scholarly journals Quantitative Computed Tomography and image analysis for advanced muscle assessment

2016 ◽  
Vol 26 (2) ◽  
Author(s):  
Kyle Joseph Edmunds ◽  
Magnus K. Gíslason ◽  
Iris D. Arnadottir ◽  
Andrea Marcante ◽  
Francesco Piccione ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Analysis ◽  
Medical Imaging ◽  
Quantitative Computed Tomography ◽  
Hounsfield Unit ◽  
Spiral Ct ◽  
Atrophic Muscle ◽  
2D And 3D ◽  
Image Analysis Techniques ◽  
Total Muscle

Medical imaging is of particular interest in the field of translational myology, as extant literature describes the utilization of a wide variety of techniques to non-invasively recapitulate and quantity various internal and external tissue morphologies. In the clinical context, medical imaging remains a vital tool for diagnostics and investigative assessment. This review outlines the results from several investigations on the use of computed tomography (CT) and image analysis techniques to assess muscle conditions and degenerative process due to aging or pathological conditions. Herein, we detail the acquisition of spiral CT images and the use of advanced image analysis tools to characterize muscles in 2D and 3D. Results from these studies recapitulate changes in tissue composition within muscles, as visualized by the association of tissue types to specified Hounsfield Unit (HU) values for fat, loose connective tissue or atrophic muscle, and normal muscle, including fascia and tendon. We show how results from these analyses can be presented as both average HU values and compositions with respect to total muscle volumes, demonstrating the reliability of these tools to monitor, assess and characterize muscle degeneration.

Quantitative Computed Tomography Image Analysis to Predict Pancreatic Neuroendocrine Tumor Grade

2021 ◽  
pp. 679-694
Author(s):  
Alessandra Pulvirenti ◽  
Rikiya Yamashita ◽  
Jayasree Chakraborty ◽  
Natally Horvat ◽  
Kenneth Seier ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Analysis ◽  
Ct Scan ◽  
Predictive Value ◽  
Quantitative Computed Tomography ◽  
Tumor Grade ◽  
Quantitative Image Analysis ◽  
Arterial Phase ◽  
Imaging Method ◽  
Quantitative Image

PURPOSE The therapeutic management of pancreatic neuroendocrine tumors (PanNETs) is based on pathological tumor grade assessment. A noninvasive imaging method to grade tumors would facilitate treatment selection. This study evaluated the ability of quantitative image analysis derived from computed tomography (CT) images to predict PanNET grade. METHODS Institutional database was queried for resected PanNET (2000-2017) with a preoperative arterial phase CT scan. Radiomic features were extracted from the primary tumor on the CT scan using quantitative image analysis, and qualitative radiographic descriptors were assessed by two radiologists. Significant features were identified by univariable analysis and used to build multivariable models to predict PanNET grade. RESULTS Overall, 150 patients were included. The performance of models based on qualitative radiographic descriptors varied between the two radiologists (reader 1: sensitivity, 33%; specificity, 66%; negative predictive value [NPV], 63%; and positive predictive value [PPV], 37%; reader 2: sensitivity, 45%; specificity, 70%; NPV, 72%; and PPV, 47%). The model based on radiomics had a better performance predicting the tumor grade with a sensitivity of 54%, a specificity of 80%, an NPV of 81%, and a PPV of 54%. The inclusion of radiomics in the radiographic descriptor models improved both the radiologists' performance. CONCLUSION CT quantitative image analysis of PanNETs helps predict tumor grade from routinely acquired scans and should be investigated in future prospective studies.

scholarly journals Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis

2018 ◽  
Vol 25 (4) ◽  
pp. 1034-1042 ◽  
Author(s):  
Marc A. Attiyeh ◽  
Jayasree Chakraborty ◽  
Alexandre Doussot ◽  
Liana Langdon-Embry ◽  
Shiana Mainarich ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Analysis ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Quantitative Computed Tomography ◽  
Ductal Adenocarcinoma ◽  
Survival Prediction ◽  
Tomography Image ◽  
Computed Tomography Image

scholarly journals The MITK Approach

2005 ◽  
Author(s):  
Ivo Wolf ◽  
Marco Nolden ◽  
Thomas Boettger ◽  
Ingmar Wegner ◽  
Max Schoebinger ◽  
...  
Keyword(s):  
Image Analysis ◽  
Medical Imaging ◽  
Medical Image ◽  
Medical Image Analysis ◽  
Interactive Systems ◽  
Analysis Software ◽  
Image Analysis Software ◽  
Visualization Toolkit ◽  
Key Features ◽  
2D And 3D

The Medical Imaging Interaction Toolkit (MITK) is an opensource toolkit for the development of interactive medical image analysis software. MITK is based on the open-source Insight Toolkit (ITK) and Visualization Toolkit (VTK) and extends them with features required for interactive systems. ITK is used for the algorithmic scope and general infrastructure, VTK for visualization. Key features of MITK are the coordination of multiple 2D and 3D visualizations of arbitrary data, a general interaction concept including undo/redo, and its extendibility and flexibility to create tailored applications due to its toolkit character and different layers of hidden complexity. The paper gives a brief introduction into the overall concepts and goals of the MITK approach. Suggestions and participation are welcome. MITK is available at www.mitk.org.

Hounsfield Unit Determination of Relative Risk for Incidental Durotomy by Quantitative Computed Tomography

2013 ◽  
Vol 13 (9) ◽  
pp. S154-S155
Author(s):  
Jerry Y. Du ◽  
Alexander Aichmair ◽  
Federico P. Girardi ◽  
Frank P. Cammisa ◽  
Darren R. Lebl
Keyword(s):  
Computed Tomography ◽  
Relative Risk ◽  
Quantitative Computed Tomography ◽  
Hounsfield Unit ◽  
Incidental Durotomy

scholarly journals Correlation Of Bone Mineral Density Measured In Quantitative Computed Tomography With Hounsfield Unit

2020 ◽  
Author(s):  
R Lalruatfela ◽  
Rahul P Kotian ◽  
Nitika C Panakkal
Keyword(s):  
Computed Tomography ◽  
Bone Mineral Density ◽  
Lumbar Spine ◽  
Trabecular Bone ◽  
Bone Mineral ◽  
Quantitative Computed Tomography ◽  
Hounsfield Unit ◽  
Mineral Density ◽  
Ct Attenuation ◽  
The Mean

Abstract Background: Bone mineral density scan (BMD) is a simple, non-invasive procedure used to assess the strength of the bones by measuring the composition of minerals mainly calcium in the bones. In this study, BMD was measured using Quantitative Computed Tomography (QCT) and Hounsfield unit (HU) in the lumbar spine and the values were correlated.Methods: 240 participants referred for CT Abdomen and CT Lumbar spine were scanned using 64 slice Brilliance CT. Using BMD software, three different vertebral bodies from L1-L3 were taken and ROI was placed at the central portion of the trabecular bone. Two references ROI one in retro spinal muscle and one in fat tissue was also placed. To measure CT attenuation value an ROI graphic tool was drawn at the trabecular bone. The average of BMD in QCT and HU value was taken from L1-L3. Pearson Correlation Coefficient was used to correlate QCT and HU values.Results: The mean BMD for the 21-40 age group was found to be 156.3 and 228.0 for QCT and HU respectively. Similarly, the mean BMD for 41-60 and 61-80 age groups was found to be 125.5, 173.6 and 109.1, 140.4 for QCT and HU respectively. The results showed a strong positive correlation between QCT and HU BMD (r = 0.94) with a p-value less than 0.001.Discussion: In our present study, 64.53% (n=155) were found to have normal BMD based on the WHO diagnostic category for spine BMD in QCT. Whereas 24.58% were found to have a low bone mass (osteopenia) and 10.83% were found to have osteoporosis. The equivalent mean HU was found to be 211.98 ±31.06, 139.64 ±18.58, 87.22 ±15.92 for normal, osteopenia and osteoporosis respectively.Conclusion: The study shows a strong correlation between QCT BMD with HU. Therefore, the CT attenuation technique can also be used to derive bone mineral density values from routine abdomen and lumbar spine MDCT for osteoporosis screening with no additional cost to the patient

High resolution peripheral quantitative computed tomography (HR-pQCT) und die klinische Relevanz der Resultate

2013 ◽  
Vol 22 (01) ◽  
pp. 13-17
Author(s):  
J. M. Patsch ◽  
R. Kocijan ◽  
H. Resch ◽  
J. Haschka
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
Quantitative Computed Tomography ◽  
Peripheral Quantitative Computed Tomography ◽  
Klinische Relevanz

ZusammenfassungKnochenstabilität ist durch Knochenvolumen und Mikroarchitektur des Knochens determiniert. Mittels HR-pQCT (high resolution peripheral quantitative computed tomography) steht eine nicht invasive Methode zur Verfügung, um die Mikroarchitektur des Knochens darzustellen. Die Resultate aus zahlreichen Studien geben Rückschlüsse auf unterschiedliche Strukturalterationen im Rahmen von Erkrankungen, die mit einem erhöhten Frakturrisiko einhergehen. Die Knochendichtemessung mittels DXA spiegelt das Frakturrisiko oft nicht adäquat wider. Umso entscheidender ist es, Risikofaktoren in der Wahl der Therapie zu berücksichtigen. Die klinische Relevanz der Resultate aus HR-pQCT-Messungen besteht derzeit dahingehend, dass wertvolle Informationen über Veränderungen der Mikroarchitektur auf Forschungsebene erhoben werden.

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