Hadley DeBrosse, Giavanna Jadick, Ling Jian Meng, Patrick La Rivière
{"title":"X 射线荧光发射断层扫描与计算机断层扫描的对比度与噪声比。","authors":"Hadley DeBrosse, Giavanna Jadick, Ling Jian Meng, Patrick La Rivière","doi":"10.1117/1.JMI.11.S1.S12808","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>We provide a comparison of X-ray fluorescence emission tomography (XFET) and computed tomography (CT) for detecting low concentrations of gold nanoparticles (GNPs) in soft tissue and characterize the conditions under which XFET outperforms energy-integrating CT (EICT) and photon-counting CT (PCCT).</p><p><strong>Approach: </strong>We compared dose-matched Monte Carlo XFET simulations and analytical fan-beam EICT and PCCT simulations. Each modality was used to image a numerical mouse phantom and contrast-depth phantom containing GNPs ranging from 0.05% to 4% by weight in soft tissue. Contrast-to-noise ratios (CNRs) of gold regions were compared among the three modalities, and XFET's detection limit was quantified based on the Rose criterion. A partial field-of-view (FOV) image was acquired for the phantom region containing 0.05% GNPs.</p><p><strong>Results: </strong>For the mouse phantom, XFET produced superior CNR values ( <math><mrow><mi>CNRs</mi> <mo>=</mo> <mn>24.5</mn></mrow> </math> , 21.6, and 3.4) compared with CT images obtained with both energy-integrating ( <math><mrow><mi>CNR</mi> <mo>=</mo> <mn>4.4</mn></mrow> </math> , 4.6, and 1.5) and photon-counting ( <math><mrow><mi>CNR</mi> <mo>=</mo> <mn>6.5</mn></mrow> </math> , 7.7, and 2.0) detection systems. More generally, XFET outperformed CT for superficial imaging depths ( <math><mrow><mo><</mo> <mn>28.75</mn> <mtext> </mtext> <mi>mm</mi></mrow> </math> ) for gold concentrations at and above 0.5%. XFET's surface detection limit was quantified as 0.44% for an average phantom dose of 16 mGy compatible with <i>in vivo</i> imaging. XFET's ability to image partial FOVs was demonstrated, and 0.05% gold was easily detected with an estimated dose of <math><mrow><mo>∼</mo> <mn>81.6</mn> <mtext> </mtext> <mi>cGy</mi></mrow> </math> to a localized region of interest.</p><p><strong>Conclusions: </strong>We demonstrate a proof of XFET's benefit for imaging low concentrations of gold at superficial depths and the feasibility of XFET for <i>in vivo</i> metal mapping in preclinical imaging tasks.</p>","PeriodicalId":47707,"journal":{"name":"Journal of Medical Imaging","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11478016/pdf/","citationCount":"0","resultStr":"{\"title\":\"Contrast-to-noise ratio comparison between X-ray fluorescence emission tomography and computed tomography.\",\"authors\":\"Hadley DeBrosse, Giavanna Jadick, Ling Jian Meng, Patrick La Rivière\",\"doi\":\"10.1117/1.JMI.11.S1.S12808\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>We provide a comparison of X-ray fluorescence emission tomography (XFET) and computed tomography (CT) for detecting low concentrations of gold nanoparticles (GNPs) in soft tissue and characterize the conditions under which XFET outperforms energy-integrating CT (EICT) and photon-counting CT (PCCT).</p><p><strong>Approach: </strong>We compared dose-matched Monte Carlo XFET simulations and analytical fan-beam EICT and PCCT simulations. Each modality was used to image a numerical mouse phantom and contrast-depth phantom containing GNPs ranging from 0.05% to 4% by weight in soft tissue. Contrast-to-noise ratios (CNRs) of gold regions were compared among the three modalities, and XFET's detection limit was quantified based on the Rose criterion. A partial field-of-view (FOV) image was acquired for the phantom region containing 0.05% GNPs.</p><p><strong>Results: </strong>For the mouse phantom, XFET produced superior CNR values ( <math><mrow><mi>CNRs</mi> <mo>=</mo> <mn>24.5</mn></mrow> </math> , 21.6, and 3.4) compared with CT images obtained with both energy-integrating ( <math><mrow><mi>CNR</mi> <mo>=</mo> <mn>4.4</mn></mrow> </math> , 4.6, and 1.5) and photon-counting ( <math><mrow><mi>CNR</mi> <mo>=</mo> <mn>6.5</mn></mrow> </math> , 7.7, and 2.0) detection systems. More generally, XFET outperformed CT for superficial imaging depths ( <math><mrow><mo><</mo> <mn>28.75</mn> <mtext> </mtext> <mi>mm</mi></mrow> </math> ) for gold concentrations at and above 0.5%. XFET's surface detection limit was quantified as 0.44% for an average phantom dose of 16 mGy compatible with <i>in vivo</i> imaging. XFET's ability to image partial FOVs was demonstrated, and 0.05% gold was easily detected with an estimated dose of <math><mrow><mo>∼</mo> <mn>81.6</mn> <mtext> </mtext> <mi>cGy</mi></mrow> </math> to a localized region of interest.</p><p><strong>Conclusions: </strong>We demonstrate a proof of XFET's benefit for imaging low concentrations of gold at superficial depths and the feasibility of XFET for <i>in vivo</i> metal mapping in preclinical imaging tasks.</p>\",\"PeriodicalId\":47707,\"journal\":{\"name\":\"Journal of Medical Imaging\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11478016/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Medical Imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1117/1.JMI.11.S1.S12808\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/15 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1117/1.JMI.11.S1.S12808","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/15 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Contrast-to-noise ratio comparison between X-ray fluorescence emission tomography and computed tomography.
Purpose: We provide a comparison of X-ray fluorescence emission tomography (XFET) and computed tomography (CT) for detecting low concentrations of gold nanoparticles (GNPs) in soft tissue and characterize the conditions under which XFET outperforms energy-integrating CT (EICT) and photon-counting CT (PCCT).
Approach: We compared dose-matched Monte Carlo XFET simulations and analytical fan-beam EICT and PCCT simulations. Each modality was used to image a numerical mouse phantom and contrast-depth phantom containing GNPs ranging from 0.05% to 4% by weight in soft tissue. Contrast-to-noise ratios (CNRs) of gold regions were compared among the three modalities, and XFET's detection limit was quantified based on the Rose criterion. A partial field-of-view (FOV) image was acquired for the phantom region containing 0.05% GNPs.
Results: For the mouse phantom, XFET produced superior CNR values ( , 21.6, and 3.4) compared with CT images obtained with both energy-integrating ( , 4.6, and 1.5) and photon-counting ( , 7.7, and 2.0) detection systems. More generally, XFET outperformed CT for superficial imaging depths ( ) for gold concentrations at and above 0.5%. XFET's surface detection limit was quantified as 0.44% for an average phantom dose of 16 mGy compatible with in vivo imaging. XFET's ability to image partial FOVs was demonstrated, and 0.05% gold was easily detected with an estimated dose of to a localized region of interest.
Conclusions: We demonstrate a proof of XFET's benefit for imaging low concentrations of gold at superficial depths and the feasibility of XFET for in vivo metal mapping in preclinical imaging tasks.
期刊介绍:
JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.