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Zhang J, Hu M, Cheng Q, Wang S, Liu Y, Zhou Y, Li J, Wei W. Achieving sub-millisievert CT colonography for accurate colorectal tumor detection using smart examination protocols: a prospective self-controlled study. Abdom Radiol (NY) 2024:10.1007/s00261-024-04557-5. [PMID: 39276190 DOI: 10.1007/s00261-024-04557-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 08/28/2024] [Accepted: 08/29/2024] [Indexed: 09/16/2024]
Abstract
PURPOSE To assess the feasibility of combining Auto-kVp selection technique, higher preset ASIR-V and noise index (NI) to realize individualized sub-mSv CT colonography (CTC) for accurate colorectal tumor detection and localization. METHODS Ninety patients with suspected colorectal cancer (CRC) were prospectively enrolled to undergo standard dose CTC (SDCTC) in the prone and ultra-low dose CTC (ULDCTC) in the supine position. SDCTC used 120 kVp, preset ASIR-V of 30%, SmartmA for a NI of 13; ULDCTC used Auto-kVp selection technique with 80 or 100 kVp, preset ASIR-V of 60%, SmartmA for a NI of 13 for 80 kVp, and NI of 15 for 100 kVp. The effective dose (ED), image quality [signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of colorectal neoplasms] between the two protocols were compared and the accuracies of tumor locations were evaluated for CTC in comparison with the surgery results. RESULTS The mean ED of the ULDCTC-80 kVp subgroup was 0.70 mSv, 71.43% lower than the 2.45 mSv for the 120 kVp group, while that of the ULDCTC-100 kVp subgroup was 0.98 mSv, 73.00% lower than the 3.63 mSv for the 120 kVp group (P < 0.001). The tumor SNR and CNR of the ULDCTC were higher than those of SDCTC (P < 0.05), while there was no difference in the subjective image quality between them with good inter-observer agreement (Kappa: 0.805-0.923). Both SDCTC and ULDCTC groups had high detection rate of colorectal tumors, along with good consistency in determining tumor location compared with surgery reports (Kappa: 0.718-0.989). CONCLUSION The combination of Auto-kVp selection, higher preset ASIR-V and NI achieves individualized sub-mSv CTC with good performance in detecting and locating CRC with surgery and consistent results between SDCTC and ULDCTC.
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Affiliation(s)
- Jingyi Zhang
- First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Mengting Hu
- First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Qiye Cheng
- First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Shigeng Wang
- First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yijun Liu
- First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yujing Zhou
- First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Jianying Li
- CT Research, GE Healthcare, Dalian, Dalian, China
| | - Wei Wei
- First Affiliated Hospital of Dalian Medical University, Dalian, China.
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Chen Y, Huang Z, Feng L, Zou W, Kong D, Zhu D, Dai G, Zhao W, Zhang Y, Luo M. Deep Learning-Based Reconstruction Improves the Image Quality of Low-Dose CT Colonography. Acad Radiol 2024; 31:3191-3199. [PMID: 38290889 DOI: 10.1016/j.acra.2024.01.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 01/11/2024] [Accepted: 01/11/2024] [Indexed: 02/01/2024]
Abstract
RATIONALE AND OBJECTIVES To evaluate the image quality of low-dose CT colonography (CTC) using deep learning-based reconstruction (DLR) compared to iterative reconstruction (IR). MATERIALS AND METHODS Adults included in the study were divided into four groups according to body mass index (BMI). Routine-dose (RD: 120 kVp) CTC images were reconstructed with IR (RD-IR); low-dose (LD: 100kVp) images were reconstructed with IR (LD-IR) and DLR (LD-DLR). The subjective image quality was rated on a 5-point scale by two radiologists independently. The parameters for objective image quality included noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The Friedman test was used to compare the image quality among RD-IR, LD-IR and LD-DLR. The KruskalWallis test was used to compare the results among different BMI groups. RESULTS A total of 270 volunteers (mean age: 47.94 years ± 11.57; 115 men) were included. The effective dose of low-dose CTC was decreased by approximately 83.18% (5.18mSv ± 0.86 vs. 0.86mSv ± 0.05, P < 0.001). The subjective image quality score of LD-DLR was superior to that of LD-IR (3.61 ± 0.56 vs. 2.70 ± 0.51, P < 0.001) and on par with the RD- IR's (3.61 ± 0.56 vs. 3.74 ± 0.52, P = 0.486). LD-DLR exhibited the lowest noise, and the maximum SNR and CNR compared to RD-IR and LD-IR (all P < 0.001). No statistical difference was found in the noise of LD-DLR images between different BMI groups (all P > 0.05). CONCLUSION Compared to IR, DLR provided low-dose CTC with superior image quality at an average radiation dose of 0.86mSv, which may be promising in future colorectal cancer screening.
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Affiliation(s)
- Yanshan Chen
- Department of Radiology, the Six Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Biomedical Innovation Center, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Department of Radiology, Jinling Hospital, the First School of Clinical Medicine, Southern Medical University, Nanjing, Jiangsu 210002, China (Y.C.)
| | - Zixuan Huang
- Department of Radiology, the Six Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Biomedical Innovation Center, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Department of Radiology, Guangdong Second Traditional Chinese Medicine Hospital, Guangzhou, Guangdong 510095, China (Z.H.)
| | - Lijuan Feng
- Department of Radiology, the Six Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Biomedical Innovation Center, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Department of Radiology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China (L.F.)
| | - Wenbin Zou
- Department of Radiology, the Six Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Biomedical Innovation Center, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.)
| | - Decan Kong
- Department of Radiology, the Six Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Biomedical Innovation Center, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.)
| | - Dongyun Zhu
- Department of Radiology, the Six Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Biomedical Innovation Center, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.)
| | - Guochao Dai
- Medical Imaging Center, the First People's Hospital of Kashi Area, Kashi, Xinjiang 844000, China (G.D.)
| | - Weidong Zhao
- Department of Radiology, the Second Hospital of Shanxi Medical University, Taiyuan, Shanxi 030001, China (W.Z.)
| | - Yuanke Zhang
- School of Computer Science, Qufu Normal University, Rizhao, Shandong 276826, China (Y.Z.)
| | - Mingyue Luo
- Department of Radiology, the Six Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Biomedical Innovation Center, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.).
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Fong G, Herts B, Primak A, Segars P, Li X. Effect of tin spectral filtration on organ and effective dose in CT colonography and CT lung cancer screening. Med Phys 2024; 51:103-112. [PMID: 37962008 DOI: 10.1002/mp.16836] [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: 05/26/2023] [Revised: 10/07/2023] [Accepted: 10/29/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND Studies of tin spectral filtration have demonstrated potential in reducing radiation dose while maintaining image quality for unenhanced computed tomography (CT) scans. The extent of dose reduction, however, was commonly measured using the change in the scanner's reported CTDIvol . This method does not account for how tin filtration affects patient organ and effective dose. PURPOSE To investigate the effect of tin filtration on patient organ and effective dose for CT Lung Cancer Screening (LCS) and CT Colonography (CTC). METHODS A previously-developed Monte Carlo program was adapted to model a 96-row CT scanner (Somatom Force, Siemens Healthineers) with tin filtration capabilities at 100 kV (100Sn) and 150 kV (150Sn). The program was then validated using experimental CTDIvol measurements at all available kV (70-150 kV) and tin-filtered kV options (100Sn and 150Sn). After validation, the program simulated LCS scans of the chest and CTC scan of the abdomen-pelvis for a population of 53 computational patient models from the extended cardiac-torso family. Each scan was performed using three different spectra: 120 kV, 100Sn, and 150Sn. CTDIvol -normalized organ doses and DLP-normalized effective doses, commonly referred to as dose conversion factors, were compared between the different spectra. RESULTS For all LCS and CTC scans, CTDIvol -normalized organ doses and DLP-normalized effective doses increased with increasing beam hardness (120 kV, 100Sn, 150 Sn). For LCS, relative for 120 kV, conversion factors for 100Sn produced a median increase in effective dose of 9%, with organ dose increases of 8% to lung, 5% to breast, 15% to thyroid, and 3% to skin. Conversion factors for 150Sn produced a median increase in effective dose of 20%, with organ dose increases of 16%, 18%, 26%, and 12% to these same organs, respectively. For CTC, relative for 120 kV, conversion factors for 100Sn produced a median increase in effective dose of 12%, with organ dose increases of 9% to colon, 10% to liver, 11% to stomach, and 4% to skin. Conversion factors for 150Sn produced a median increase in effective dose of 21%, with organ dose increases of 16%, 17%, 19%, and 10% to these same organs, respectively. CONCLUSIONS Results show that dose conversion factors are greater when using tin filtration and should be considered when evaluating tin's potential for dose reduction.
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Affiliation(s)
- Grant Fong
- Cleveland Clinic, Imaging Institute, Cleveland, Ohio, USA
| | - Brian Herts
- Cleveland Clinic, Imaging Institute, Cleveland, Ohio, USA
| | - Andrew Primak
- Siemens Medical Solutions USA Inc., Malvern, Pennsylvania, USA
| | - Paul Segars
- Duke University, Durham, North Carolina, USA
| | - Xiang Li
- Cleveland Clinic, Imaging Institute, Cleveland, Ohio, USA
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Guido G, Polici M, Nacci I, Bozzi F, De Santis D, Ubaldi N, Polidori T, Zerunian M, Bracci B, Laghi A, Caruso D. Iterative Reconstruction: State-of-the-Art and Future Perspectives. J Comput Assist Tomogr 2023; 47:244-254. [PMID: 36728734 DOI: 10.1097/rct.0000000000001401] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
ABSTRACT Image reconstruction processing in computed tomography (CT) has evolved tremendously since its creation, succeeding at optimizing radiation dose while maintaining adequate image quality. Computed tomography vendors have developed and implemented various technical advances, such as automatic noise reduction filters, automatic exposure control, and refined imaging reconstruction algorithms.Focusing on imaging reconstruction, filtered back-projection has represented the standard reconstruction algorithm for over 3 decades, obtaining adequate image quality at standard radiation dose exposures. To overcome filtered back-projection reconstruction flaws in low-dose CT data sets, advanced iterative reconstruction algorithms consisting of either backward projection or both backward and forward projections have been developed, with the goal to enable low-dose CT acquisitions with high image quality. Iterative reconstruction techniques play a key role in routine workflow implementation (eg, screening protocols, vascular and pediatric applications), in quantitative CT imaging applications, and in dose exposure limitation in oncologic patients.Therefore, this review aims to provide an overview of the technical principles and the main clinical application of iterative reconstruction algorithms, focusing on the strengths and weaknesses, in addition to integrating future perspectives in the new era of artificial intelligence.
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Affiliation(s)
- Gisella Guido
- From the Department of Surgical Medical Sciences and Translational Medicine, Sapienza University of Rome - Radiology Unit, Sant'Andrea University Hospital, Rome, Italy
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Diagnostic accuracy of ultra-low-dose CT colonography for the detection of colorectal polyps: a feasibility study. Jpn J Radiol 2022; 40:831-839. [PMID: 35344130 DOI: 10.1007/s11604-022-01266-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 03/10/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE The aim of this feasibility study was to evaluate the diagnostic accuracy of ultra-low-dose CT colonography using iterative reconstruction algorithms with reference to standard colonoscopy. MATERIALS AND METHODS Prior to this study, a phantom study was performed to investigate the optimal protocol for ultra-low-dose CT colonography. A total of 206 patients with average/high risk of colorectal cancer were recruited. After undergoing full bowel preparation, the patients were scanned in the prone and supine positions with the CT conditions set to 120 kV, standard deviation 45 to 50, and an adaptive iterative reconstruction algorithm applied. Two expert readers read the images independently. The main outcome measures were the per-patient and per-polyp accuracies for the detection of polyps ≥ 10 mm, with colonoscopy results as the reference standard. RESULTS Two hundred patients (102 females, mean age 67.5 years) underwent both ultra-low-dose CT colonography and colonoscopy on the same day. The mean radiation exposure dose was 0.64 ± 0.34 mSv. On colonoscopy, 39 patients had 45 polyps ≥ 10 mm (non-polypoid morphology 7), including 4 cancers. Per-patient sensitivity, specificity, and accuracy of CT colonography for polyps ≥ 10 mm were 0.74, 0.96, and 0.92 for reader one, and 0.74, 0.99, and 0.94 for reader two, respectively. Per-polyp sensitivities for polyps ≥ 10 mm were 0.73 for reader one and 0.71 for reader two. On subgroup analysis by morphology, non-polypoid polyps ≥ 10 mm were not detected by both readers. CONCLUSION Extreme ultra-low-dose CT colonography had an insufficient diagnostic performance for the detection of polyps ≥ 10 mm, because it was unable to detect non-polypoid polyps. This study showed that the problem with ultra-low-dose CT colonography was the lack of detectability of small-size polyps, especially non-polypoid polyps. To use ultra-low-dose CT colonography clinically, it is necessary to resolve the problems identified by this study.
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