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BACKGROUND CONTEXT: The amount of vertebral rotation in the axial plane is of key importance in the prognosis and treatment of adolescent idiopathic scoliosis (AIS). Current methods to determine vertebral rotation are either designed for use in analogue plain radiographs and not useful in digital images, or lack measurement precision and are therefore less suitable for the follow-up of rotation in AIS patients.PURPOSE: This study aimed to develop a digital X-ray software tool with high measurement precision to determine vertebral rotation in AIS, and to assess its (concurrent) validity and reliability.STUDY DESIGN/SETTING: In this study a combination of basic science and reliability methodology applied in both laboratory and clinical settings was used.METHODS: Software was developed using the algorithm of the Perdriolle torsion meter for analogue AP plain radiographs of the spine. Software was then assessed for (1) concurrent validity and (2) intra-and interobserver reliability. Plain radiographs of both human cadaver vertebrae and outpatient AIS patients were used. Concurrent validity was measured by two independent observers, both experienced in the assessment of plain radiographs. Reliability-measurements were performed by three independent spine surgeons.RESULTS: Pearson correlation of the software compared with the analogue Perdriolle torsion meter for mid-thoracic vertebrae was 0.98, for low-thoracic vertebrae 0.97 and for lumbar vertebrae 0.97. Measurement exactness of the software was within 5 degrees in 62% of cases and within 10 degrees in 97% of cases. Intraclass correlation coefficient (ICC) for inter-observer reliability was 0.92 (0.91-0.95), ICC for intra-observer reliability was 0.96 (0.94-0.97).CONCLUSIONS: We developed a digital X-ray software tool to determine vertebral rotation in AIS with a substantial concurrent validity and reliability, which may be useful for the follow-up of vertebral rotation in AIS patients. (C) 2015 Elsevier Inc. All rights reserved.

Image registration, the process of aligning two or more images, is the core technique of many (semi-)automatic medical image analysis tasks. Recent studies have shown that deep learning methods, notably convolutional neural networks (ConvNets), can be used for image registration. Thus far training of ConvNets for registration was supervised using predefined example registrations. However, obtaining example registrations is not trivial. To circumvent the need for predefined examples, and thereby to increase convenience of training ConvNets for image registration, we propose the Deep Learning Image Registration (DLIR) framework for \textit{unsupervised} affine and deformable image registration. In the DLIR framework ConvNets are trained for image registration by exploiting image similarity analogous to conventional intensity-based image registration. After a ConvNet has been trained with the DLIR framework, it can be used to register pairs of unseen images in one shot. We propose flexible ConvNets designs for affine image registration and for deformable image registration. By stacking multiple of these ConvNets into a larger architecture, we are able to perform coarse-to-fine image registration. We show for registration of cardiac cine MRI and registration of chest CT that performance of the DLIR framework is comparable to conventional image registration while being several orders of magnitude faster., Comment: Accepted: Medical Image Analysis - Elsevier

Dose reduction may compromise patients because of a decrease of image quality. Therefore, the amount of dose savings in new dose-reduction techniques needs to be thoroughly assessed. To avoid repeated studies in one patient, chest computed tomography (CT) scans with different dose levels were performed in corpses comparing model-based iterative reconstruction (MBIR) as a tool to enhance image quality with current standard full-dose imaging.Twenty-five human cadavers were scanned (CT HD750) after contrast medium injection at different, decreasing dose levels D0-D5 and respectively reconstructed with MBIR. The data at full-dose level, D0, have been additionally reconstructed with standard adaptive statistical iterative reconstruction (ASIR), which represented the full-dose baseline reference (FDBR). Two radiologists independently compared image quality (IQ) in 3-mm multiplanar reformations for soft-tissue evaluation of D0-D5 to FDBR (-2, diagnostically inferior; -1, inferior; 0, equal; +1, superior; and +2, diagnostically superior). For statistical analysis, the intraclass correlation coefficient (ICC) and the Wilcoxon test were used.Mean CT dose index values (mGy) were as follows: D0/FDBR = 10.1 ± 1.7, D1 = 6.2 ± 2.8, D2 = 5.7 ± 2.7, D3 = 3.5 ± 1.9, D4 = 1.8 ± 1.0, and D5 = 0.9 ± 0.5. Mean IQ ratings were as follows: D0 = +1.8 ± 0.2, D1 = +1.5 ± 0.3, D2 = +1.1 ± 0.3, D3 = +0.7 ± 0.5, D4 = +0.1 ± 0.5, and D5 = -1.2 ± 0.5. All values demonstrated a significant difference to baseline (P .05), except mean IQ for D4 (P = .61). ICC was 0.91.Compared to ASIR, MBIR allowed for a significant dose reduction of 82% without impairment of IQ. This resulted in a calculated mean effective dose below 1 mSv.

Contains fulltext : 110186.pdf (Publisher’s version ) (Open Access) BACKGROUND: Incidental CT findings may provide an opportunity for early detection of chronic obstructive pulmonary disease (COPD), which may prove important in CT-based lung cancer screening setting. We aimed to determine the diagnostic performance of human observers to visually evaluate COPD presence on CT images, in comparison to automated evaluation using quantitative CT measures. METHODS: This study was approved by the Dutch Ministry of Health and the institutional review board. All participants provided written informed consent. We studied 266 heavy smokers enrolled in a lung cancer screening trial. All subjects underwent volumetric inspiratory and expiratory chest computed tomography (CT). Pulmonary function testing was used as the reference standard for COPD. We evaluated the diagnostic performance of eight observers and one automated model based on quantitative CT measures. RESULTS: The prevalence of COPD in the study population was 44% (118/266), of whom 62% (73/118) had mild disease. The diagnostic accuracy was 74.1% in the automated evaluation, and ranged between 58.3% and 74.3% for the visual evaluation of CT images. The positive predictive value was 74.3% in the automated evaluation, and ranged between 52.9% and 74.7% for the visual evaluation. Interobserver variation was substantial, even within the subgroup of experienced observers. Agreement within observers yielded kappa values between 0.28 and 0.68, regardless of the level of expertise. The agreement between the observers and the automated CT model showed kappa values of 0.12-0.35. CONCLUSIONS: Visual evaluation of COPD presence on chest CT images provides at best modest accuracy and is associated with substantial interobserver variation. Automated evaluation of COPD subjects using quantitative CT measures appears superior to visual evaluation by human observers.

ResumenEntre junio de 2009 y agosto de 2010 la Organización Mundial de la Salud (OMS) declaró una pandemia por el virus de influenza AH1N1. Para junio 2010 se habían confirmado en Colombia 3.572 casos de infección respiratoria por el virus de influenza AH1N1 con una mortalidad de 239 pacientes.ObjetivosDescribir las manifestaciones radiológicas de un grupo de 38 pacientes con diagnóstico confirmado de infección respiratoria por influenza A(H1N1) que requirieron hospitalización. Correlacionar las alteraciones radiológicas con la presentación clínica de los pacientes estudiados en la serie.MetodologíaAnálisis retrospectivo de historias clínicas y estudios de imágenes de una cohorte de 38 pacientes con diagnóstico confirmado de infección por influenza A (H1N1) hospitalizados en el Hospital Universitario Mayor – Méderi en Bogotá entre junio de 2009 y marzo de 2010. Los pacientes fueron divididos en dos grupos de acuerdo a la necesidad de soporte ventilatorio durante la hospitalización. Los estudios de imágenes fueron revisados en consenso por dos radiólogos con experiencia en radiología torácica.ResultadosDe las 38 radiografías de tórax analizadas, 23 (60%) fueron normales. En las radiografías anormales (40% de los casos), las alteraciones más importantes fueron consolidación y vidrio esmerilado. En el grupo que requirió ventilación mecánica, todas las radiografías fueron anormales.ConclusionesEn nuestra serie, los hallazgos en los estudios de imágenes se correlacionaron con la severidad del cuadro clínico. En los pacientes que no requirieron ventilación mecánica, la radiografía de tórax fue normal en un 60%. Todos los pacientes que necesitaron soporte ventilatorio tenían alteraciones radiológicas al ingreso. En los pacientes que requirieron ventilación mecánica, la alteración radiológica predominante fue consolidación de predominio basal.AbstractBetween June 2009 and August 2010, the World Health Organization (WHO) declared a pandemic of the influenza H1N1 virus. Until June 2010, there were 3,572 confirmed cases of influenza AH1N1 virus respiratory infection in Colombia, with 239 deaths.ObjectivesTo describe the radiological studies of a group of 38 patients with a confirmed influenza A(H1N1) respiratory infection diagnosis who required hospitalization. The radiology results were correlated with clinical symptoms.MethodologyMedical records and image studies retrospective analysis of a 38 patient cohort with confirmed influenza A H1N1 infection diagnosis, who were hospitalized at the Universitario Mayor – Méderi Hospital in Bogota, Colombia between June 2009 and March 2010. Patients were divided into two groups according to the need for ventilatory support during hospitalization. The image studies were reviewed by two radiologists with thoracic radiology experience.ResultsOf 38 chest radiographs analyzed, 23 (60%) were normal. Of the 40% abnormal radiographs, the findings were consolidation and ground glass images. In the group requiring mechanical ventilation, all radiographs were abnormal.ConclusionsIn our series, the image study findings were correlated with the severity of the clinical symptoms. Among the patients requiring mechanical ventilation, the thoracic radiography was normal in 79% of the cases. All patients who required mechanical ventilation had radiological alterations at admission. The most common radiographic finding in the group of patients who required mechanical ventilation was basal parenchymal consolidation.