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Lotspeich SC, Richardson BD, Baldoni PL, Enders KP, Hudgens MG. Quantifying the HIV reservoir with dilution assays and deep viral sequencing. Biometrics 2024; 80:ujad018. [PMID: 38364812 PMCID: PMC10873562 DOI: 10.1093/biomtc/ujad018] [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: 02/01/2023] [Revised: 09/29/2023] [Accepted: 11/24/2023] [Indexed: 02/18/2024]
Abstract
People living with HIV on antiretroviral therapy often have undetectable virus levels by standard assays, but "latent" HIV still persists in viral reservoirs. Eliminating these reservoirs is the goal of HIV cure research. The quantitative viral outgrowth assay (QVOA) is commonly used to estimate the reservoir size, that is, the infectious units per million (IUPM) of HIV-persistent resting CD4+ T cells. A new variation of the QVOA, the ultra deep sequencing assay of the outgrowth virus (UDSA), was recently developed that further quantifies the number of viral lineages within a subset of infected wells. Performing the UDSA on a subset of wells provides additional information that can improve IUPM estimation. This paper considers statistical inference about the IUPM from combined dilution assay (QVOA) and deep viral sequencing (UDSA) data, even when some deep sequencing data are missing. Methods are proposed to accommodate assays with wells sequenced at multiple dilution levels and with imperfect sensitivity and specificity, and a novel bias-corrected estimator is included for small samples. The proposed methods are evaluated in a simulation study, applied to data from the University of North Carolina HIV Cure Center, and implemented in the open-source R package SLDeepAssay.
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Affiliation(s)
- Sarah C Lotspeich
- Department of Statistical Sciences, Wake Forest University, Winston-Salem, NC 27109, United States
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Brian D Richardson
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Pedro L Baldoni
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3052, Australia
| | - Kimberly P Enders
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Michael G Hudgens
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
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Ma X, Lu T, Qin D, Cai H, Tang Z, Yang Y, Cui Y, Wang R. Analysis of pulmonary artery variation based on 3D reconstruction of CT angiography. Front Physiol 2023; 14:1156513. [PMID: 37234424 PMCID: PMC10206427 DOI: 10.3389/fphys.2023.1156513] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/12/2023] [Indexed: 05/28/2023] Open
Abstract
Objective: The aim of this study is to acquire pulmonary CT (Computed tomography) angiographic data for the purpose of creating a three-dimensional reconstruction. Additionally, we aim to analyze the features and deviations of the branches in both pulmonary lobes. This information is intended to serve as a more comprehensive and detailed reference for medical professionals when conducting preoperative evaluations and devising surgical plans. Method: Between August 2019 and December 2021, 420 patients were selected from the thoracic surgery department at the First Hospital of Jilin University, and underwent pulmonary 64 channel contrast enhanced CT examinations (Philips ICT 256). The images were acquired at a 1.5 mm slice thickness, and the DCM files that complied with DICOM (Digital Imaging and Communications in Medicine) standards were analysed for 3D (three dimensional) reconstruction using Mimics 22.0 software. The reconstructed pulmonary artery models were assessed by attending chest surgeons and radiologists with over 10 years of clinical experience. The two-dimensional image planes, as well as the coronary and sagittal planes, were utilized to evaluate the arteries. The study analyzed the characteristics and variations of the branches and courses of pulmonary arteries in each lobe of the lungs, with the exception of the subsegmental arterial system. Two chest surgeons and two radiologists with professional titles-all of whom had over a decade of clinical experience-jointly evaluated the 3D models of the pulmonary artery and similarly assessed the characteristics and variations of the branches and courses in each lobe of the lungs. Results: Significant variations were observed in the left superior pulmonary artery across the 420 subjects studied. In the left upper lobe, the blood supply of 4 arteries accounted for 50.5% (n = 212), while the blood supply of 2 arteries in the left lower lobe was the most common, accounting for 79.5% (n = 334). The greatest variation in the right pulmonary artery was observed in the branch supply of the right upper lobe mediastinal artery. In the majority of cases (77.9%), there were two arteries present, which was the most common configuration observed accounting for 64% (n = 269). In the right inferior lobe of the lung, there were typically 2-4 arteries, with 2 arteries being the most common configuration (observed in 79% of cases, n = 332). Conclusion: The three-dimensional reconstruction of pulmonary artery CT angiography enables clear observation of the branches and distribution of the pulmonary artery while also highlighting any variations. This technique holds significant clinical value for preoperative assessments regarding lesions and blood vessels.
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Affiliation(s)
- Xiaochao Ma
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Tianyu Lu
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Da Qin
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Hongfei Cai
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Ze Tang
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Yue Yang
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Youbin Cui
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Rui Wang
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, Jilin, China
- School of Public Health, Jilin University, Changchun, Jilin, China
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