Ultra-high resolution CT and quantitative CT development and clinical applications

超高分辨率CT和定量CT的发展及临床应用

• 批准号: 10929148
• 负责人: HAN WEN
• 金额: $ 166.48万
• 依托单位: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10929148
• 关键词: Affect; Air; Air Movements; Alveolar; American; Area; Arterial calcification due to deficiency of CD73; Blood Vessels; Body part; COVID-19; COVID-19 patient; Calibration; Characteristics; Chest; Clinical; Clinical Protocols; Clinical Research; Clinical Trials; Collaborations; Computed Tomography Scanners; Computer software; Critical Care; Cyst; Dedications; Development; Diffusion; Disease; Disease Management; Disease Progression; Evaluation; Genetic Diseases; Hand; High Resolution Computed Tomography; Hybrids; Image; Image Analysis; Imaging technology; Impairment; Infection; Job' s Syndrome; Joints; Journals; Kidney; Limb structure; Location; Longitudinal Studies; Lower Extremity; Lung; Lung Capacity; Lung diseases; Lymphangioleiomyomatosis; Manuscripts; Measurement; Measures; Mediating; Medicine; Methods; Molecular; Monitor; Mosses; Mucous body substance; Muscle Cramp; Mutation; National Heart, Lung, and Blood Institute; Nodule; Patients; Phase; Physiological; Predisposition; Protocols documentation; Publishing; Radiology Specialty; Recovery; Reporting; Residual state; Resolution; SARS-CoV-2 infection; STAT3 gene; Scanning; Societies; Structure; Structure of parenchyma of lung; Surface; Symptoms; System; Technology; Testing; Time; Touch sensation; Transplantation; Treatment Effectiveness; United States National Institutes of Health; Vascular Diseases; Vascular calcification; Woman; X-Ray Computed Tomography; autosome; calcification; chest computed tomography; clinical application; clinical center; cohort; coping; density; detector; foot; high resolution imaging; improved; long term consequences of COVID-19; lung lesion; novel; pain symptom; participant enrollment; patient population; photon-counting detector; post-COVID-19; pulmonary function decline; rare genetic disorder; structural determinants; tomography; tool; treatment effect; treatment response; ultra high resolution

This project is the main effort of my lab for the last year. On the clinical application front, we developed computed-tomography image analysis and image acquisition technologies that are used in four clinical protocols: 96-H-0100, LAM and other rare cystic lung diseases, PI Joel Moss, NHLBI Pulmonary Branch Lymphangioleiomyomatosis (LAM) is a multi-system disease that affects almost exclusively women. It causes progressive formation of air-filled cysts in the lungs and associated decline of lung function. With a median transplant-free survival of 29 years from the onset of symptoms, computed-tomographic tracking of cystic changes in the lungs is an integral part of the management of the disease, and provides valuable information in clinical studies on the treatment of the disease. This is an on-going collaboration with Dr. Joel Moss since 2018. In the past year we performed 141 CT scans in patients with LAM. With our ultra-high resolution CT method we found previously that very small pulmonary cysts in LAM patients affect the diffusion capacity of the lungs but not airflow (1). This year we developed new image analysis tools to understand this finding. We discovered in a study of 182 LAM patients that the diffusion capacity of the lungs was more closely associated with the total surface area of the pulmonary cysts than the total volume occupied by the cysts. This explains why very small cysts have a large effect on the diffusion capacity of the lungs (2). With several new CT-based metrics, we began to expand our study to answer clinical questions such as when to initiate treatment and ways to predict the effectiveness of treatment. However, we uncovered inconsistencies in CT-derived measurements over a period of decades owing to instrumental changes and physiological variabilities (3). As a remedy, current commercial dedicated software rely on operator input to cope with the variabilites. However, this is impractical for us and also susceptible to subjective factors when it comes to longitudinal studies that include a large number of CT scans over decades from a population of patients. Thus, as part of the next phase of this study, we created an automated method for measuring cystic changes in the lungs. In a test against the current standard semi-automated method, it was as consistent as the semi-automated method in longitudinal measurements over time, and more accurate. A manuscript reporting this technology is being prepared. This method used an image-analysis tool which was developed in the COVID-19 project described below. We continued a development project of a novel method to attain ultra-high resolution in clinical CT scanners by inserting into it a high-resolution photon-counting detector that is directly touching the patients body. This technology targets niche applications where very high resolution in a specific part of the body may be required, such as in the kidneys. A particular technical challenge is to know the precise location and orientation of the inserted detector relative to the bore of the CT scanner, since these vary from patient to patient. We published an online calibration method (4), and recently simplified the method to streamline the workflow of the application of this technology. 20-CC-0113, COVID-19 long term effects in the lung, Collaboration with Dr. Anthony Suffredini, NIH Clinical Center Critical Care Medicine In this study, our collaborator Dr. Suffredini posed to us the question why some post-COVID-19 patients with minimal residual abnormalities in the lungs still have persistent low values of the diffusion capacity of the lungs at three to six months after the infection. We focused on quantitative CT measurements of global characteristics that would not manifest as visible local abnormalities such as reticulations, nodule and bands. Specifically, we developed fully-automated global measurements of vascular structure and parenchymal radio-density for chest CT scans. In a study of 45 patients, we found the diffusion capacity of the lung was associated with the vascular volume fraction of the lung tissue and the parenchymal density. These structural factors independently explained 22% of the variability of the DLCO_adj (% predicted) values among the cohort, in addition to the 27% that was explained by the alveolar volume. The results overall suggest that in patients who had recovered from COVID-19, but had poor recovery of the diffusion capacity of the lungs without clear correlates of radiologic abnormalities, it may be benefitial to assess certain global measures of vascular and parenchymal structures in the lungs from HRCT scans as potential contributors to low diffusion capacity (5). 18-H-0108, Genetic disease ACDC, PI Manfred Boehm, NHLBI Translational Vascular Medicine This protocol studies the rare genetic disease of arterial calcification due to deficiency of CD73, or ACDC. Patients with ACDC have progressive vascular calcification in the extremities and the joints of the hands and feet, with symptoms of pain and cramping in the extremities as early as their twenties. As a collaborator on this protocol, we perform ultra-high resolution CT scans on a yearly basis for the patients enrolled in the protocol, and make CT-based measurements to assess the progression or regression of arterial calcification in the lower extremity of the patients. In the past year we performed 6 CT scans and generated the associated measurements for the clinical team. U01 STAT3/Job's Syndrome We are part of a consortium that involves NIH and other academic centers in a U01 supported study titled The Molecular and Cellular Mechanisms of the STAT3 Mutations-Mediated Pulmonary Disorder in Autosomal Dominant Hyper IgE Syndrome (AD-HIES). One of the specific aims of the study is to assess airway mucus plugs in the lungs using advance CT imaging technologies. Our part is to use our high-resolution CT method to detect mucus plugs in small airways that are not otherwise visible in conventional high-resolution chest CT scans. This collaboration was set up at the end of 2022. This year one patient with Jobs syndrome has been scanned with our technology under this collaboration. Imaging analysis will be performed by another partner in the consortium. 1. Matthew BP, Hasani AM, Chen Y-C, Pirooznia M, Stylianou M, Rollison SF, Machado TR, Quade NM, Jones AM, Julien-Williams P, Taveira-DaSilva A, Chen MY, Moss J, Wen H. Ultra-Small Lung Cysts Impair Diffusion Without Obstructing Air Flow in Lymphangioleiomyomatosis. CHEST; 2021; 160: 199208. 2. Matthew BP, Lebron A, Chen Y-C, Lohr WH, Rollison SF, Worthy TA, Jones AM, Julien-Williams P, Pirooznia M, Chen MY, Moss J, Wen H. Novel Pulmonary Cyst Characteristics Associated with the Diffusing Capacity of the Lung in Lymphangioleiomyomatosis: A Cross-Sectional Clinical Trial. Annals ATS; 2023; 20: 10731076. 3. Matthew B p., Lebron A, Lee S c., Rollison S, Worthy T a., Jones A m., Julien-Williams P, Chen M y., Moss J, Wen H. Longitudinal Consistency of CT-Based Evaluation of the Volumetric Percentage of Cystic Regions in the Lungs of Patients With Lymphangioleiomyomatosis. B40. POTPOURRI IN ILD: SPANNING THE SPECTRUM FROM RARE TO COMMON LUNG DISEASES American Thoracic Society; 2023. p. A3312A3312 4. King DH, Wang M, Bennett EE, Mazilu D, Chen MY, Wen H. Online Geometric Calibration of a Hybrid CT System for Ultrahigh-Resolution Imaging. Tomography; 2022; 8: 25472555. 5. Wen H, Huapaya JA, Kanth SM, Sun J, Matthew BP, Lee SC, Do M, Chen MY, Malayeri AA, Suffredini AF. Quantitative CT Metrics Associated with Variability in the Diffusion Capacity of the Lung of Post-COVID-19 Patients with Minimal Residual Lung Lesions. Journal of Imaging; 2023; 9: 150.

这个项目是我实验室去年的主要工作。在临床应用方面，我们开发了计算机断层成像图像分析和图像采集技术，用于四种临床方案：

项目成果

Optimization of a secondary VOI protocol for lung imaging in a clinical CT scanner.

• DOI: 10.1002/acm2.12354
• 发表时间: 2018-07
• 期刊: Journal of applied clinical medical physics
• 影响因子: 2.1
• 作者: Larsen TC;Gopalakrishnan V;Yao J;Nguyen CP;Chen MY;Moss J;Wen H
• 通讯作者: Wen H

Micro-CT scouting for transmission electron microscopy of human tissue specimens.

• DOI: 10.1111/jmi.12385
• 发表时间: 2016-07
• 期刊: Journal of microscopy
• 影响因子: 2
• 作者: Morales AG;Stempinski ES;Xiao X;Patel A;Panna A;Olivier KN;McShane PJ;Robinson C;George AJ;Donahue DR;Chen P;Wen H
• 通讯作者: Wen H

Ultra-Small Lung Cysts Impair Diffusion Without Obstructing Air Flow in Lymphangioleiomyomatosis.

• DOI: 10.1016/j.chest.2021.01.077
• 发表时间: 2021-07
• 期刊: Chest
• 影响因子: 9.6
• 作者: Matthew BP;Hasani AM;Chen YC;Pirooznia M;Stylianou M;Rollison SF;Machado TR;Quade NM;Jones AM;Julien-Williams P;Taveira-DaSilva A;Chen MY;Moss J;Wen H
• 通讯作者: Wen H