of CBD in patients with severe COVID-19, possibly trying higher doses than the used in our study. Trial Registration: ClinicalTrials.gov identifier NCT04467918 (date of registration: July 13, 2020).

Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity.

OBJECTIVE: To determine whether the radiomic features of lung lesions on computed tomography correlate with overall survival in lung cancer patients. MATERIALS AND METHODS: This was a retrospective study involving 101 consecutive patients with malignant neoplasms confirmed by biopsy or surgery. On computed tomography images, the lesions were submitted to semi-automated segmentation and were characterized on the basis of 2,465 radiomic variables. The prognostic assessment was based on Kaplan-Meier analysis and log-rank tests, according to the median value of the radiomic variables. RESULTS: Of the 101 patients evaluated, 28 died (16 dying from lung cancer), and 73 were censored, with a mean overall survival time of 1,819.4 days (95% confidence interval [95% CI]: 1,481.2-2,157.5). One radiomic feature (the mean of the Fourier transform) presented a difference on Kaplan-Meier curves (p < 0.05). A high-risk group of patients was identified on the basis of high values for the mean of the Fourier transform. In that group, the mean survival time was 1,465.4 days (95% CI: 985.2-1,945.6), with a hazard ratio of 2.12 (95% CI: 1.01-4.48). We also identified a low-risk group, in which the mean of the Fourier transform was low (mean survival time of 2,164.8 days; 95% CI: 1,745.4-2,584.1). CONCLUSION: A radiomic signature based on the Fourier transform correlates with overall survival, representing a prognostic biomarker for risk stratification in patients with lung cancer.

OBJETIVO: Associar características radiômicas de lesões pulmonares em imagens de tomografia computadorizada com a sobrevida global de pacientes com câncer de pulmão. MATERIAIS E MÉTODOS: Estudo retrospectivo composto por 101 pacientes consecutivos com neoplasia maligna confirmada por biópsia/cirurgia. As lesões foram semiautomaticamente segmentadas e caracterizadas por 2.465 variáveis radiômicas. A avaliação prognóstica foi baseada na análise de Kaplan-Meier e no teste log-rank, de acordo com a mediana dos valores das variáveis. RESULTADOS: Vinte e oito pacientes faleceram (16 por câncer de pulmão) e 73 foram censurados, com tempo médio de sobrevida de 1.819,4 dias (intervalo de confiança 95% [IC 95%]: 1.481,2-2.157,5). Uma característica radiômica (média de Fourier) apresentou diferença nas curvas de Kaplan-Meier (p < 0,05). Um grupo de pacientes de maior risco foi identificado a partir de valores altos da variável: sobrevida de 1.465,4 dias (IC 95%: 985,2-1.945,6) e razão de risco de 2,12 (IC 95%: 1,01-4,48). Um grupo de menor risco foi identificado a partir de valores baixos da variável (sobrevida de 2.164,8 dias; IC 95%: 1.745,4-2.584,1). CONCLUSÃO: Este estudo apresentou uma assinatura radiômica em imagens de tomografia computadorizada, baseada na transformada de Fourier, correlacionada com a sobrevida global de pacientes com câncer de pulmão, representando assim um biomarcador prognóstico.

Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity / Análise radiômica do câncer de pulmão para avaliação prognóstica do paciente e da heterogeneidade intratumoral

Abstract Objective: To determine whether the radiomic features of lung lesions on computed tomography correlate with overall survival in lung cancer patients. Materials and Methods: This was a retrospective study involving 101 consecutive patients with malignant neoplasms confirmed by biopsy or surgery. On computed tomography images, the lesions were submitted to semi-automated segmentation and were characterized on the basis of 2,465 radiomic variables. The prognostic assessment was based on Kaplan-Meier analysis and log-rank tests, according to the median value of the radiomic variables. Results: Of the 101 patients evaluated, 28 died (16 dying from lung cancer), and 73 were censored, with a mean overall survival time of 1,819.4 days (95% confidence interval [95% CI]: 1,481.2-2,157.5). One radiomic feature (the mean of the Fourier transform) presented a difference on Kaplan-Meier curves (p < 0.05). A high-risk group of patients was identified on the basis of high values for the mean of the Fourier transform. In that group, the mean survival time was 1,465.4 days (95% CI: 985.2-1,945.6), with a hazard ratio of 2.12 (95% CI: 1.01-4.48). We also identified a low-risk group, in which the mean of the Fourier transform was low (mean survival time of 2,164.8 days; 95% CI: 1,745.4-2,584.1). Conclusion: A radiomic signature based on the Fourier transform correlates with overall survival, representing a prognostic biomarker for risk stratification in patients with lung cancer.

Resumo Objetivo: Associar características radiômicas de lesões pulmonares em imagens de tomografia computadorizada com a sobrevida global de pacientes com câncer de pulmão. Materiais e Métodos: Estudo retrospectivo composto por 101 pacientes consecutivos com neoplasia maligna confirmada por biópsia/cirurgia. As lesões foram semiautomaticamente segmentadas e caracterizadas por 2.465 variáveis radiômicas. A avaliação prognóstica foi baseada na análise de Kaplan-Meier e no teste log-rank, de acordo com a mediana dos valores das variáveis. Resultados: Vinte e oito pacientes faleceram (16 por câncer de pulmão) e 73 foram censurados, com tempo médio de sobrevida de 1.819,4 dias (intervalo de confiança 95% [IC 95%]: 1.481,2-2.157,5). Uma característica radiômica (média de Fourier) apresentou diferença nas curvas de Kaplan-Meier (p < 0,05). Um grupo de pacientes de maior risco foi identificado a partir de valores altos da variável: sobrevida de 1.465,4 dias (IC 95%: 985,2-1.945,6) e razão de risco de 2,12 (IC 95%: 1,01-4,48). Um grupo de menor risco foi identificado a partir de valores baixos da variável (sobrevida de 2.164,8 dias; IC 95%: 1.745,4-2.584,1). Conclusão: Este estudo apresentou uma assinatura radiômica em imagens de tomografia computadorizada, baseada na transformada de Fourier, correlacionada com a sobrevida global de pacientes com câncer de pulmão, representando assim um biomarcador prognóstico.

Post-Traumatic Giant Left Ventricular Pseudoaneurysm: a Multimedia Presentation.

Traumatic left ventricular pseudoaneurysms are rare and surgical correction is the treatment of choice. In this article, it is reported a case of a myocardial stab injury with primary suture and development of a giant pseudoaneurysm, five years later, that underwent surgical repair.

Post-traumatic giant left ventricular pseudoaneurysm: a multimedia presentation

Abstract Traumatic left ventricular pseudoaneurysms are rare and surgical correction is the treatment of choice. In this article, it is reported a case of a myocardial stab injury with primary suture and development of a giant pseudoaneurysm, five years later, that underwent surgical repair.

CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms.

PURPOSE: As some of the most important factors for treatment decision of lung cancer (which is the deadliest neoplasm) are staging and histology, this work aimed to associate quantitative contrast-enhanced computed tomography (CT) features from malignant lung tumors with distant and nodal metastases (according to clinical TNM staging) and histopathology (according to biopsy and surgical resection) using radiomics assessment. METHODS: A local cohort of 85 patients were retrospectively (2010-2017) analyzed after approval by the institutional research review board. CT images acquired with the same protocol were semiautomatically segmented by a volumetric segmentation method. Tumors were characterized by quantitative CT features of shape, first-order, second-order, and higher-order textures. Statistical and machine learning analyses assessed the features individually and combined with clinical data. RESULTS: Univariate and multivariate analyses identified 40, 2003, and 45 quantitative features associated with distant metastasis, nodal metastasis, and histopathology (adenocarcinoma and squamous cell carcinoma), respectively. A machine learning model yielded the highest areas under the receiver operating characteristic curves of 0.92, 0.84, and 0.88 to predict the same previous patterns. CONCLUSION: Several radiomic features (including wavelet energies, information measures of correlation and maximum probability from co-occurrence matrix, busyness from neighborhood intensity-difference matrix, directionalities from Tamura's texture, and fractal dimension estimation) significantly associated with distant metastasis, nodal metastasis, and histology were discovered in this work, presenting great potential as imaging biomarkers for pathological diagnosis and target therapy decision.

Automatic Quantitative Computed Tomography Evaluation of the Lungs in Patients With Systemic Sclerosis Treated With Autologous Stem Cell Transplantation.

BACKGROUND/OBJECTIVE: Interstitial lung disease stands among the leading causes of death in systemic sclerosis (SSc) patients. Autologous hematopoietic stem cell transplantation (AHSCT) has been proven superior to conventional immunosuppressive therapy in severe and progressive SSc. Here, pulmonary quantitative measurements were obtained in high-resolution computed tomography (HRCT) scans of patients with SSc before and after AHSCT. METHODS: The medical records of thirthy-three patients who underwent AHSCT between 2011 and 2017 were evaluated for clinical and tomographic features at baseline (pre-AHCST) and 18 months after the procedure. Quantitative analysis of HRCT images by a fully automated program calculated lung volumes, densities, attenuation percentiles, and vascular volume. Patients were divided into 2 groups, according to changes in forced vital capacity (FVC). The "best response" group included patients that had an increased FVC of 10% or greater, and the "stable response" group included those who had a decreased or an increased FVC of less than 10%. RESULTS: In the best response group (15 patients), there was reduction (p < 0.05) of mean lung density and density percentile values after AHSCT. In the stable response group (18 patients), there were no significant changes in lung volumes and pulmonary densities after AHSCT. Pulmonary HRCT densities showed moderate/strong correlation with function. CONCLUSIONS: Quantitative HRCT analysis identified significant reduction in pulmonary densities in patients with improved pulmonary function after AHSCT. Lung density, as evaluated by the quantitative HRCT analysis tool, has potential to become a biomarker in the evaluation of interstitial lung disease treatment in patients with SSc.

dp-BREATH: Heat maps and probabilistic classification assisting the analysis of abnormal lung regions.

BACKGROUND AND OBJECTIVE: Identifying abnormalities in chest CT scans is an important and challenging task, demanding time and effort from specialists. Different parts of a single lung image may present both normal and abnormal characteristics. Thus, detecting a single lung as healthy (normal) or not is inaccurate. METHODS: In this work we propose dp-BREATH, a method capable of detecting abnormalities in pulmonary tissue regions and directing the specialist's attention to the lung region containing them. It starts by highlighting regions that may indicate pulmonary abnormalities based on the healthy pulmonary tissue behavior using a superpixel-based approach and a heat map visualization. This is achieved by modeling regions of healthy tissue using a statistical model. All regions considered abnormal are modeled and classified according to their probability of containing each of the studied abnormalities. Further, dp-BREATH provides a better recognition of radiological patterns, with the likelihood of a selected lung region to contain abnormalities. RESULTS: We validate the statistical model of healthy and abnormal detection using a representative dataset of chest CT scans. The model has shown almost no overlap between healthy and abnormal regions, and the detection of abnormalities presented precision higher than 86%, for all recall values. Additionally, the fitted models describing pulmonary radiological patterns present precision of up to 87%, with a high separation for three of five radiological patterns. CONCLUSIONS: dp-BREATH's heat map representation and its list of radiological patterns probabilities provided are intuitive methods to assist physicians during diagnosis.

Radiomics-based features for pattern recognition of lung cancer histopathology and metastases.

BACKGROUND AND OBJECTIVES: lung cancer is the leading cause of cancer-related deaths in the world, and its poor prognosis varies markedly according to tumor staging. Computed tomography (CT) is the imaging modality of choice for lung cancer evaluation, being used for diagnosis and clinical staging. Besides tumor stage, other features, like histopathological subtype, can also add prognostic information. In this work, radiomics-based CT features were used to predict lung cancer histopathology and metastases using machine learning models. METHODS: local image datasets of confirmed primary malignant pulmonary tumors were retrospectively evaluated for testing and validation. CT images acquired with same protocol were semiautomatically segmented. Tumors were characterized by clinical features and computer attributes of intensity, histogram, texture, shape, and volume. Three machine learning classifiers used up to 100 selected features to perform the analysis. RESULTS: radiomics-based features yielded areas under the receiver operating characteristic curve of 0.89, 0.97, and 0.92 at testing and 0.75, 0.71, and 0.81 at validation for lymph nodal metastasis, distant metastasis, and histopathology pattern recognition, respectively. CONCLUSIONS: the radiomics characterization approach presented great potential to be used in a computational model to aid lung cancer histopathological subtype diagnosis as a "virtual biopsy" and metastatic prediction for therapy decision support without the necessity of a whole-body imaging scanning.

Influence of fissure integrity on quantitative CT and emphysema distribution in emphysema-type COPD using a dedicated COPD software.

OBJECTIVES: Fissure integrity (FI) plays a key role in selecting patients for interventional emphysema therapy. We investigated its interference with automated lobar segmentation in quantitative computed tomography (CT) and emphysema distribution. METHODS: CT was available for 50 patients with chronic obstructive pulmonary disease (COPD). Lobe segmentation was performed fully automated by software and corrected manually. FI was evaluated visually using a %-scale. The influence of FI on emphysema ratio (ER=percentage of lung volume with density values<-950 HU), mean lung density (MLD), emphysema and total volume of adjacent lobes was analyzed. Lobe-based results were compared with respect to FI. RESULTS: Differences in ER in adjacent lobes for complete vs. incomplete fissures were 12.4% for the right horizontal, 0.2% and 3% for the right oblique and 4.4% for the left oblique fissure (all p>0.05). Results for emphysema comparing automated vs. manually corrected segmentation exceeded clinically acceptable values, but were not significantly affected by FI (p>0.05). The widest limits of agreement for ER and MLD were noted in the right middle lobe ([-14, 17.4%], [-22.4, 32.4 Hounsfield Units]). CONCLUSIONS: Automated lobe segmentation and emphysema distribution are not significantly affected by FI. Manual correction of automated lobar segmentation is still recommended in severe emphysema.

Contrast-enhanced magnetic resonance imaging of pulmonary lesions: description of a technique aiming clinical practice.

OBJECTIVE: To propose a technique for evaluation of pulmonary lesions using contrast-enhanced MRI; to assess morphological patterns of enhancement and correlate quantitative analysis with histopathology. MATERIAL AND METHODS: Thirty-six patients were prospectively studied. Volumetric-interpolated T1W images were obtained during consecutive breath holds after bolus triggered contrast injection. Volume coverage of first three acquisitions was limited (higher temporal resolution) and last acquisition obtained at 4th min. Two radiologists individually evaluated the patterns of enhancement. Region-of-interest-based signal intensity (SI)-time curves were created to assess quantitative parameters. RESULTS: Readers agreed moderately to substantially concerning lesions' enhancement pattern. SI-time curves could be created for all lesions. In comparison to benign, malignant lesions showed higher values of maximum enhancement, early peak, slope and 4th min enhancement. Early peak >15% showed 100% sensitivity to detect malignancy, maximum enhancement >40% showed 100% specificity. CONCLUSIONS: The proposed technique is robust, simple to perform and can be applied in clinical scenario. It allows visual evaluation of enhancement pattern/progression together with creation of SI-time curves and assessment of derived quantitative parameters. Perfusion analysis was highly sensitive to detect malignancy, in accordance to what is recommended by most recent guidelines on imaging evaluation of pulmonary lesions.