Can the specificity of MRI breast imaging be improved by fusing 3D MRI volume data sets with FDG PET?

2005 ◽  
Author(s):  
M.E. Noz ◽  
L. Moy ◽  
F. Ponzo ◽  
E.L. Kramer ◽  
G.Q. Maguire
Keyword(s):  
Fdg Pet ◽  
Breast Imaging ◽  
Data Sets ◽  
Volume Data ◽  
3D Mri

Time consumption and quality of an automated fusion tool for SPECT and MRI images of the brain

2003 ◽  
Vol 42 (05) ◽  
pp. 215-219
Author(s):  
G. Platsch ◽  
A. Schwarz ◽  
K. Schmiedehausen ◽  
B. Tomandl ◽  
W. Huk ◽  
...  
Keyword(s):  
Data Sets ◽  
3D Mri ◽  
Clinical Routine ◽  
Fusion Procedure ◽  
3D Data ◽  
Mri Scans ◽  
2D Data ◽  
Time Required ◽  
The Brain ◽  
Manual Correction

Summary: Aim: Although the fusion of images from different modalities may improve diagnostic accuracy, it is rarely used in clinical routine work due to logistic problems. Therefore we evaluated performance and time needed for fusing MRI and SPECT images using a semiautomated dedicated software. Patients, material and Method: In 32 patients regional cerebral blood flow was measured using 99mTc ethylcystein dimer (ECD) and the three-headed SPECT camera MultiSPECT 3. MRI scans of the brain were performed using either a 0,2 T Open or a 1,5 T Sonata. Twelve of the MRI data sets were acquired using a 3D-T1w MPRAGE sequence, 20 with a 2D acquisition technique and different echo sequences. Image fusion was performed on a Syngo workstation using an entropy minimizing algorithm by an experienced user of the software. The fusion results were classified. We measured the time needed for the automated fusion procedure and in case of need that for manual realignment after automated, but insufficient fusion. Results: The mean time of the automated fusion procedure was 123 s. It was for the 2D significantly shorter than for the 3D MRI datasets. For four of the 2D data sets and two of the 3D data sets an optimal fit was reached using the automated approach. The remaining 26 data sets required manual correction. The sum of the time required for automated fusion and that needed for manual correction averaged 320 s (50-886 s). Conclusion: The fusion of 3D MRI data sets lasted significantly longer than that of the 2D MRI data. The automated fusion tool delivered in 20% an optimal fit, in 80% manual correction was necessary. Nevertheless, each of the 32 SPECT data sets could be merged in less than 15 min with the corresponding MRI data, which seems acceptable for clinical routine use.

scholarly journals Contrast-driven approach to intracranial segmentation using a combination of T2- and T1-weighted 3D MRI data sets

2006 ◽  
Vol 24 (4) ◽  
pp. 790-795 ◽  
Author(s):  
Gunther Helms ◽  
Kai Kallenberg ◽  
Peter Dechent
Keyword(s):  
Data Sets ◽  
3D Mri

Transforming data into information

2003 ◽  
Vol 47 (2) ◽  
pp. 43-51 ◽  
Author(s):  
M.B. Beck ◽  
Z. Lin
Keyword(s):  
High Volume ◽  
Recursive Estimation ◽  
Data Sets ◽  
Monitoring Networks ◽  
Volume Data ◽  
Demand Pull ◽  
Variable Character ◽  
History Of ◽  
On Line ◽  
Automated Instruments

In spite of a long history of automated instruments being deployed in the water industry, only recently has the difficulty of extracting timely insights from high-grade, high-volume data sets become an important problem. Put simply, it is now relatively easy to be “data-rich”, much less easy to become “information-rich". Whether the availability of so many data arises from “technological push” or the “demand pull” of practical problem solving is not the subject of discussion. The paper focuses instead on two issues: first, an outline of a methodological framework, based largely on the algorithms of (on-line) recursive estimation and involving a sequence of transformations to which the data can be subjected; and second, presentation and discussion of the results of applying these transformations in a case study of a biological system of wastewater treatment. The principal conclusion is that the difficulty of transforming data into information may lie not so much in coping with the high sampling intensity enabled by automated monitoring networks, but in coming to terms with the complexity of the higher-order, multi-variable character of the data sets, i.e., in interpreting the interactions among many contemporaneously measured quantities.

Linear accuracy and reliability of volume data sets acquired by two CBCT-devices and an MSCT using virtual models: A comparativein-vitrostudy

2015 ◽  
Vol 74 (1) ◽  
pp. 51-59 ◽  
Author(s):  
Johannes Wikner ◽  
Henning Hanken ◽  
Christine Eulenburg ◽  
Max Heiland ◽  
Alexander Gröbe ◽  
...  
Keyword(s):  
Data Sets ◽  
Volume Data ◽  
Virtual Models ◽  
Linear Accuracy

scholarly journals Visualizing Vertebrate Embryos with Episcopic 3D Imaging Techniques

2009 ◽  
Vol 9 ◽  
pp. 1423-1437 ◽  
Author(s):  
Stefan H. Geyer ◽  
Timothy J. Mohun ◽  
Wolfgang J. Weninger
Keyword(s):  
3D Imaging ◽  
Imaging Techniques ◽  
Three Dimensional ◽  
Computer Models ◽  
Hereditary Diseases ◽  
Data Sets ◽  
Data Generation ◽  
Volume Data ◽  
Vertebrate Embryos ◽  
Technical Principles

The creation of highly detailed, three-dimensional (3D) computer models is essential in order to understand the evolution and development of vertebrate embryos, and the pathogenesis of hereditary diseases. A still-increasing number of methods allow for generating digital volume data sets as the basis of virtual 3D computer models. This work aims to provide a brief overview about modern volume data–generation techniques, focusing on episcopic 3D imaging methods. The technical principles, advantages, and problems of episcopic 3D imaging are described. The strengths and weaknesses in its ability to visualize embryo anatomy and labeled gene product patterns, specifically, are discussed.

Factors influencing 3D-MRI diagnosis in preoperative breast cancer patients

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 620-620
Author(s):  
K. Hisamatsu ◽  
W. Takiyama ◽  
R. Sakabe ◽  
Y. Satou ◽  
S. Saeki ◽  
...  
Keyword(s):  
Tumor Size ◽  
Breast Imaging ◽  
False Negative ◽  
Breast Conserving Surgery ◽  
Breast Cancer Patients ◽  
3D Mri ◽  
3D Images ◽  
Intraductal Spread ◽  
Imaging Tool ◽  
Factors Influencing

620 Background: We presented 3D-MRI will be the useful breast imaging tool in diagnosing intraductal spread and tumor size in breast cancer patients. (ASCO 2008).To do breast conserving surgery, careful management was needed in cases with widely ductal spreading and multifocal lesion. This study was to evaluate factors influencing false negative diagnosis and multifocal types of 3D-MRI, retrospectively. Methods: From July 2000, pre-operative 3D-MRI was underwent 488 cases and images were obtained 479 cases (98%). These patients could be divided into three groups according to 3D-MRI images: pattern 1) localized type (273 cases), 2) widely enhanced type (106 cases) and 3) multi-focal type (100 cases). From April 2005, resected specimen was serially step cut and total specimens were microscopically evaluated. Tumor size in 3D-MRI was 1cm over smaller than resected specimens were defined false negative cases. Investigated factors influencing 3D-MRI were age, patterns of 3D-MRI images, presence of pre-operative chemotherapy, histological type, histological grade, microscopical invasive tumor size (mm) and presence of ductal spreading. Results: The rate of histological confirmed intraductal spread were seen in 58% (158/273cases), 89% (94/106 cases) of patients with 3D-MRI pattern 1) and 2), respectively. Tumor size was correlated between MRI and specimens, significantly (n = 162, r = 06706, p < 0.001). Factors influencing false negative diagnosis of 3D-MRI were presence of pre-operative chemotherapy (p < 0.05), presence of ductal spreading (p < 0.001) and patterns of 3D-MRI images (p < 0.05). In the cases with multi-focal 3D- images, there were only 11(11/41, 26%) cases with true multifocal lesions by total specimens examination. Selection for breast conserving surgery and margin width were based by 3D-MRI images. The proportion of breast-conserved surgery were obtained 90% (437/488 cases) and local failure seen only 6 cases (local failure rate 1.4%) in 3D-MRI guided surgery. (median follow up 52 months). Conclusions: These results suggest that MRI will be the useful breast imaging tool, but caution will be needed in cases with pre-operative systemic therapy, cases expected intraductal spread by imaging tools and cases with multi-focal 3D- images. No significant financial relationships to disclose.

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