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  • 1
    Keywords: CANCER ; COMPUTED-TOMOGRAPHY ; HELICAL CT ; MANAGEMENT ; GUIDELINES ; IMAGE QUALITY ; CHEST CT ; STATEMENT ; SCREENING TRIAL ; LOW-DOSE CT
    Abstract: OBJECTIVES: To evaluate the influence of exposure parameters and raw-data based iterative reconstruction (IR) on the measurement variability of computer-aided nodule volumetry on chest multidetector computed tomography (MDCT). MATERIALS AND METHODS: N=7 porcine lung explants were inflated in a dedicated ex vivo phantom and prepared with n=162 artificial nodules. MDCT was performed eight consecutive times (combinations of 120 and 80 kV with 120, 60, 30 and 12 mAs), and reconstructed with filtered back projection (FBP) and IR. Nodule volume and diameter were measured semi-automatically with dedicated software. The absolute percentage measurement error (APE) was computed in relation to the 120 kV 120 mAs acquisition. Noise was recorded for each nodule in every dataset. RESULTS: Mean nodule volume and diameter were 0.32 +/- 0.15 ml and 12.0 +/- 2.6mm, respectively. Although IR reduced noise by 24.9% on average compared to FBP (p〈0.007), APE with IR was equal to or slightly higher than with FBP. Mean APE for volume increased significantly below a volume computed tomography dose index (CTDI) of 1.0 mGy: for 120 kV 12 mAs APE was 3.8 +/- 6.2% (FBP) vs. 4.0 +/- 5.2% (IR) (p〈0.007); for 80 kV 12 mAs APE was 8.0 +/- 13.0% vs. 9.3 +/- 15.8% (n.s.), respectively. Correlating APE with image noise revealed that at identical noise APE was higher with IR than with FBP (p〈0.05). CONCLUSIONS: Computer-aided volumetry is robust in a wide range of exposure settings, and reproducibility is reduced at a CTDI below 1.0 mGy only, but the error rate remains clinically irrelevant. Noise reduction by IR is not detrimental for measurement error in the setting of semi-automatic nodule volumetry on chest MDCT.
    Type of Publication: Journal article published
    PubMed ID: 23727376
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  • 2
    Abstract: Recently, a novel classification system based on tumour architecture and with high prognostic impact has been proposed for pulmonary adenocarcinomas (ADCs). For imaging-based prediction of histological ADC subtypes and, thus, prognosis, it is of paramount importance to investigate the correlations of radio- and histomorphological parameters. Associations between histomorphological ADC growth patterns (lepidic, acinar, papillary, micropapillary and solid) and data from pre-operative assessment by computed tomography (CT) imaging of 174 resected pulmonary ADCs were analysed. Margin configuration as well as solidity/ground glass opacity of an ADC was associated with distinct histomorphological ADC growth patterns. Solid-predominant ADCs usually had smooth margins and were also solid in CT scans, while lepidic-predominant ADCs had no predominant margin pattern, were located in the periphery, showed a positive bronchogram and were frequently associated with solidity/ground glass opacity. In addition, nonspherical tumour growth was a negative predictor of overall and disease-specific patient survival. We defined CT morphological parameters that were associated with histomorphological growth patterns of pulmonary ADCs. These data may form the basis for the development of future prognostic algorithms in the palliative setting, which include an integrated evaluation of biopsy histomorphology and CT scan morphology of nonresectable pulmonary ADC.
    Type of Publication: Journal article published
    PubMed ID: 22835610
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  • 3
    Keywords: INVASION ; SURVIVAL ; tumor ; THERAPY ; CLASSIFICATION ; MANAGEMENT ; SOCIETY ; LUNG-CANCER PATIENTS ; CHEMORADIOTHERAPY ; SECTION CT FINDINGS
    Abstract: OBJECTIVE: To characterize the morphological computed tomography (CT) features of pulmonary squamous cell carcinomas (SQCC) submitted to therapeutic resection; to correlate these features with patients' outcomes; and to compare with pulmonary adenocarcinomas (ADC). MATERIALS AND METHODS: Two chest radiologists retrospectively evaluated CT exams of 123 patients with SQCC resected between 2002 and 2008. Tumors' size, location (central vs. peripheral), shape, margins, attenuation, enhancement, presence of calcification, cavitation, internal air bronchograms and pleural tags were assigned by consensus. Prevalence of features was compared with patients' survival data and a previously studied population of ADC surgically resected at the same time period. RESULTS: Cavitation correlated negatively with overall (hazard ratio=3.04), disease-specific (HR=3.67) and disease-free survival (HR=2.69), independent from age, gender, tumor pathological stage, size, and location. In relation to ADC, SQCC presented different shape, margins, attenuation, enhancement, with more cavitation, rare internal air bronchograms, and less pleural tags. Differences were also significant when comparing only the peripheral type of tumors. CONCLUSIONS: Cavitation at CT was an independent and negative predictive factor for SQCC. Different CT morphological features were described for SQCC and ADC. Image evaluation of lung lesions should go beyond measuring and addressing adjacent structures invasion. Adequate imaging characterization not only helps to differentiate benign versus malignant disease and to determine malignancy staging, it may also imply the histologic subtype and improve the prognostic assessment of lung cancer patients.
    Type of Publication: Journal article published
    PubMed ID: 24840477
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  • 4
    Keywords: CANCER ; DIAGNOSIS ; PERFORMANCE ; REPRODUCIBILITY ; HELICAL CT ; IMAGE QUALITY ; volumetry ; CHEST CT ; RADIOLOGISTS DETECTION ; CAD SOFTWARE
    Abstract: OBJECTIVES: To evaluate the influence of exposure parameters and raw-data based iterative reconstruction (IR) on the performance of computer-aided detection (CAD) of pulmonary nodules on chest multidetector computed tomography (MDCT). MATERIAL AND METHODS: Seven porcine lung explants were inflated in a dedicated ex vivo phantom shell and prepared with n=162 artificial nodules of a clinically relevant volume and maximum diameter (46-1063mul, and 6.2-21.5mm). n=118 nodules were solid and n=44 part-solid. MDCT was performed with different combinations of 120 and 80kV with 120, 60, 30 and 12mA*s, and reconstructed with both filtered back projection (FBP) and IR. Subsequently, 16 datasets per lung were subjected to dedicated CAD software. The rate of true positive, false negative and false positive CAD marks was measured for each reconstruction. RESULTS: The rate of true positive findings ranged between 88.9-91.4% for FBP and 88.3-90.1% for IR (n.s.) with most exposure settings, but was significantly lower with the combination of 80kV and 12mA*s (80.9% and 81.5%, respectively, p〈0.05). False positive findings ranged between 2.3 - 8.1 annotations per lung. For nodule volumes 〈200mul the rate of true positives was significantly lower than for 〉300mul (p〈0.05). Similarly, it was significantly lower for diameters 〈12mm compared to 〉/=12mm (p〈0.05). The rate of true positives for solid and part-solid nodules was similar. CONCLUSIONS: Nodule CAD on chest MDCT is robust over a wide range of exposure settings. Noise reduction by IR is not detrimental for CAD, and may be used to improve image quality in the setting of low-dose MDCT for lung cancer screening.
    Type of Publication: Journal article published
    PubMed ID: 25740701
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  • 5
    Keywords: CT ; FLOW ; COMPUTED-TOMOGRAPHY ; PULMONARY-EMBOLISM ; proton MRI ; INITIAL-EXPERIENCE ; DUAL-ENERGY TECHNIQUE
    Abstract: PURPOSE: To assess the reproducibility of Fourier decomposition (FD) based ventilation- and perfusion-weighted lung MRI. METHODS: Sixteen healthy volunteers were examined on a 1.5 T whole-body MR-scanner with 4-6 sets of coronal slices over the chest volume with a non-contrast enhanced steady-state free precession sequence. The identical protocol was repeated after 24h. Reconstructed perfusion- and ventilation-weighted images were obtained through non-rigid registration and FD post-processing of images. Analysis of signal in segmented regions of interest was performed for both native and post-processed data. Two blinded chest radiologists rated image quality of perfusion- and ventilation-weighted images using a 3-point scale. RESULTS: Reproducibility of signal between the two time points was very good with intra-class correlation coefficients of 0.98, 0.94 and 0.86 for native, perfusion- and ventilation-weighted images, respectively. Perfusion- and ventilation-weighted images were of overall good quality with proportions of diagnostic images of 87-95% and 69-75%, respectively. Lung signal decreased from posterior to anterior slices with image quality of ventilation-weighted images in anterior areas rated worse than in posterior or perfusion-weighted images. Inter- and intra-observer agreement of image quality was good for perfusion and ventilation. CONCLUSIONS: The study demonstrates high reproducibility of ventilation- and perfusion-weighted FD lung MRI.
    Type of Publication: Journal article published
    PubMed ID: 23295084
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