Data transformations for variance stabilization in the statistical assessment of quantitative imaging biomarkers

2019 ◽  
Author(s):  
Qi Gong ◽  
Qin Li ◽  
Marios A. Gavrielides ◽  
Nicholas A. Petrick
Keyword(s):  
Quantitative Imaging ◽  
Imaging Biomarkers ◽  
Statistical Assessment ◽  
Data Transformations ◽  
Variance Stabilization ◽  
Quantitative Imaging Biomarkers

Data transformations for statistical assessment of quantitative imaging biomarkers: Application to lung nodule volumetry

2020 ◽  
Vol 29 (9) ◽  
pp. 2749-2763
Author(s):  
Qi Gong ◽  
Qin Li ◽  
Marios A Gavrielides ◽  
Nicholas Petrick
Keyword(s):  
Computed Tomography ◽  
Quantitative Imaging ◽  
Lung Nodule ◽  
Imaging Biomarkers ◽  
Statistical Assessment ◽  
Variance Stabilization ◽  
Computed Tomography Images ◽  
Quantitative Imaging Biomarkers ◽  
Nodule Volume ◽  
Box Cox Transformation

Variance stabilization is an important step in the statistical assessment of quantitative imaging biomarkers. The objective of this study is to compare the Log and the Box–Cox transformations for variance stabilization in the context of assessing the performance of a particular quantitative imaging biomarker, the estimation of lung nodule volume from computed tomography images. First, a model is developed to generate and characterize repeated measurements typically observed in computed tomography lung nodule volume estimation. Given this model, we derive the parameter of the Box–Cox transformation that stabilizes the variance of the measurements across lung nodule volumes. Second, simulated, phantom, and clinical datasets are used to compare the Log and the Box–Cox transformations. Two metrics are used for quantifying the stability of the measurements across the transformed lung nodule volumes: the coefficient of variation for the standard deviation and the repeatability coefficient. The results for simulated, phantom, and clinical datasets show that the Box–Cox transformation generally had better variance stabilization performance compared to the Log transformation for lung nodule volume estimates from computed tomography scans.

scholarly journals Quantitative imaging biomarkers: A review of statistical methods for technical performance assessment

2014 ◽  
Vol 24 (1) ◽  
pp. 27-67 ◽  
Author(s):  
David L Raunig ◽  
Lisa M McShane ◽  
Gene Pennello ◽  
Constantine Gatsonis ◽  
Paul L Carson ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Statistical Methods ◽  
Quantitative Imaging ◽  
Imaging Biomarkers ◽  
Technical Performance ◽  
Quantitative Imaging Biomarkers

scholarly journals Correction: Global spectral and local molecular connects for optical coherence tomography features to classify oral lesions towards unravelling quantitative imaging biomarkers

RSC Advances ◽  
2016 ◽  
Vol 6 (48) ◽  
pp. 42612-42612
Author(s):  
Satarupa Banerjee ◽  
Swarnadip Chatterjee ◽  
Anji Anura ◽  
Jitamanyu Chakrabarty ◽  
Mousumi Pal ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Quantitative Imaging ◽  
Imaging Biomarkers ◽  
Oral Lesions ◽  
Optical Coherence ◽  
Quantitative Imaging Biomarkers

Correction for ‘Global spectral and local molecular connects for optical coherence tomography features to classify oral lesions towards unravelling quantitative imaging biomarkers’ by Satarupa Banerjee et al., RSC Adv., 2016, 6, 7511–7520.

scholarly journals Quantitative Imaging Biomarkers for 90Y Distribution on Bremsstrahlung SPECT After Resin-Based Radioembolization

2019 ◽  
Vol 60 (8) ◽  
pp. 1066-1072
Author(s):  
Isabel Schobert ◽  
Julius Chapiro ◽  
Nariman Nezami ◽  
Charlie A. Hamm ◽  
Bernhard Gebauer ◽  
...  
Keyword(s):  
Quantitative Imaging ◽  
Imaging Biomarkers ◽  
Quantitative Imaging Biomarkers

scholarly journals Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE‐MRI derived biomarkers in multicenter oncology trials

2019 ◽  
Vol 49 (7) ◽  
pp. i-i ◽  
Author(s):  
Amita Shukla‐Dave ◽  
Nancy A. Obuchowski ◽  
Thomas L. Chenevert ◽  
Sachin Jambawalikar ◽  
Lawrence H. Schwartz ◽  
...  
Keyword(s):  
Quantitative Imaging ◽  
Imaging Biomarkers ◽  
Dce Mri ◽  
Quantitative Imaging Biomarkers
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