Multiparameter MRI assessment of normal-appearing and diseased vertebral bone marrow

Biffar, Andreas; Baur‐Melnyk, Andrea; Schmidt, Gerwin P.; Reiser, Maximilian; Dietrich, Olaf

doi:10.1007/s00330-010-1833-4

Cited by 28 publications

(14 citation statements)

References 39 publications

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“…As in previous studies, DW-EPI showed more susceptibility heterogeneities, resulting in distortion artifacts, than DW single-shot TSE [10]. The ADCs of osteoporotic and malignant fractures using DW-EPI did not differ significantly, whereas the ADCs of osteoporotic and malignant fractures determined with DW single-shot TSE differed significantly but showed a large overlap.…”

Section: Geith Et Alsupporting

confidence: 71%

“…

1083of signal intensities (SIs) on diffusion-weighted (DW) steady-state free-precession (SSFP), echo-planar imaging (EPI), single-shot turbo spin-echo (TSE), and opposed-phase sequences as well as the quantitative measurement of apparent diffusion coefficients (ADCs) and the value of quantitative chemical-shift imaging to improve specificity [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. Because there have been partially contradicting statements about the value of these techniques and there is still uncertainty whether quantification is really necessary and how it improves specificity,

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confidence: 99%

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Comparison of Qualitative and Quantitative Evaluation of Diffusion-Weighted MRI and Chemical-Shift Imaging in the Differentiation of Benign and Malignant Vertebral Body Fractures

Geith

Schmidt

Biffar

et al. 2012

American Journal of Roentgenology

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The DW-PSIF sequence (delta = 3 ms) had the highest accuracy in differentiating benign from malignant vertebral fractures. Quantitative chemical-shift imaging and quantitative DW single-shot TSE imaging had a lower accuracy than DW-PSIF imaging because of a large overlap. Qualitative assessment of opposed-phase, DW-EPI, and DW single-shot TSE sequences and quantitative assessment of the DW-EPI sequence were not suitable for distinguishing between benign and malignant vertebral fractures.

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Section: Geith Et Alsupporting

confidence: 71%

“…

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mentioning

confidence: 99%

Comparison of Qualitative and Quantitative Evaluation of Diffusion-Weighted MRI and Chemical-Shift Imaging in the Differentiation of Benign and Malignant Vertebral Body Fractures

Geith

Schmidt

Biffar

et al. 2012

American Journal of Roentgenology

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“…Biffar et al demonstrated that the use of FLDA to combine ADC and T 2 relaxation times of water in the vertebral bone marrow allowed for increased sensitivity and accuracy in the separation between malignant and benign lesions compared to using each classifier individually [32]. In the present study, a significant correlation between tumor ADC changes and relative tumor growth was found in the control group but not in the therapy group.…”

Section: Discussionsupporting

confidence: 44%

“…A meaningful combined evaluation of tumor morphology and DW-MRI could reduce the individual limitations of each approach, allowing for non-invasive response monitoring during initial treatment. Such a combination is constituted by Fisher's linear discriminant analysis (FLDA) [31], which has been demonstrated to increase the accuracy to separate between malignant and benign lesions in the vertebral bone marrow by incorporating ADC and T 2 relaxation time values compared to using each classifier individually [32].…”

Section: Introductionmentioning

confidence: 99%

Monitoring Early Response to Anti-Angiogenic Therapy: Diffusion-Weighted Magnetic Resonance Imaging and Volume Measurements in Colon Carcinoma Xenografts

et al. 2014

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ObjectivesTo evaluate the use of diffusion-weighted MRI (DW-MRI) and volume measurements for early monitoring of antiangiogenic therapy in an experimental tumor model.Materials and Methods23 athymic nude rats, bearing human colon carcinoma xenografts (HT-29) were examined before and after 6 days of treatment with regorafenib (n = 12) or placebo (n = 11) in a clinical 3-Tesla MRI. For DW-MRI, a single-shot EPI sequence with 9 b-values (10–800 s/mm2) was used. The apparent diffusion coefficient (ADC) was calculated voxelwise and its median value over a region of interest, covering the entire tumor, was defined as the tumor ADC. Tumor volume was determined using T2-weighted images. ADC and volume changes between first and second measurement were evaluated as classifiers by a receiver-operator-characteristic (ROC) analysis individually and combined using Fisher's linear discriminant analysis (FLDA).ResultsAll ADCs and volumes are stated as median±standard deviation. Tumor ADC increased significantly in the therapy group (0.76±0.09×10−3 mm2/s to 0.90±0.12×10−3 mm2/s; p<0.001), with significantly higher changes of tumor ADC than in the control group (0.10±0.11×10−3 mm2/s vs. 0.03±0.09×10−3 mm2/s; p = 0.027). Tumor volume increased significantly in both groups (therapy: 347.8±449.1 to 405.3±823.6 mm3; p = 0.034; control: 219.7±79.5 to 443.7±141.5 mm3; p<0.001), however, the therapy group showed significantly reduced tumor growth (33.30±47.30% vs. 96.43±31.66%; p<0.001). Area under the curve and accuracy of the ADC-based ROC analysis were 0.773 and 78.3%; and for the volume change 0.886 and 82.6%. The FLDA approach yielded an AUC of 0.985 and an accuracy of 95.7%.ConclusionsRegorafenib therapy significantly increased tumor ADC after 6 days of treatment and also significantly reduced tumor growth. However, ROC analyses using each parameter individually revealed a lack of accuracy in discriminating between therapy and control group. The combination of both parameters using FLDA substantially improved diagnostic accuracy, thus highlighting the potential of multi-parameter MRI as an imaging biomarker for non-invasive early tumor therapy monitoring.

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“…FLDA is a statistical method to reduce the dimensionality of data; by finding an optimal linear combination of a given feature set, the differentiation between two (or more) classes can be improved [20][21][22]. FLDA was applied using either two out of three alternately combined parameters or using all three parameters as input.…”

Section: Part 2 -Differentiation Of Arterial and Venous Vesselsmentioning

confidence: 99%

Validation of a method to differentiate arterial and venous vessels in CT perfusion data using linear combinations of quantitative time-density curve characteristics

Havla

Schneider

Thierfelder³

et al. 2015

Eur Radiol

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• For classification of cerebral vasculature, time-to-peak has the best single-parameter accuracy. • Fisher's linear discriminant analysis improves the performance of the individual classifiers. • Combining signal maximum and time-to-peak parameters significantly increased the classifying potential. • Pre-processing of time-density-curves by Gaussian filtering or fitting can improve diagnostic accuracy.

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Multiparameter MRI assessment of normal-appearing and diseased vertebral bone marrow

Cited by 28 publications

References 39 publications

Comparison of Qualitative and Quantitative Evaluation of Diffusion-Weighted MRI and Chemical-Shift Imaging in the Differentiation of Benign and Malignant Vertebral Body Fractures

Comparison of Qualitative and Quantitative Evaluation of Diffusion-Weighted MRI and Chemical-Shift Imaging in the Differentiation of Benign and Malignant Vertebral Body Fractures

Monitoring Early Response to Anti-Angiogenic Therapy: Diffusion-Weighted Magnetic Resonance Imaging and Volume Measurements in Colon Carcinoma Xenografts

Validation of a method to differentiate arterial and venous vessels in CT perfusion data using linear combinations of quantitative time-density curve characteristics

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