1
|
Klein K, Schafigh DG, Wallis MG, Campbell GM, Malter W, Schömig-Markiefka B, Maintz D, Hellmich M, Krug KB. Assignment of the biological value of solid breast masses based on quantitative evaluations of spectral CT examinations using electron density mapping, Zeffective mapping and iodine mapping. Eur J Radiol 2024; 171:111280. [PMID: 38219351 DOI: 10.1016/j.ejrad.2023.111280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 12/18/2023] [Accepted: 12/22/2023] [Indexed: 01/16/2024]
Abstract
OBJECTIVE We aimed to asses, in a clinical setting, whether the newly available quantitative evaluation of electron density (ED) in spectral CT examinations of the breast provide information on the biological identity of solid breast masses and whether ED maps yield added value to the diagnostic information of iodine maps and Zeff maps calculated from the same CT image datasets. METHODS All patients at the University Breast Cancer Center who underwent a clinically indicated Dual Layer Computed Tomography (DLCT) examination for staging of invasive breast cancer from 2018 to 2020 were prospectively included. Iodine concentration maps, Zeff maps and ED maps were automatically reconstructed from the DLCT datasets. Region of interest (ROI) based evaluations in the breast target lesions and in the aorta were performed semi-automatically in identical anatomical positions using dedicated evaluation software. Case-by-case evaluations were carried independently by 2 of 4 radiologists for each examination, respectively. Statistical analysis derived from the ROIs was done by calculating ROC/AUC curves and Youden indices. RESULTS The evaluations comprised 166 DLCT examinations. In the ED maps the measurements in the breast target lesions yielded Youden cutpoints of 104.0% (reader 1) and 103.8% (reader 2) resulting in AUCs of 0.63 and 0.67 at the empirical cutpoints. The variables "Zeff" and "iodine content" derived from the target lesions showed superior diagnostical results, with a Youden cutpoint of 8.0 mg/ml in the iodine maps and cutpoints of 1.1/1.2 in the Zeff maps the AUCs ranging from 0.84 to 0.85 (p = 0.023 to <0.000). The computational combination of Zeff and ED measurements in the target lesions yielded a slight AUC increase (readers 1: 0.85-0.87; readers 2: 0.84-0.94). The ratios of the measured values in the target lesions normalized to the values measured in the aorta showed comparable results. The AUCs of ED derived from the cutpoints showed inferior results to those derived from the Zeff maps and iodine maps (ED: 0.64 and 0.66 for reader 1 and 2; Zeff: 0.86 for both readers; iodine content: 0.89 and 0.86 for reader 1 and 2, respectively). The computational combination of the ED results and the Zeff measurements did not lead to a clinically relevant diagnostic gain with AUCs ranging from 0.86 to 0.88. CONCLUSIONS Quantitative assessments of Zeff, iodine content and ED all targeting the physical and chemical aspects of iodine uptake in solid breast masses confirmed diagnostically robust cutpoints for the differentiation of benign and malignant findings (Zeff < 7.7, iodine content of <0.8 mg/ml). The evaluations of the ED did not indicate any added diagnostic value beyond the quantitative assessments of Zeff and iodine content. Further research is warranted to develop suitable clinical indications for the use of ED maps.
Collapse
Affiliation(s)
- Konstantin Klein
- Dept. of Diagnostic and Interventional Radiology, University Hospital of Cologne, Cologne, Germany
| | - Darius Gabriel Schafigh
- Dept. of Diagnostic and Interventional Radiology, University Hospital of Cologne, Cologne, Germany; Dept. of ENT Surgery, University Hospital of Cologne, Cologne, Germany
| | - Matthew G Wallis
- Cambridge Breast Unit, NIHR Cambridge Biomedical Research Centre Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | | | - Wolfram Malter
- Breast Cancer Center, Department of Gynecology and Obstetrics, University of Cologne, Cologne, Germany
| | | | - David Maintz
- Dept. of Diagnostic and Interventional Radiology, University Hospital of Cologne, Cologne, Germany
| | - Martin Hellmich
- Institute of Medical Statistics and Bioinformatics, Medical Faculty, University of Cologne, Germany
| | - Kathrin Barbara Krug
- Dept. of Diagnostic and Interventional Radiology, University Hospital of Cologne, Cologne, Germany.
| |
Collapse
|
2
|
Zimmerman J, Thor D, Poludniowski G. Stopping-power ratio estimation for proton radiotherapy using dual-energy computed tomography and prior-image constrained denoising. Med Phys 2023; 50:1481-1495. [PMID: 36322128 DOI: 10.1002/mp.16063] [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: 04/02/2022] [Revised: 09/12/2022] [Accepted: 09/26/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Dual-energy computed tomography (DECT) is a promising technique for estimating stopping-power ratio (SPR) for proton therapy planning. It is known, however, that deriving electron density (ED) and effective atomic number (EAN) from DECT data can cause noise amplification in the resulting SPR images. This can negate the benefits of DECT. PURPOSE This work introduces a new algorithm for estimating SPR from DECT with noise suppression, using a pair of CT scans with spectral separation. The method is demonstrated using phantom measurements. MATERIALS AND METHODS An iterative algorithm is presented, reconstructing ED and EAN with noise suppression, based on Prior Image Constrained Denoising (PIC-D). The algorithm is tested using a Siemens Definition AS+ CT scanner (Siemens Healthcare, Forchheim, Germany). Three phantoms are investigated: a calibration phantom (CIRS 062M), a QA phantom (CATPHAN 700), and an anthropomorphic head phantom (CIRS 731-HN). A task-transfer function (TTF) and the noise power spectrum are derived from SPR images of the QA phantom for the evaluation of image quality. Comparisons of accuracy and noise for ED, EAN, and SPR are made for various versions of the algorithm in comparison to a solution based on Siemens syngo.via Rho/Z software and the current clinical standard of a single-energy CT stoichiometric calibration. A gamma analysis is also applied to the SPR images of the head phantom and water-equivalent distance (WED) is evaluated in a treatment planning system for a proton treatment field. RESULTS The algorithm is effective at suppressing noise in both ED and EAN and hence also SPR. The noise is tunable to a level equivalent to or lower than that of the syngo.via Rho/Z software. The spatial resolution (10% and 50% frequencies in the TTF) does not degrade even for the highest noise suppression investigated, although the average spatial frequency of noise does decrease. The PIC-D algorithm showed better accuracy than syngo.via Rho/Z for low density materials. In the calibration phantom, it was superior even when excluding lung substitutes, with root-mean-square deviations for ED and EAN less than 0.3% and 2%, respectively, compared to 0.5% and 3%. In the head phantom, however, the SPR accuracy of the PIC-D algorithm was comparable (excluding sinus tissue) to that derived from syngo.via Rho/Z: less than 1% error for soft tissue, brain, and trabecular bone substitutes and 5-7% for cortical bone, with the larger error for the latter likely related to the phantom geometry. Gamma evaluation showed that PIC-D can suppress noise in a patient-like geometry without introducing substantial errors in SPR. The absolute pass rates were almost identical for PIC-D and syngo.via Rho/Z. In the WED evaluations no general differences were shown. CONCLUSIONS The PIC-D DECT algorithm provides scanner-specific calibration and tunable noise suppression. It is vendor agnostic and applicable to any pair of CT scans with spectral separation. Improved accuracy to current methods was not clearly demonstrated for the complex geometry of a head phantom, but the suppression of noise without spatial resolution degradation and the possibility of incorporating constraints on image properties, suggests the usefulness of the approach.
Collapse
Affiliation(s)
- Jens Zimmerman
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Daniel Thor
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Gavin Poludniowski
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| |
Collapse
|
3
|
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.
Collapse
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
| |
Collapse
|
4
|
Kim Y, Kim JS, Cho S. Feasibility study of using triple-energy CT images for improving stopping power estimation. NUCLEAR ENGINEERING AND TECHNOLOGY 2022. [DOI: 10.1016/j.net.2022.12.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
|
5
|
Simard M, Bouchard H. One-step iterative reconstruction approach based on eigentissue decomposition for spectral photon-counting computed tomography. J Med Imaging (Bellingham) 2022; 9:044003. [PMID: 35911210 PMCID: PMC9328749 DOI: 10.1117/1.jmi.9.4.044003] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 07/01/2022] [Indexed: 11/14/2022] Open
Abstract
Purpose: We propose a one-step tissue characterization method for spectral photon-counting computed tomography (SPCCT) using eigentissue decomposition (ETD), tailored for highly accurate human tissue characterization in radiotherapy. Methods: The approach combines a Poisson likelihood, a spatial prior, and a quantitative prior constraining eigentissue fractions based on expected values for tabulated tissues. There are two regularization parameters: α for the quantitative prior, and β for the spatial prior. The approach is validated in a realistic simulation environment for SPCCT. The impact of α and β is evaluated on a virtual phantom. The framework is tested on a virtual patient and compared with two sinogram-based two-step methods [using respectively filtered backprojection (FBP) and an iterative method for the second step] and a post-reconstruction approach with the same quantitative prior. All methods use ETD. Results: Optimal performance with respect to bias or RMSE is achieved with different combinations of α and β on the cylindrical phantom. Evaluated in tissues of the virtual patient, the one-step framework outperforms two-step and post-reconstruction approaches to quantify proton-stopping power (SPR). The mean absolute bias on the SPR is 0.6% (two-step FBP), 0.6% (two-step iterative), 0.6% (post-reconstruction), and 0.2% (one-step optimized for low bias). Following the same order, the RMSE on the SPR is 13.3%, 2.5%, 3.2%, and 1.5%. Conclusions: Accurate and precise characterization with ETD can be achieved with noisy SPCCT data without the need to rely on post-reconstruction methods. The one-step framework is more accurate and precise than two-step methods for human tissue characterization.
Collapse
Affiliation(s)
- Mikaël Simard
- Université de Montréal, Département de physique, Montréal, Québec, Canada
| | - Hugo Bouchard
- Université de Montréal, Département de physique, Montréal, Québec, Canada.,Centre de recherche du Centre hospitalier de l'Université de Montréal, Montréal, Québec, Canada.,Centre hospitalier de l'Université de Montréal (CHUM), Département de radio-oncologie, Montréal, Québec, Canada
| |
Collapse
|
6
|
Shim E, Kim BH, Kang WY, Hong SJ, Kang CH, Ahn KS, Lee H, Kwack TJ. Diagnostic performance of electron-density dual-energy CT in detection of cervical disc herniation in comparison with standard gray-scale CT and virtual non-calcium images. Eur Radiol 2022; 32:2209-2220. [PMID: 35064315 PMCID: PMC8782689 DOI: 10.1007/s00330-021-08374-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 09/14/2021] [Accepted: 09/30/2021] [Indexed: 01/07/2023]
Abstract
Objectives To assess the diagnostic performance of dual-energy CT (DECT) with electron-density (ED) image reconstruction compared with standard CT (SC) and virtual non-calcium (VNCa) image CT reconstruction for detecting cervical disc herniation. Methods This cross-sectional study was approved by the IRB. We enrolled 64 patients (336 intervertebral discs from C2/3 to C7/T1; mean age, 55 years; 17 women and 47 men) who underwent DECT with spectral reconstruction and 3-T MRI within 2 weeks between January 2018 and June 2020. Four radiologists independently evaluated the first image set of randomized SC, VNCa, and ED images to detect cervical disc herniation. After 8 weeks, the readers re-evaluated the second and the last image sets with an 8-week interval. MRI evaluations performed by two other experienced served as the reference standard. Comparing diagnostic performance between each images set was evaluated by a generalized estimating equation. Results A total of 233 cervical disc herniations were noted on MRI. For detecting cervical disc herniation, electron-density images showed higher sensitivity (94% [219/233; 95% CI, 90–97] vs. 76% [177/233; 70–81] vs. 69% [160/233; 62–76]) (p < 0.001) and similar specificity (90% [93/103; 83–95] vs. 89% [92/103; 82–96] vs. 90% [93/103; 83–95]) (p > 0.05) as SC and VNCa images, respectively. Inter-reader agreement for cervical disc herniation calculated among the four readers was moderate for all image sets (κ = 0.558 for ED, κ = 0.422 for SC, and κ = 0.449 for VNCa). Conclusion DECT with ED reconstruction can improve cervical disc herniation detection and diagnostic confidence compared with SC and VNCa images. Key Points • Intervertebral discs with high material density are well visualized on electron-density images obtained from dual-energy CT. • Electron-density images showed much higher sensitivity and diagnostic accuracy than standard CT and virtual non-calcium images for the detection of cervical disc herniation. • Electron-density images can have false-negative results, especially for disc herniation with high signal intensity on T2W images and can show pseudo-disc extrusion at the lower cervical spine. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-021-08374-y.
Collapse
|
7
|
Medrano M, Liu R, Zhao T, Webb T, Politte DG, Whiting BR, Liao R, Ge T, Porras-Chaverri MA, O'Sullivan JA, Williamson JF. Towards sub-percentage uncertainty proton stopping-power mapping via dual-energy CT: direct experimental validation and uncertainty analysis of a statistical iterative image reconstruction method. Med Phys 2022; 49:1599-1618. [PMID: 35029302 DOI: 10.1002/mp.15457] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 10/28/2021] [Accepted: 12/22/2021] [Indexed: 11/06/2022] Open
Abstract
PURPOSE To assess the potential of a joint dual-energy CT reconstruction process (Statistical Image Reconstruction method built on a Basis Vector Model (JSIR-BVM)) implemented on a 16-slice commercial CT scanner to measure high spatial-resolution stopping-power ratio (SPR) maps with uncertainties of less than 1%. METHODS JSIR-BVM was used to reconstruct images of effective electron density and mean excitation energy from dual-energy CT (DECT) sinograms for ten high-purity samples of known density and atomic composition inserted into head and body phantoms. The measured DECT data consisted of 90 kVp and 140 kVp axial sinograms serially acquired on a Philips Brilliance Big Bore CT scanner without beam-hardening corrections. The corresponding SPRs were subsequently measured directly via ion chamber measurements on a MEVION S250 superconducting synchrocyclotron and evaluated theoretically from the known sample compositions and densities. Deviations of JSIR-BVM SPR values from their theoretically calculated and directly measured ground-truth values were evaluated for our JSIR-BVM method and for our implementation of the Hünemohr-Saito (H-S) DECT image-domain decomposition technique for SPR imaging. A thorough uncertainty analysis was then performed for 5 different scenarios (comparison of JSIR-BVM SPR/SP to International Commission on Radiation Measurements and Units (ICRU) benchmarks; comparison of JSIR-BVM SPR to measured benchmarks; and uncertainties in JSIR-BVM SPR/SP maps for patients of unknown composition) per the Joint Committee for Guides in Metrology (JCGM) and the Guide to expression of Uncertainty in Measurement (GUM), including the impact of uncertainties in measured photon spectra, sample composition and density, photon cross-section and I-value models, and random measurement uncertainty. Estimated SPR uncertainty for three main tissue groups in patients of unknown composition and the weighted proportion of each tissue type for three proton treatment sites were then used to derive a composite range uncertainty for our method. RESULTS Mean JSIR-BVM SPR estimates deviated by less than 1% from their theoretical and directly measured ground-truth values for most inserts and phantom geometries except for high density Delrin and Teflon samples with SPR error relative to proton measurements of 1.1% and -1.0% (Head Phantom) and 1.1% and -1.1% (Body Phantom). The overall RMS deviations over all samples were 0.39% and 0.52% (head phantom) and 0.43% and 0.57% (body phantom) relative to theoretical and directly measured ground-truth SPRs, respectively. The corresponding RMS (maximum) errors for the image-domain decomposition method were 2.68% and 2.73% (4.68% and 4.99%) for the head phantom and 0.71% and 0.87% (1.37% and 1.66%) for the body phantom. Compared to H-S SPR maps, JSIR-BVM yielded 30% sharper and two-fold sharper images for soft tissues and bone-like surrogates, respectively, while reducing noise by factors of 6 and 3, respectively. The uncertainty (coverage factor k = 1) of the DECT-to-benchmark values comparison ranged from 0.5% to 1.5% and is dominated by scanning-beam photon-spectra uncertainties. An analysis of the SPR uncertainty for patients of unknown composition showed a JSIR-BVM uncertainty of 0.65%, 1.21%, and 0.77% for soft-, lung-, and bony-tissue groups which led to a composite range uncertainty of 0.6%-0.9%. CONCLUSIONS Observed JSIR-BVM SPR estimation errors were all less than 50% of the estimated k = 1 total uncertainty of our benchmarking experiment, demonstrating that JSIR-BVM high spatial-resolution, low-noise SPR mapping is feasible and is robust to variations in the geometry of the scanned object. In contrast, the much larger H-S SPR estimation errors are dominated by imaging noise and residual beam-hardening artifacts. While the uncertainties characteristic of our current JSIR-BVM implementation can be as large as 1.5%, achieving <1% total uncertainty is feasible by improving the accuracy of scanner-specific scatter-profile and photon-spectrum estimates. With its robustness to beam-hardening artifact, image noise and variations in phantom size and geometry, JSIR-BVM has the potential to achieve high spatial-resolution SPR mapping with sub-percentage accuracy and estimated uncertainty in the clinical setting. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Maria Medrano
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Ruirui Liu
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
| | - Tianyu Zhao
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, 63110, USA
| | - Tyler Webb
- Department of Physics, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - David G Politte
- Mallinckrodt Institute of Radiology, St. Louis, MO, 63110, USA
| | - Bruce R Whiting
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Rui Liao
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Tao Ge
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Mariela A Porras-Chaverri
- Atomic, Nuclear and Molecular Sciences Research Center (CICANUM), University of Costa Rica, San Jose, Costa Rica
| | - Joseph A O'Sullivan
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Jeffrey F Williamson
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, 63110, USA
| |
Collapse
|
8
|
Bär E, Volz L, Collins-Fekete CA, Brons S, Runz A, Schulte RW, Seco J. Experimental comparison of photon versus particle computed tomography to predict tissue relative stopping powers. Med Phys 2022; 49:474-487. [PMID: 34709667 DOI: 10.1002/mp.15283] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 09/18/2021] [Accepted: 09/20/2021] [Indexed: 01/21/2023] Open
Abstract
PURPOSE Measurements comparing relative stopping power (RSP) accuracy of state-of-the-art systems representing single-energy and dual-energy computed tomography (SECT/DECT) with proton CT (pCT) and helium CT (HeCT) in biological tissue samples. METHODS We used 16 porcine and bovine samples of various tissue types and water, covering an RSP range from 0.90 ± 0.06 to 1.78 ± 0.05. Samples were packed and sealed into 3D-printed cylinders ( d = 2 cm, h = 5 cm) and inserted into an in-house designed cylindrical polymethyl methacrylate (PMMA) phantom ( d = 10 cm, h = 10 cm). We scanned the phantom in a commercial SECT and DECT (120 kV; 100 and 140 kV/Sn (tin-filtered)); and acquired pCT and HeCT ( E ∼ 200 MeV/u, 2 ∘ steps, ∼ 6.2 × 10 6 (p)/ ∼ 2.3 × 10 6 (He) particles/projection) with a particle imaging prototype. RSP maps were calculated from SECT/DECT using stoichiometric methods and from pCT/HeCT using the DROP-TVS algorithm. We estimated the average RSP of each tissue per modality in cylindrical volumes of interest and compared it to ground truth RSP taken from peak-detection measurements. RESULTS Throughout all samples, we observe the following root-mean-squared RSP prediction errors ± combined uncertainty from reference measurement and imaging: SECT 3.10 ± 2.88%, DECT 0.75 ± 2.80%, pCT 1.19 ± 2.81%, and HeCT 0.78 ± 2.81%. The largest mean errors ± combined uncertainty per modality are SECT 8.22 ± 2.79% in cortical bone, DECT 1.74 ± 2.00% in back fat, pCT 1.80 ± 4.27% in bone marrow, and HeCT 1.37 ± 4.25% in bone marrow. Ring artifacts were observed in both pCT and HeCT reconstructions, imposing a systematic shift to predicted RSPs. CONCLUSION Comparing state-of-the-art SECT/DECT technology and a pCT/HeCT prototype, DECT provided the most accurate RSP prediction, closely followed by particle imaging. The novel modalities pCT and HeCT have the potential to further improve on RSP accuracies with work focusing on the origin and correction of ring artifacts. Future work will study accuracy of proton treatment plans using RSP maps from investigated imaging modalities.
Collapse
Affiliation(s)
- Esther Bär
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,Department of Radiotherapy Physics, University College London Hospitals NHS Foundation Trust, Radiotherapy Physics, London, UK
| | - Lennart Volz
- Biomedical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld, Heidelberg, Germany
| | | | - Stephan Brons
- Heidelberg Ion Beam Therapy Center, Im Neuenheimer Feld, Heidelberg, Germany
| | - Armin Runz
- Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld, Heidelberg, Germany
| | | | - Joao Seco
- Biomedical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld, Heidelberg, Germany.,Department of Physics and Astronomy, Heidelberg University, Germany
| |
Collapse
|
9
|
Farace P, Tommasino F, Righetto R, Fracchiolla F, Scaringella M, Bruzzi M, Civinini C. Technical Note: CT calibration for proton treatment planning by cross-calibration with proton CT data. Med Phys 2021; 48:1349-1355. [PMID: 33382083 DOI: 10.1002/mp.14698] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 11/30/2020] [Accepted: 12/23/2020] [Indexed: 12/31/2022] Open
Abstract
PURPOSE This study explores the possibility of a new method for x-ray computed tomography (CT) calibration by means of cross-calibration with proton CT (pCT) data. The proposed method aims at a more accurate conversion of CT Hounsfield Units (HU) into proton stopping power ratio (SPR) relative to water to be used in proton-therapy treatment planning. METHODS X-ray CT scan was acquired on a synthetic anthropomorphic phantom, composed of different tissue equivalent materials (TEMs). A pCT apparatus was instead adopted to obtain a reference three-dimensional distribution of the phantom's SPR values. After rigid registration, the x-ray CT was artificially blurred to the same resolution of pCT. Then a scatter plot showing voxel-by-voxel SPR values as a function of HU was employed to link the two measurements and thus obtaining a cross-calibrated x-ray CT calibration curve. The cross-calibration was tested at treatment planning system and then compared with a conventional calibration based on exactly the same TEMs constituting the anthropomorphic phantom. RESULTS Cross-calibration provided an accurate SPR mapping, better than by conventional TEMs calibration. The dose distribution of single beams optimized on the reference SPR map was recomputed on cross-calibrated CT, showing, with respect to conventional calibration, minor deviation at the dose fall-off (lower than 1%). CONCLUSIONS The presented data demonstrated that, by means of reference pCT data, a heterogeneous phantom can be used for CT calibration, paving the way to the use of biological samples, with their accurate description of patients' tissues. This overcomes the limitations of conventional CT calibration requiring homogenous samples, only available by synthetic TEMs, which fail in accurately mimicking the properties of biological tissues. Once a heterogeneous biological sample is provided with its corresponding reference SPR maps, a cross-calibration procedure could be adopted by other PT centers, even when not equipped with a pCT system.
Collapse
Affiliation(s)
- Paolo Farace
- Protontherapy Unit, Hospital of Trento, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy.,Istituto Nazionale di Fisica Nucleare TIFPA, via Sommarive, 14, Trento, Italy
| | - Francesco Tommasino
- Istituto Nazionale di Fisica Nucleare TIFPA, via Sommarive, 14, Trento, Italy.,Department of Physics, University of Trento, via Sommarive, 14, Trento, Italy
| | - Roberto Righetto
- Protontherapy Unit, Hospital of Trento, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy.,Istituto Nazionale di Fisica Nucleare TIFPA, via Sommarive, 14, Trento, Italy
| | - Francesco Fracchiolla
- Protontherapy Unit, Hospital of Trento, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy.,Istituto Nazionale di Fisica Nucleare TIFPA, via Sommarive, 14, Trento, Italy
| | - Monica Scaringella
- Istituto Nazionale di Fisica Nucleare sezione di Firenze, Via G. Sansone 1, Sesto Fiorentino, Italy
| | - Mara Bruzzi
- Istituto Nazionale di Fisica Nucleare sezione di Firenze, Via G. Sansone 1, Sesto Fiorentino, Italy.,Dipartimento di Fisica e Astronomia, Università degli Studi di Firenze, via G. Sansone 1, Sesto Fiorentino, Italy
| | - Carlo Civinini
- Istituto Nazionale di Fisica Nucleare sezione di Firenze, Via G. Sansone 1, Sesto Fiorentino, Italy
| |
Collapse
|