8/2/2016. Measures the degradation/distortion of the acquired image (relative to an ideal image) using a quantitative figure-of-merit
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1 Ke Li Assistant Professor Department of Medical Physics and Department of Radiology School of Medicine and Public Health, University of Wisconsin-Madison This work is partially supported by an NIH Grant No. R1CA and a GE Research Agreement Special thanks to the following colleagues and collaborators for their contributions to this presentation Dr. Guang-Hong Chen Dr. Jie Tang Dr. Jiang Hsieh John Garrett Daniel Gomez-Cardona Juan Pablo Cruz-Bastida Yongshuai Ge Adam Budde Dr. Timothy Szczykutowicz Quantitative image quality assessment of conventional linear CT systems Challenges in the quantitative image quality assessment of MBIR-based nonlinear CT systems Potential solutions 1
2 Measures the degradation/distortion of the acquired image (relative to an ideal image) using a quantitative figure-of-merit Advantages over qualitative image quality assessment: Reduces subjectivity associated with qualitative assessments Enables more meaningful comparison of CT systems across institutions and vendors Usually has higher efficiency and lower cost Frequency-independent metrics Noise magnitude CT number uniformity Contrast Contrast-to-noise ratio (CNR) CNR normalized by dose (CNRD) Frequency-dependent metrics Noise power spectrum (NPS) Modulation transfer function (MTF) Task-based detectability index Quantitative CT image quality assessment does not include: Visual determination of linear pair resolution (not quantitative) X-ray beam collimation accuracy (not an assessment of image quality) Measurement of dose-length product (assessment of CT dosimetry instead of image quality) 2
3 (mgy) 2 (HU 2 ) Standard kernel Bone Plus kernel Std. Bone plus HD Ultra MTF Frequency (mm-1) J. P. Cruz-Bastida et al. Med. Phys. 43, 2399 (216) Hi-Res mode with HD Ultra kernel (in vivo results) 2 exp( ul) exp( ul) 2 Patient Size L (mm) Courtesy of Dr. Szczykutowicz Szczykutowicz, T. P., Bour, R. K., Pozniak, M., & Ranallo, F. N. Journal of Applied Clinical Medical Physics, 16, 2 (215) 1 mgy 1 mgy 6 mgy Noise variance (σ 2 ) or noise standard deviation (σ) 1 4 N 2 1 ( xi x) N 1 i 1 1 mgy 1 mgy 6 mgy 1 3 K. Li, J. Tang, G.-H. Chen, Med. Phys. 41, 4196 (214) (mgy) 3
4 2 (HU 2 ).625 mm 1.25 mm z mgy 5 mgy 2 mgy 6 mgy 2.5 mm 5. mm Slice thickness (mm) Contrast C x x feature background W/L: 15/3 Contrast = 1 HU Contrast = 225 HU Contrast = 35 HU Contrast = 4 HU Contrast-to-noise ratio (CNR) CNR C W/L: 15/3 4
5 CNR CNR 4 mgy 8 mgy CNR mgy 16 mgy R 2 =.994 W/L: 3/ Standard kernel Lung kernel Bone+ kernel Edge kernel Highest CNR Fracture least visible Lowest CNR Fracture most visible Signal present Conventional CT Signal absent Differential phase contrast CT DPC-CT noise absorption CT noise Same CNR Different detection performance AUC 1 AUC.88 K. Li et al., Proc. SPIE, 8313, 83131L(212) 5
6 NPS (HU 2 mm 2 ) Normalized NPS (A.U.) Same CNR, different object detectability Contrast = 3 HU W/L: 5/16 CTDIvol = 16 mgy Noise power spectrum (NPS) x y NPS DFT(ROI-ROI) N N x y 2 D. Gomez-Cardona et al., Med. Phys. 43, 4495 (216) The shape of the NPS is independent on radiation dose 12 NPS () 5 mas 2.5 Normalized NPS () 12.5 mas 1 25 mas 5 mas mas 2 mas mas f xy (mm -1 ) f xy (mm -1 ) K. Li, J. Tang, G.-H. Chen, Med. Phys. 41, 4196 (214) 6
7 Point Spread Function Point Spread Function NPS magnitude is independent on contrast level Contrast = 1 HU Contrast = 225 HU Contrast = 35 HU Contrast = 4 HU W/L: 15/3 Point spread function (PSF) or modulation transfer function (MTF) 1.2 HD Std. HD Bone plus HD Edge HD Lung MTF.8 Standard Lung Frequency (mm-1) J. P. Cruz-Bastida et al. Med. Phys. 43, 2399 (216) Bone plus Edge Spatial resolution is independent on dose and contrast.25 independence.25 Contrast independence 16 mgy 3 HU 6 HU.2 12 mgy.2 8 mgy 1 HU 4 mgy 225 HU.15 Question: Are these assumptions.15still valid in MBIR? Position (mm) Position (mm) Li, Garrett, Ge, Chen, Med. Phys. 41, (214) 7
8 2 (HU 2 ) projection data final image update the estimated image forward projection estimated image Noise magnitude is independent on contrast level Li et al., RSNA 214 Annual Meeting MBIR noise-only reconstruction image Solomon and Samei, Proc SPIE 8668, 86684M (213) Solomon and Samei, Med. Phys. 41, 9198 (214) MBIR noise-only image Noise variance is inversely proportional to radiation dose 1 4 (fitting) MBIR (mgy) : MBIR: 2 2 1? 8
9 NPS (HU 2 mm 2 ) Normalized NPS (A.U.) 2 (HU 2 ) The shape of the NPS independent on radiation dose NPS NPS of MBIR (Veo) Normalized NPS NPS of (Veo) MBIR 6 5 mas 5 mas mas 12.5 mas 25 mas 25 mas 45 mas 5 mas 1 mas 1 mas 2 mas 2 mas 3 3 mas 3 mas f xy (mm -1 ) f xy (mm -1 ) K. Li, J. Tang, G.-H. Chen, Med. Phys. 41, 4196 (214) Noise variance is inversely proportional to slice thickness.625 mm 1.25 mm 2.5 mm 5. mm z Veo 1 2 Veo Matched W/L: 5/; CTDI vol = 4 mgy Slice thickness z (mm) K. Li, J. Tang, G.-H. Chen, Med. Phys. 41, 4196 (214).625 mm thin thick 5. mm Veo thin Veo thick Veo.625 mm Veo 5. mm HIPAA-compliant prospective human subject study, IRB-approved 9
10 Slice sensitivity profile Point Spread Function Point Spread Function Slice sensitivity profile K. Li, J. Tang, G.-H. Chen, Med. Phys. 41, 4196 (214) Spatial resolution is independent on dose and contrast contrast = 35 HU contrast = 1 HU mgy.2 12 mgy 8 mgy 4 mgy Position (mm) Position (mm) Li, Garrett, Ge, Chen, Med. Phys. 41, (214) The Z resolution is independent on dose and contrast.15.1 Contrast = 27 HU 25% dose (Veo) 5% dose (Veo) 75% dose (Veo) 1% dose (Veo) 1% dose ().15.1 Contrast = 12 HU 25% dose (Veo) 5% dose (Veo) 75% dose (Veo) 1% dose (Veo) 1% dose () z position (mm) z position (mm) Li, Garrett, Ge, Chen, Med. Phys. 41, (214) 1
11 Noise assessments Contrast dependence Modified dose dependence Magnitude NPS shape Modified slice thickness dependence Magnitude NPS shape Spatial resolution assessments Contrast dependence dependence Spatial resolution assessments at low-contrast and low dose conditions are extremely challenging High contrast, high dose Low contrast, low dose Task-based spatial resolution Repeated scans Noise ensemble Task-based detectability Task-based NPS Task-based edge noise Object edge Gradient image Edge central line Normal cuts Edge profile at arbitrary location High contrast Low contrast Richard et al., Towards task-based assessment of CT performance: System and objective MTF across different reconstruction algorithm. Med. Phys. 39, 4115 (212) Li et al., Statistical Model Based Iterative Reconstruction (MBIR) in clinical CT systems: Part II. Experimental assessment of spatial resolution performance. Med. Phys. 41, 71911(214) Yu et al., Technical Note: Measuring contrast-and noise-dependent spatial resolution of an iterative reconstruction method in CT using ensemble averaging. Med. Phys. 42, 2261 (215) 11
12 NPS peak position f peak (mm -1 ) Width PSF of width PSF (mm) (mm) Width PSF of width PSF (mm) (mm) Veo (mm) % % Contrast (HU) 1% 75% Li, Garrett, Ge, Chen, Med. Phys. 41, (214) 1 At each given exposure level, (mm) the spatial Veo resolution of Veo improves with.8.8 higher contrast level.7 At each given contrast level, the spatial.6.6 resolution of Veo improves with higher dose level.5.4 At some intermediate contrast/dose.4 level, the spatial resolutions of Veo and becomes equivalent 1%.2 75% % % Contrast (HU) Li, Garrett, Ge, Chen, Med. Phys. 41, (214).8.4 (fitting) Veo Veo (fitting) : f peak const..2.1 f MBIR: 1 5 peak dose (mgy) 12
13 2 (HU 2 ) 2 (HU 2 ) 1 3 Veo 2 1 : z 1 2 MBIR: 2 1 z Slice thickness z (mm) (fitting) Veo Veo (fitting) 2 1 : 2 1 MBIR: (mgy).4±.1 1.±.1 Reduced dose Reference dose HIPAA-compliant and IRB-approved D. Gomez-Cardona et al., 215 AAPM Annual Meeting 13
14 ma ma Noise = 15 HU (, 65 mgy) Noise = 15 HU (MBIR,.6 mgy) Problem formulation kv,ma Practical solution argmin (kv,ma) s.t. d'(kv,ma) d ' Black lines: Iso-dose lines; Iso-dose White map lines: Iso-detectability Iso-detectability Iso-d lines map lines () d ' kv kv Li et al., Med. Phys. 42, 529 (215) Routine dose scan Reduced dose scan 12kV 65 ma 19.4 mgy 8 kv 275 ma 2.4 mgy MBIR HIPAA-compliant and IRB-approved Li et al., Med. Phys. 42, 529 (215) 14
15 Major challenges in quantitative image quality assessment of MBIR Violation of several basic assumptions and relationships in CT image quality assessment Nonlinearity of the reconstruction method determines that there is no theoretical basis in deriving the modified relationships For example, how does the shape of the NPS quantitatively vary with radiation dose Potential solutions in address these challenges Empirical relationships between image quality and CT system parameters have been found Try to use frequency-dependent metrics (e.g NPS) rather than zero-frequency metrics (e.g. CNR) Be task-specific rather than task-generic Perform repeated acquisitions rather than shifting an ROI Use model observer detectability to combine noise and spatial resolution metrics with task function Thank You 45 15
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