MRI Image Quality Assessment

Transcription

1 in partnership with MRI Image Quality Assessment David Collins CR-UK Cancer Imaging Centre, The Institute of Cancer Research Making the discoveries that defeat cancer

2 Overview Current Practice Quality Assurance and Acceptance testing Emerging applications Quantitative DCE-MRI, DWI Whole Body

3 Acceptance Testing Current Practice We measure 1, 2 : Resonance Frequency Signal to Noise Spatial Linearity Spatial Resolution Slice Thickness Slice Position/Separation Image Uniformity Artifacts; Phase and other ghosts Many others Dynamic and Quantitative Measurements, are the above sufficient? 1. Price et al Med Phys 17(2) Mar/Apr/ Och Med Phys 19(1) Jan/Feb 1992

4 Acceptance Testing Current Practice We rarely measure as specified 1, 2 : Eddy Currents (sequence programming or integrator circuit required) Slice Profiles (1D FT method) Nutation Angle calibration (vendor restrictions on user) SNR (Modern scanners have many Rx channels ) B0 (Phase images not produced), spectroscopy not always an option, vendors may provide field maps. B1 uniformity 1. Price et al Med Phys 17(2) Mar/Apr/ Och Med Phys 19(1) Jan/Feb 1992

5 Acceptance Testing Current Practice We rarely measure as specified 1, 2 : Eddy Currents (sequence programming or integrator circuit required) Slice Profiles (1D FT method) Nutation Angle calibration (vendor restrictions on user) SNR (Modern scanners have many Rx channels ) B0 (Phase images not produced), spectroscopy not always an option, vendors do provide field maps. B1 uniformity We rely on vendor installation tests and procedures, it is now vitally important to engage a site physicist in this process 1. Price et al Med Phys 17(2) Mar/Apr/ Och Med Phys 19(1) Jan/Feb 1992

6 Acceptance Testing Current Practice How long should we spend performing acceptance testing? At the Royal Marsden/ICR we allocate one week. At least two senior clinical scientists with trainees. We use a range of vendor, Eurospin test objects and home built test objects. Some sites (DGH) perform zero testing.

7 Examples of gradient linearity correction Previously gradient linearity required extensive evaluation and correction if MR images were used for R/T planning 1 Vendors now provide gradient linearity correction as either a default or selection option 1. Doran et al. Medical Physics 2005

8 NSA=2, Slice thickness=3mm Geometrical Distortions in Spin Echo Sequences Coronal Orientation NSA=1, Slice thickness=5mm NSA=2, Slice thickness=5mm NSA=2, Slice thickness=3mm, Without Distortion Correction Sequence 5mm, 1NSA 5mm, 2NSA 3mm, 2NSA 3mm, 2NSA, without Dist Cor 3mm, 2NSA, with Body Coil x 0.42 y 0.42 x 0.83 y 0.42 x 1.25 y 0.42 x 0.83 y 0 x 0.83 y 0 % deviation NSA=2, Slice thickness=3mm With Body Coil

9 Custom-built Quality Assurance equipment 1. 3T Achieva, without and with 3D distortion correction 2. Test object dimensions: 440mm LR, 400mm HF, 250mm AP 1.Tanner et al, Phys Med Biol 2000 Aug;45(8): Doran et al. Medical Physics 2005

10 Gradient Linearity QA Test Object Rapid 3D DCE-MRI protocol coronal acquisition No Gradient Correction Vendor Gradient Correction Dimensions 28 x 28cm Virtualscopics test object

11 Gradient Linearity QA Test Object Rapid 3D DCE-MRI protocol coronal acquisition No Gradient Correction Vendor Gradient Correction Dimensions 28 x 28cm Virtualscopics test object

12 SNR Well established tests for conventional Spin Echo. In practice single spin echo rarely used except acceptance testing Parallel imaging is now ubiquitous in clinical protocols. How do we assess SNR is a protocol specific way? Is it a practical measure with multiple channels and flexible coils?

13 Evaluation of SNR with G-noise Sum of Squares Adaptive Combine Mean 826 Mean 894 2D EPI, parallel imaging factor 2, different signal combination options All other measurement parameters fixed.

14 Evaluation of G-noise Sum of Squares Adaptive Combine Mean Mean snr = snr = Note the spatial dependence of the noise distribution Images acquired off resonance, alternatively transmitter at 0v.

15 Changing Role of MRI Moving from purely morphological to include functional quantitative imaging Moving from regional to whole body or large field of view imaging 32 Receiver channels 72 CP receiver elements in this configuration.

16 Functional Measures Functional MRI (fmri) minutes Dynamic susceptibility contrast (DSC-MRI) 1-2 minutes Dynamic Contrast Enhanced (DCE-MRI) 4-8 minutes Diffusion Weighted Imaging (DWI) 1-30 minutes

17 Functional Measures Functional MRI (fmri) minutes Dynamic susceptibility contrast (DSC-MRI) 1-2 minutes Dynamic Contrast Enhanced (DCE-MRI) 4-8 minutes Diffusion Weighted Imaging (DWI) 1-30 minutes 3 of the above typically use Echo Planar Imaging readout

18 Requirements for Functional Measures Temporal stability Rapid data acquisition, high parallel imaging factors Eddy Current compensation Uniformity of both B0 and B1 +

19 DCE-MRI Protocol Schematic MR images using different T1 contrast Dynamic Series Contrast agent injection Measurement of T 1 pre-injection Measurement of T 1 post-injection Schematic diagram of the data acquisition

20 Quality Control for DCE-MRI Acquisitions Dynamic contrast enhanced imaging requires an accurate and precise measurement of T1 changes to model pharmacokinetic behaviour. T1 measurements can be affected by many factors including Slice profile Scanner stability (RF and gradients) B1 variations K-space sampling Evaluate how these factors can effect T1 measurements with a series of phantom experiments at 1.5T and 3.0T.

21 Phantoms What should be assessed Signal(t) T1(t) [Gd](t) in true dynamic phantom that emulates tissue enhancement and is well characterized? extremely difficult! Range of T1 / T2 values of well characterized materials in static phantom. feasible! Spatial uniformity of transmit (B1) field System SNR under test and clinical DCE scan conditions CNR under DCE scan conditions Repeatability and reproducibility

22 T1 Measurement Accuracy Phased array coil Sequence parameters of T1 measurement methods Inversion recovery turbo-flash method TR/TE/θ/NSA = ms/1.14 ms/2 /1 39 inversion times varying from ms Variable flip angle method 3D GRE sequence TR/TE/NSA = 4.36 ms/1.36 ms/3 3 varying θs = 2, 8 and 12 Measurements were acquired with GRAPPA (ipat = 2) and without GRAPPA Siemens, Avanto (1.5T) A quick, easy and accurate method of T1 measurement is the variable flip angle (VFA) method 1 where gradient echo MR images are acquired using different flip angles, αi and T1 is calculated from the gradient of the linear plot of Si/sin(αi) vs. Si/tan(αi) A range of [Gd] doped water phantoms with T1 values ranging from 55ms-2865ms were evaluated. No major difference in T1 values obtained with and without partial parallel imaging 1. Fram et al Magn Reson Imaging. 1987;5(3):201-8.

23 Accuracy of Variable Flip Angle Method at 1.5T The accuracy and dynamic stability of clinical DCE-MRI protocols are assessed with phantom measurements Eurospin TO5 with 12 gels (T1 s ranging from 200 to 1300ms) were measured. In each experiment the phantom temperature was equilibrated and recorded. Dynamic stability was evaluated GRE sequences frequently exhibited an initial (40 second to 2 minutes) signal drift in T1W acquisitions. T1 Map ( )ms) Eurospin test object The signal drift in T1W images translates to 8-12% change in calculated T1 values

24 Stability of DCE-MRI measurements Dynamic acquisitions may have a 2% T1 variation over the initial seconds. Calculated T1 values across a dynamic time series had different dynamic variability depending on the sampling scheme used. Standard deviations ranged from 11.5ms (elliptical encoding) to 4.7ms (elliptical encoding with phase and slice undersampling). 1.5T No signal drift has been observed at 3T and dynamic variation is comparable with experiments at 1.5T. The standard deviation of 3D GRE sequences was reduced from 12.4ms to 6.4ms with the use of phase stabilisation. 3.0T Eurospin test object is temperature sensitive ~3% change in T1 with 1 o C (20-23 o C)

25 GRE Slice profiles Slice profiles obtained from measurements at different nutation angles using a silicone oil test object Slice profile results can be used to provide correction terms within the post-processing software to correct these errors. Essential to ensure that the slice positioning is centred on the region of interest. Sample T1 = 740ms Brookes JA et al; J Magn Reson Imaging Feb;9(2):

26 Inhomogeneous Transmit RF (B 1 ) Field RF transmit coils produce non-uniform field strengths FAs vary over the field of view % dt 1 vs. T 1 40% error in α % dt 1 30% error in α 20% error in α dt 1 2 dα 10% error in α T 1 (ms) B 1 θ Correct δt1 by performing in-vivo B 1 mapping Sung et al Magn Reson Med Oct;70(4):954-61

27 B1 1 Typical value for breast at 3.0T ROI Fatty tissue ROI T1 = 77ms. Original T1 estimate nutation angles 3 o and 16 o 1. Linderman et al JMRI (40); Data courtesy of Elizabeth O Flynn

28 DCE-MRI QA Assessments Noise Factor evaluated from full DCE-MRI protocol Useful for comparing protocols Can be applied to pre-enhanced clinical data SNR evaluated from full DCE- MRI protocol Useful for comparing protocols Useful for routine QA Kurland RJ MRM 2; Imran J et al MRI 17;

29 What is diffusion MR? Signal is exponentially dependent on the ADC and the sequence parameters (b-value): b = 0 s mm -2 b = 50 s mm -2 b = 100 s mm -2 ADC map b = 250 s mm -2 b = 500 s mm -2 b = 750 s mm -2

30 Diffusion Weighted Imaging Quality Assurance Use a range of phantoms: ADC accuracy use Sucrose, PVP (temperature sensitive) Ice water, temperature insensitive (long preparation >60mins) Silicone oil, non diffusing material (artefact assessments) Flood phantom ADC linearity Fat/Water test object (evaluate fat suppression efficiency) Others; alkanes for ADC, standard geometrical test objects

31 Diffusion Encoding pulse schemes Unipolar Diffusion encoding scheme Stejskal-Tanner Scanning with shorter TE Bipolar Diffusion encoding scheme Reduction of eddy currents induced spatial distortions 1 1. Chan et al J Magn Reson Jul;244:74-84

32 EPI N/2 Ghosting Axial images of a PDMS phantom acquired using receive bandwidths (a) 1628 Hx/pixel, (b) 1776 Hx/pixel, (c) 1860 Hx/pixel, (d) 2170 Hx/pixel, (e) 2298 Hx/ pixel, (f) 2442 Hx/pixel, (g) 2790 Hx/pixel, (h) 3004 Hx/pixel b = 0 s mm -2 ). Images have been windowed to enhance the visibility of the ghosts, at the same window width and level. Target to reduce ghosting below 3%

33 EPI N/2 Ghosting Axial images of a PDMS phantom acquired using receive bandwidths (a) 1628 Hx/pixel, (b) 1776 Hx/pixel, (c) 1860 Hx/pixel, (d) 2170 Hx/pixel, (e) 2298 Hx/ pixel, (f) 2442 Hx/pixel, (g) 2790 Hx/pixel, (h) 3004 Hx/pixel b = 0 s mm -2 ). Images have been windowed to enhance the visibility of the ghosts, at the same window width and level. What bandwidth should we use for N/2 ghost assessment?

34 Optimization of protocol critical to success Eddy currents: image distortion b0 b0 b1000 : b0 (background) 754 Hz/px 1450 Hz/px 2012 Hz/px 2416 Hz/px

35 Optimization of protocol critical to success Eddy currents: image distortion b0 b0 b1000 : b0 (background) 754 Hz/px 1450 Hz/px 2012 Hz/px 2416 Hz/px

36 (a) monopolar (b) DSE Axial images of a PDMS phantom (a, b) b = 0 s mm -2, (c, d) b = 1000 s mm -2 and (e, f) subtraction images. Images (a, c) acquired using a monopolar sequence and (b, d) using DSE Subtraction images show the b = 0 s mm -2 image subtracted from the b = 1000 s mm -2 image. (c) (d) (e) (f)

37 Quality Assurance ADC Accuracy ADC o C = mm 2 /s Malyarenko D et al J Magn Reson Imaging May;37(5):

38 Polyvinylpyrrolidone (PVP) phantom The cylindrical ice water phantom was used for the experiment, containing the vials with the different PVP concentrations. # PVP (% w/w) ROI 1 ROI 2 ROI 3 ROI 4 ROI 5 ROI 6 ROI min before the scanning the phantom was refilled with ice-water, in order to obtain a temperature of 00C. Dr Marianthi-Vasiliki Papoutsaki

39 ADC estimates from PVP phantom C PVP (% w/w) ADC median (*10-3 mm 2 /s) 0 - ROI ROI ROI ROI ROI ROI ROI ADC map Linear relationship between PVP concentration and R 2 ADC. = Boss et al ISMRM 2013 Dr. Marianthi-Vasiliki Papoutsaki

40 ADC Uniformity Assessment ADC ADC profile Evaluation of ADC uniformity is essential for quantitative WBDWI Malyarenko et al. Magn Reson Med May 13. Courtesy Dr. Jessica Winfield

41 ADC profile ADC profile Non -Uniform Gradient ~2% ADC ADC ADC uniformity is image acquisition, reconstruction and post-processing dependent Courtesy Dr. Jessica Winfield

42 ADC profiles along x and z axis of bipolar and unipolar diffusion pulse x- axis Median ADC value +/- 2.5% Centred at isocentre ADC map bipolar z- axis Median ADC value +/- 2.5% Centred at isocentre 53% deviation from the median value in bipolar Dr Marianthi-Vasiliki Papoutsaki

43 Fat-Water Test-object Inner cylinder: water/nacl/cuso mm coronal 400 mm x 400 mm FOV Annulus: Corn oil Gradient echo localiser images. Test object placed at 45 degrees to z-axis to create large ellipse in axial slices. 185 mm 140 mm axial 400 mm x 400 mm FOV Winfield et al Phys Med Biol May 7;59(9):

44 Upfield and downfield fat signals PE direction = AP Test object: No fat suppression, b=900 Volunteer: No fat suppression, b=900 upfield fat (1.3 ppm) shifted in anterior direction downfield fat (5.3 ppm) shifted in posterior direction Courtesy Dr. Jessica Winfield

45 Unsuppressed upfield fat at edges of FOV using SPAIR at 1.5 T Test object: SPAIR, b=900 Volunteer: SPAIR, b=900 Unsuppressed upfield fat at edges of FOV in test object and volunteer SPAIR leaves downfield fat signal unsuppressed Courtesy Dr Jessica Winfield

46 Whole Body Dixon (Fat/Water) Whole Body Dixon registered and fused with WBDWI a) WBDWI, b) Water, c) Fused a)+b), d) Dixon T1 map, e) Water ratio

47 Whole Body Dixon (Fat/Water) Whole Body Dual Contrast Dixon registered and fused with WBDWI a) WBDWI, b) Water, c) Fused a)+b), d) Dixon T1 map, e) Water ratio Three quantitative whole body metrics ADC, T1 and Fat/Water ratio Blackledge et al ISMRM 2009

48 Semi-automatic segmentation + b = 0 s/mm 2 Acquired data ADC map Select computed b-value and initial disease threshold Smoothing of regions using Markov random field model (MRF) Visualization/quantification of disease User modifiable regions of interest (ROI) Blackledge et al PLoS One Apr 7;9(4):e91779.

49 ADC stats (x10-3 mm2/s) Pretreatment Posttreatment Mean Variance Skewness Kurtosis

50 Discussion Routine Acceptance testing and QA informs only on the important basic functionality Broader range of test objects required How well do phantom measurements translate into meaningful measures (eg ADC repeatabilty, DCE-MRI noise factors)? QA has to move from the generic to the assessment of specific clinical protocols

51 in partnership with Acknowledgements Dr James d Arcy Dr Jessica Winfield Dr Mihaela Rata Dr Marianthi-Vasiliki Papoutsaki Dr Matthew Blackledge

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