scholarly journals Morphologic Changes of Mammary Carcinomas in Mice over Time as Monitored by Flat-Panel Detector Volume Computed Tomography

Neoplasia ◽  
2008 ◽  
Vol 10 (7) ◽  
pp. 663-673 ◽  
Author(s):  
Jeannine Missbach-Guentner ◽  
Christian Dullin ◽  
Sarah Kimmina ◽  
Marta Zientkowska ◽  
Melanie Domeyer-Missbach ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Flat Panel ◽  
Mammary Carcinomas ◽  
Flat Panel Detector ◽  
Volume Computed Tomography ◽  
Morphologic Changes ◽  
Over Time ◽  
Detector Volume

TH-D-L100J-04: Dose and Image Quality of Flat-Panel Detector Volume Computed Tomography for Sinus Imaging

2007 ◽  
Vol 34 (6Part23) ◽  
pp. 2634-2634 ◽  
Author(s):  
J Alspaugh ◽  
E Christodoulou ◽  
M Goodsitt ◽  
J Stayman
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Flat Panel ◽  
Flat Panel Detector ◽  
Volume Computed Tomography ◽  
Detector Volume

scholarly journals Flat-Panel Detector—Based Volume Computed Tomography: A Novel 3D Imaging Technique to Monitor Osteolytic Bone Lesions in a Mouse Tumor Metastasis Model

Neoplasia ◽  
2007 ◽  
Vol 9 (9) ◽  
pp. 755-765 ◽  
Author(s):  
Jeannine Missbach-Guentner ◽  
Christian Dullin ◽  
Marta Zientkowska ◽  
Melanie Domeyer-Missbach ◽  
Sarah Kimmina ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Tumor Metastasis ◽  
3D Imaging ◽  
Imaging Technique ◽  
Bone Lesions ◽  
Mouse Tumor ◽  
Flat Panel ◽  
Flat Panel Detector ◽  
Volume Computed Tomography ◽  
Metastasis Model

Planar cone-beam computed tomography with a flat-panel detector

2015 ◽  
Vol 10 (12) ◽  
pp. T12004-T12004 ◽  
Author(s):  
S.H. Kim ◽  
D.W. Kim ◽  
H. Youn ◽  
D. Kim ◽  
S. Kam ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Cone Beam ◽  
Flat Panel ◽  
Flat Panel Detector

Reproducibility of trabecular structure analysis using flat-panel volume computed tomography

2009 ◽  
Vol 38 (10) ◽  
pp. 1003-1008 ◽  
Author(s):  
Arnold C. Cheung ◽  
Miriam A. Bredella ◽  
Ma’moun Al Khalaf ◽  
Michael Grasruck ◽  
Christianne Leidecker ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Structure Analysis ◽  
Trabecular Structure ◽  
Flat Panel ◽  
Volume Computed Tomography

scholarly journals Semi-Automatic Classification of Skeletal Morphology in Genetically Altered Mice Using Flat-Panel Volume Computed Tomography

PLoS Genetics ◽  
2007 ◽  
Vol 3 (7) ◽  
pp. e118 ◽  
Author(s):  
Christian Dullin ◽  
Jeannine Missbach-Guentner ◽  
Wolfgang F Vogel ◽  
Eckhardt Grabbe ◽  
Frauke Alves
Keyword(s):  
Computed Tomography ◽  
Automatic Classification ◽  
Flat Panel ◽  
Skeletal Morphology ◽  
Volume Computed Tomography

scholarly journals Flat Panel Computed Tomography Pooled Blood Volume and Infarct Prediction in Endovascular Stroke Treatment

Stroke ◽  
2019 ◽  
Vol 50 (11) ◽  
pp. 3274-3276 ◽  
Author(s):  
Aneka Mueller ◽  
Marlies Wagner ◽  
Elke Hattingen ◽  
Alexander Seiler ◽  
Se-Jong You ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Endovascular Treatment ◽  
Blood Volume ◽  
Cerebral Artery ◽  
Clinical Decision Making ◽  
Infarct Volume ◽  
Multislice Ct ◽  
Flat Panel ◽  
Flat Panel Detector ◽  
Angiography Suite

Background and Purpose— Patients with large-vessel stroke frequently need to be transferred to comprehensive stroke centers for endovascular treatment. An update of physiological perfusion parameters and stroke progression on arrival is desirable. We examined the reliability of preinterventional pooled blood volume (PBV)-maps acquired by flat-panel detector computed tomography (CT) in the interventional angiography suite. Methods— The volumes of preinterventional perfusion deficit in flat-panel detector CT-PBV source images were compared with final infarct volume on follow-up multislice-CT after endovascular treatment of 29 consecutive patients with occlusion of the middle cerebral artery (MCA) or the distal internal carotid artery (ICA). Results— Endovascular treatment was successful in 26 patients (Thrombolysis in Cerebral Infarction, 2b-3). Overall, the median preinterventional PBV-deficit was 9×larger than median final infarct volume on multislice-CT (86.4 mL [10.3; 111.6] versus 9.6 mL [3.6; 36.8]). This was especially evident in the subgroup of successful recanalization (PBV-deficit: 87.5 mL [10.6; 115.1], final infarct: 8.7 mL [3.6; 29]). In futile recanalization, the final infarct tended to be underestimated (PBV-deficit: 86.4 mL [5.9; –] and final infarct: 116.4 mL [3.5; –]). Conclusions— Flat panel detector CT-PBV is not reliable in predicting the final infarct volume and should not be used in clinical decision making for endovascular treatment of acute cerebral artery occlusions.

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