CT Iterative Reconstruction Techniques

Transcription

1 RECENT ADVANCES IN CT RADIATION DOSE REDUCTION TECHNIQUES CT Iterative Reconstruction Techniques Kalpana Kanal, PhD, FSCBTMR, FACR, FAAPM University of Washington Seattle, WA SCBT-MR 2017 Nashville, Tennessee 1

2 DISCLOSURE NONE 2

3 HOW DOES ITERATIVE RECONSTRUCTION (IR) WORK? Ref: Beister et al, Physica Medica, 2012, 28:

4 DIFFERENT TYPES OF IR Pure IR (no modeling) Statistical IR (modeling of photon counting statistics) Raw data domain (sinogram domain) Volumetric images (image domain) During IR process Model based IR (go beyond statistical IR) Try to model acquisition process as accurately as possible Ref: Beister et al, Physica Medica, 2012, 28:

5 GEOMETRIC MODELING Ref: Beister et al, Physica Medica, 2012, 28:

6 VARIOUS AVAILABLE IR ALGORITHMS IN THE USA Toshiba FIRST Ref: Raman et al, JACR 2013, 10:37-41 Philips IMR GE ASIR-V Siemens ADMIRE Ref: Beister et al, Physica Medica, 2012, 28:

7 GENERATIONS OF ITERATIVE RECONSTRUCTION (GE) ASiR ASiR-V Veo Physics Noise Object Noise Object Optics Real-time performance (up to 35 ips) Reduce dose up to 82% Profound image quality under 1 msv Full model-based IR Longer reconstruction times Slide courtesy: GE Medical Systems Ref: Beister et al, Physica Medica, 2012, 28:

8 ASIR - V Slide courtesy: GE Medical Systems 8

9 BENEFITS IMAGES TECHNOLOGY SOLUTIONS ASiR-V reconstruction demonstrating improvements in low contrast detectability ASIR 30% ASiR-V 30% Revolution HD 2016 General Electric Company IMAGES COURTESY OF FROEDTERT & THE MEDICAL COLLEGE OF WISCONSIN, MILWAUKEE, WI 9

10 SIEMENS ADMIRE Five image noise and sharpness levels Strength 1 Strength 4 Strength 5 There is an incremental reduction of noise in each of the images at a natural image impression. Slide courtesy: GE Medical Systems 10

11 FIRST (MBIR) TOSHIBA - FIRST Forward Projected Model-Based Iterative Reconstruction SoluTion Scan Acquisition Original Projection Seed Image Strength 4 Forward Projection with every iteration Updated Image Optimized FIRST image Model Based Iterative Reconstruction: Slide courtesy: Toshiba Medical Integrated and easy to use Automated Fast 11 11

12 MBIR Up to 129% improved spatial resolution* FBP up to 74% improved low contrast detectability* up to 85.3% dose reduction* Slide courtesy: Toshiba Medical *as compared to FBP

13 IR AND LESION DETECTION Ref: Jensen et al, Eur Radiol, July

14 IR and Rad Dose Ref: Padole et al, AJR,

15 CLINICAL IMPLEMENTATION OF IR How does one go about implementing IR? Section buy-in is important, have all radiologists on board Start at vendor recommendations based on clinical application, then fine-tune? Important to reduce dose upfront by at least 20-25% before using IR Be prepared for resistance to new technology/process Continuous iterative improvement process 15

16 ADVANTAGES OF IR Reduce image noise and artifacts depending on degree of modeling By modeling cause of artifacts during reconstruction, IR methods represent more intuitive and natural way of image reconstruction Potential for significant patient dose reduction Using model based IR has better lesion conspicuity than FBP Using statistical based IR does not show significant lesion conspicuity unless dose reduced compared to FBP 16

17 DISADVANTAGES OF IR Artificial appearance of image Increased computational effort Evaluation of image noise and resolution is more complex Statistical modeling for low dose CT electronic noise more dominant Difficult to adopt by radiologists as noise patterns and artifacts look different Are we missing diagnostically important information? 17

18 ARE WE MISSING DIAGNOSTICALLY IMPORTANT INFORMATION? Hypodense seam along the stent indicating proliferation of the vessel intima which may ultimately lead to stent stenosis Hypodense seam not visible in IR image Hypodense seam confirmed by interventional angiography Ref: Beister et al, Physica Medica, 2012, 28:

19 CONCLUSIONS Iterative reconstruction methods are available on modern scanners Adoption and implementation varies depending on facility Faster computational speeds will make model-based IR more practical to use Radiologist adoption due to different image quality (less noise, more artificial look) and confidence level (are we missing something) varies 19

20 THANK YOU Mt. Rainier, WA, July 2017 Kanal 20