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Bal NJS, Chitra Ragupathy I, Tramm T, Nijkamp J. A Novel and Reliable Pixel Response Correction Method (DAC-Shifting) for Spectral Photon-Counting CT Imaging. Tomography 2024; 10:1168-1191. [PMID: 39058061 PMCID: PMC11281142 DOI: 10.3390/tomography10070089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/02/2024] [Accepted: 07/16/2024] [Indexed: 07/28/2024] Open
Abstract
Spectral photon-counting cone-beam computed tomography (CT) imaging is challenged by individual pixel response behaviours, which lead to noisy projection images and subsequent image artefacts like rings. Existing methods to correct for this either use calibration measurements, like signal-to-thickness calibration (STC), or perform a post-processing ring artefact correction of sinogram data or scan reconstructions without taking the pixel response explicitly into account. Here, we present a novel post-processing method (digital-to-analogue converter (DAC)-shifting) which explicitly measures the current pixel response using flat-field images and subsequently corrects the projection data. The DAC-shifting method was evaluated using a repeat series of the spectral photon-counting imaging (Medipix3) of a phantom with different density inserts and iodine K-edge imaging. The method was also compared against polymethyl methacrylate (PMMA)-based STC. The DAC-shifting method was shown to be effective in correcting individual pixel responses and was robust against detector instability; it led to a 47.4% average reduction in CT-number variation in homogeneous materials, with a range of 40.7-55.6%. On the contrary, the STC correction showed varying results; a 13.7% average reduction in CT-number variation, ranging from a 43.7% increase to a 45.5% reduction. In K-edge imaging, DAC-shifting provides a sharper attenuation peak and more uniform CT values, which are expected to benefit iodine concentration quantifications.
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Affiliation(s)
- Navrit Johan Singh Bal
- Department of Clinical Medicine, Aarhus University, 8200 Aarhus, Denmark; (N.J.S.B.); (I.C.R.); (T.T.)
- Danish Centre for Particle Therapy, Aarhus University Hospital, 8200 Aarhus, Denmark
| | - Imaiyan Chitra Ragupathy
- Department of Clinical Medicine, Aarhus University, 8200 Aarhus, Denmark; (N.J.S.B.); (I.C.R.); (T.T.)
- Danish Centre for Particle Therapy, Aarhus University Hospital, 8200 Aarhus, Denmark
| | - Trine Tramm
- Department of Clinical Medicine, Aarhus University, 8200 Aarhus, Denmark; (N.J.S.B.); (I.C.R.); (T.T.)
- Department of Pathology, Aarhus University Hospital, 8200 Aarhus, Denmark
| | - Jasper Nijkamp
- Department of Clinical Medicine, Aarhus University, 8200 Aarhus, Denmark; (N.J.S.B.); (I.C.R.); (T.T.)
- Danish Centre for Particle Therapy, Aarhus University Hospital, 8200 Aarhus, Denmark
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Rodesch PA, Si-Mohamed SA, Lesaint J, Douek PC, Rit S. Image quality improvement of a one-step spectral CT reconstruction on a prototype photon-counting scanner. Phys Med Biol 2023; 69:015005. [PMID: 38041870 DOI: 10.1088/1361-6560/ad11a3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 12/01/2023] [Indexed: 12/04/2023]
Abstract
Objective. X-ray spectral computed tomography (CT) allows for material decomposition (MD). This study compared a one-step material decomposition MD algorithm with a two-step reconstruction MD algorithm using acquisitions of a prototype CT scanner with a photon-counting detector (PCD).Approach. MD and CT reconstruction may be done in two successive steps, i.e. decompose the data in material sinograms which are then reconstructed in material CT images, or jointly in a one-step algorithm. The one-step algorithm reconstructed material CT images by maximizing their Poisson log-likelihood in the projection domain with a spatial regularization in the image domain. The two-step algorithm maximized first the Poisson log-likelihood without regularization to decompose the data in material sinograms. These sinograms were then reconstructed into material CT images by least squares minimization, with the same spatial regularization as the one step algorithm. A phantom simulating the CT angiography clinical task was scanned and the data used to measure noise and spatial resolution properties. Low dose carotid CT angiographies of 4 patients were also reconstructed with both algorithms and analyzed by a radiologist. The image quality and diagnostic clinical task were evaluated with a clinical score.Main results. The phantom data processing demonstrated that the one-step algorithm had a better spatial resolution at the same noise level or a decreased noise value at matching spatial resolution. Regularization parameters leading to a fair comparison were selected for the patient data reconstruction. On the patient images, the one-step images received higher scores compared to the two-step algorithm for image quality and diagnostic.Significance. Both phantom and patient data demonstrated how a one-step algorithm improves spectral CT image quality over the implemented two-step algorithm but requires a longer computation time. At a low radiation dose, the one-step algorithm presented good to excellent clinical scores for all the spectral CT images.
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Affiliation(s)
- Pierre-Antoine Rodesch
- Univ. Lyon, INSA-Lyon, UCBLyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR5220, U1294, F-69373 Lyon, France
| | - Salim A Si-Mohamed
- Univ. Lyon, INSA-Lyon, UCBLyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR5220, U1294, F-69373 Lyon, France
- Department of Radiology, Louis Pradel Hospital, Hospices Civils de Lyon, Bron, France
| | - Jérôme Lesaint
- Univ. Lyon, INSA-Lyon, UCBLyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR5220, U1294, F-69373 Lyon, France
| | - Philippe C Douek
- Univ. Lyon, INSA-Lyon, UCBLyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR5220, U1294, F-69373 Lyon, France
- Department of Radiology, Louis Pradel Hospital, Hospices Civils de Lyon, Bron, France
| | - Simon Rit
- Univ. Lyon, INSA-Lyon, UCBLyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR5220, U1294, F-69373 Lyon, France
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Yang M, Wohlfahrt P, Shen C, Bouchard H. Dual- and multi-energy CT for particle stopping-power estimation: current state, challenges and potential. Phys Med Biol 2023; 68. [PMID: 36595276 DOI: 10.1088/1361-6560/acabfa] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022]
Abstract
Range uncertainty has been a key factor preventing particle radiotherapy from reaching its full physical potential. One of the main contributing sources is the uncertainty in estimating particle stopping power (ρs) within patients. Currently, theρsdistribution in a patient is derived from a single-energy CT (SECT) scan acquired for treatment planning by converting CT number expressed in Hounsfield units (HU) of each voxel toρsusing a Hounsfield look-up table (HLUT), also known as the CT calibration curve. HU andρsshare a linear relationship with electron density but differ in their additional dependence on elemental composition through different physical properties, i.e. effective atomic number and mean excitation energy, respectively. Because of that, the HLUT approach is particularly sensitive to differences in elemental composition between real human tissues and tissue surrogates as well as tissue variations within and among individual patients. The use of dual-energy CT (DECT) forρsprediction has been shown to be effective in reducing the uncertainty inρsestimation compared to SECT. The acquisition of CT data over different x-ray spectra yields additional information on the material elemental composition. Recently, multi-energy CT (MECT) has been explored to deduct material-specific information with higher dimensionality, which has the potential to further improve the accuracy ofρsestimation. Even though various DECT and MECT methods have been proposed and evaluated over the years, these approaches are still only scarcely implemented in routine clinical practice. In this topical review, we aim at accelerating this translation process by providing: (1) a comprehensive review of the existing DECT/MECT methods forρsestimation with their respective strengths and weaknesses; (2) a general review of uncertainties associated with DECT/MECT methods; (3) a general review of different aspects related to clinical implementation of DECT/MECT methods; (4) other potential advanced DECT/MECT applications beyondρsestimation.
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Affiliation(s)
- Ming Yang
- The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, 1515 Holcombe Blvd Houston, TX 77030, United States of America
| | - Patrick Wohlfahrt
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Boston, MA 02115, United States of America
| | - Chenyang Shen
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, 2280 Inwood Rd Dallas, TX 75235, United States of America
| | - Hugo Bouchard
- Département de physique, Université de Montréal, Complexe des sciences, 1375 Avenue Thérèse-Lavoie-Roux, Montréal, Québec H2V0B3, Canada.,Centre de recherche du Centre hospitalier de l'Université de Montréal, 900 Rue Saint-Denis, Montréal, Québec, H2X 0A9, Canada.,Département de radio-oncologie, Centre hospitalier de l'Université de Montréal, 1051 Rue Sanguinet, Montréal, Québec H2X 3E4, Canada
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