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Meloni A, Maffei E, Clemente A, De Gori C, Occhipinti M, Positano V, Berti S, La Grutta L, Saba L, Cau R, Bossone E, Mantini C, Cavaliere C, Punzo B, Celi S, Cademartiri F. Spectral Photon-Counting Computed Tomography: Technical Principles and Applications in the Assessment of Cardiovascular Diseases. J Clin Med 2024; 13:2359. [PMID: 38673632 PMCID: PMC11051476 DOI: 10.3390/jcm13082359] [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: 03/16/2024] [Revised: 04/15/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
Spectral Photon-Counting Computed Tomography (SPCCT) represents a groundbreaking advancement in X-ray imaging technology. The core innovation of SPCCT lies in its photon-counting detectors, which can count the exact number of incoming x-ray photons and individually measure their energy. The first part of this review summarizes the key elements of SPCCT technology, such as energy binning, energy weighting, and material decomposition. Its energy-discriminating ability represents the key to the increase in the contrast between different tissues, the elimination of the electronic noise, and the correction of beam-hardening artifacts. Material decomposition provides valuable insights into specific elements' composition, concentration, and distribution. The capability of SPCCT to operate in three or more energy regimes allows for the differentiation of several contrast agents, facilitating quantitative assessments of elements with specific energy thresholds within the diagnostic energy range. The second part of this review provides a brief overview of the applications of SPCCT in the assessment of various cardiovascular disease processes. SPCCT can support the study of myocardial blood perfusion and enable enhanced tissue characterization and the identification of contrast agents, in a manner that was previously unattainable.
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Affiliation(s)
- Antonella Meloni
- Bioengineering Unit, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.)
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Erica Maffei
- Department of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico SYNLAB SDN, 80131 Naples, Italy; (E.M.); (C.C.); (B.P.)
| | - Alberto Clemente
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Carmelo De Gori
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Mariaelena Occhipinti
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Vicenzo Positano
- Bioengineering Unit, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.)
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Sergio Berti
- Diagnostic and Interventional Cardiology Department, Fondazione G. Monasterio CNR-Regione Toscana, 54100 Massa, Italy;
| | - Ludovico La Grutta
- Department of Radiology, University Hospital “P. Giaccone”, 90127 Palermo, Italy;
| | - Luca Saba
- Department of Radiology, University Hospital of Cagliari, 09042 Monserrato (CA), Italy; (L.S.); (R.C.)
| | - Riccardo Cau
- Department of Radiology, University Hospital of Cagliari, 09042 Monserrato (CA), Italy; (L.S.); (R.C.)
| | - Eduardo Bossone
- Department of Cardiology, Ospedale Cardarelli, 80131 Naples, Italy;
| | - Cesare Mantini
- Department of Radiology, “G. D’Annunzio” University, 66100 Chieti, Italy;
| | - Carlo Cavaliere
- Department of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico SYNLAB SDN, 80131 Naples, Italy; (E.M.); (C.C.); (B.P.)
| | - Bruna Punzo
- Department of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico SYNLAB SDN, 80131 Naples, Italy; (E.M.); (C.C.); (B.P.)
| | - Simona Celi
- BioCardioLab, Fondazione G. Monasterio CNR-Regione Toscana, 54100 Massa, Italy;
| | - Filippo Cademartiri
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
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Dehlinger N, Bach J, Willaume T, Ohana M, Dillenseger JP. Accuracy of iodine quantification in dual energy CT: A phantom study across 3 different CT systems. Radiography (Lond) 2024; 30:226-230. [PMID: 38035437 DOI: 10.1016/j.radi.2023.11.015] [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: 08/22/2023] [Revised: 10/30/2023] [Accepted: 11/14/2023] [Indexed: 12/02/2023]
Abstract
INTRODUCTION No study has rigorously compared the performances of iodine quantification on recent CT systems employing different emission-based technologies, depending on the manufacturers and models. METHODS A specific bespoke phantom was used for this study, with 12 known concentrations of iodinated contrast agent: 0.4, 0.5, 1.0, 2.0, 3.0, 4.0, 5.0, 10.0, 15.0, 20.0, 30.0 and 50.0 mg/mL. Three different dual-energy scanners were tested: one system using dual-source acquisition (CT#1) and two systems using Fast kilovolt-peak switching technology ± artificial intelligence (AI) reconstruction methods (CT#2 and #3) from two different manufacturers. For each system, helical scans were performed following recommended clinical protocols. Four acquisitions were performed per iodine concentration (mg/mL), and measurements were made on iodine-maps using ROIs. Mean measured values were compared to the known concentrations, and the absolute quantification error (AQE) and the relative percentage error (RPE) were used to compare the performances of each CT. RESULTS The accuracy of the obtained measurements varied depending on the studied model but not on the acquisition mode (dual-source vs kVp switch ± AI). The quantification was more precise at high concentrations. RPE values were below 10 % with CT#2 (kVp switch) and below 25 % with CT#1 (dual-source), but were significantly higher with CT#3 (kVp switch + AI), exceeding 50 % at low concentrations (<3 mg/mL). CONCLUSIONS With the help of a phantom, we identified variability in the results accuracy depending on the CT model, with sometimes significant deviation. Considering the performances of the different DECT technologies in iodine mapping, dual-source (CT#1) and kVp switch (CT#2) technologies appear more accurate than kVp switch technology combined with deep-learning-based reconstruction (CT#3) especially at low concentrations (<3 mg/mL). IMPLICATIONS FOR PRACTICE As the primary and daily user of medical imaging devices, the radiographer role is to be attentive to the performance of imaging systems, particularly when performing quantitative acquisitions like iodine-quantification. In CT quantitative imaging (iodine map), it's essential for radiographers to consider their CT systems as measuring tools, and to be aware of their accuracies and limits.
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Affiliation(s)
- N Dehlinger
- Pole d'imagerie médicale, Hôpitaux universitaire de Strasbourg, Strasbourg, France
| | - J Bach
- Pole d'imagerie médicale, Hôpitaux universitaire de Strasbourg, Strasbourg, France
| | - T Willaume
- Pole d'imagerie médicale, Hôpitaux universitaire de Strasbourg, Strasbourg, France
| | - M Ohana
- Pole d'imagerie médicale, Hôpitaux universitaire de Strasbourg, Strasbourg, France; ICube - UMR 7357, CNRS, Université de Strasbourg, Strasbourg, France; Faculté de médecine, maïeutique et des sciences de la santé, Université de Strasbourg, Strasbourg, France
| | - J P Dillenseger
- Pole d'imagerie médicale, Hôpitaux universitaire de Strasbourg, Strasbourg, France; ICube - UMR 7357, CNRS, Université de Strasbourg, Strasbourg, France; Faculté de médecine, maïeutique et des sciences de la santé, Université de Strasbourg, Strasbourg, France.
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Dual-Energy Computed Tomography–Derived Iodine Density and Spectral Attenuation Analysis for Differentiation of Inverted Papilloma and Sinonasal Squamous Cell Carcinoma/Lymphoma. J Comput Assist Tomogr 2022; 46:953-960. [DOI: 10.1097/rct.0000000000001370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Li Z, Liu Z, Guo Y, Wang S, Qu X, Li Y, Pan Y, Zhang L, Su D, Yang Q, Tao X, Yue Q, Xian J. Dual-energy CT-based radiomics nomogram in predicting histological differentiation of head and neck squamous carcinoma: a multicenter study. Neuroradiology 2021; 64:361-369. [PMID: 34860278 DOI: 10.1007/s00234-021-02860-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 11/09/2021] [Indexed: 02/05/2023]
Abstract
PURPOSE To develop and validate a dual-energy CT (DECT)-based radiomics nomogram from multicenter trials for predicting the histological differentiation of head and neck squamous cell carcinoma (HNSCC). METHODS A total of 178 patients (112 in the training and 66 in the validation cohorts) from eight institutions with histologically proven HNSCCs were included in this retrospective study. Radiomics-signature models were constructed from features extracted from virtual monoenergetic images (VMI) and iodine-based material decomposition images (IMDI), reconstructed from venous-phase DECT images. Clinical factors were also assessed to build a clinical model. Multivariate logistic regression analysis was used to develop a nomogram combining the radiomics signature models and clinical model for predicting poorly differentiated HNSCC and moderately well-differentiated HNSCC. The predictive performance of the clinical model, radiomics signature models, and nomogram was compared. The calibration degree of the nomogram was also assessed. RESULTS The tumor location, VMI-signature, and IMDI-signature were associated with the degree of HNSCC differentiation, and areas under the ROC curves (AUCs) were 0.729, 0.890, and 0.833 in the training cohort and 0.627, 0.859, and 0.843 in the validation cohort, respectively. The nomogram incorporating tumor location and two radiomics-signature models yielded the best performance in training (AUC = 0.987) and validation (AUC = 0.968) cohorts with a good calibration degree. CONCLUSION The nomogram that integrated the DECT-based radiomics-signature models and tumor location showed good performance in predicting histological differentiation degree of HNSCC, providing a novel combination for predicting HNSCC differentiation.
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Affiliation(s)
- Zheng Li
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1, DongJiaoMinXiang Street, Dongcheng District, Beijing, 100730, China
| | - Zhaohui Liu
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1, DongJiaoMinXiang Street, Dongcheng District, Beijing, 100730, China
| | - Yan Guo
- Pharmaceutical Diagnostics, Precision Health Institute, GE Healthcare China, Beijing, 100176, China
| | - Sicong Wang
- Pharmaceutical Diagnostics, Precision Health Institute, GE Healthcare China, Beijing, 100176, China
| | - Xiaoxia Qu
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1, DongJiaoMinXiang Street, Dongcheng District, Beijing, 100730, China
| | - Yajun Li
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, 410011, China
| | - Yucheng Pan
- Department of Radiology, Eye Ear Nose and Throat Hospital of Fudan University, Shanghai, 200031, China
| | - Longjiang Zhang
- Department of Diagnostic Radiology, General Hospital of Eastern Theater Command/Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, China
| | - Danke Su
- Imaging Center, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning, 530021, China
| | - Qian Yang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Xiaofeng Tao
- Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Qiang Yue
- Department of Radiology, West China Hospital, West China Medical School, Sichuan University, Chengdu, 610041, China
| | - Junfang Xian
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1, DongJiaoMinXiang Street, Dongcheng District, Beijing, 100730, China.
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Adam SZ, Rabinowich A, Kessner R, Blachar A. Spectral CT of the abdomen: Where are we now? Insights Imaging 2021; 12:138. [PMID: 34580788 PMCID: PMC8476679 DOI: 10.1186/s13244-021-01082-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 08/16/2021] [Indexed: 12/14/2022] Open
Abstract
Spectral CT adds a new dimension to radiological evaluation, beyond assessment of anatomical abnormalities. Spectral data allows for detection of specific materials, improves image quality while at the same time reducing radiation doses and contrast media doses, and decreases the need for follow up evaluation of indeterminate lesions. We review the different acquisition techniques of spectral images, mainly dual-source, rapid kV switching and dual-layer detector, and discuss the main spectral results available. We also discuss the use of spectral imaging in abdominal pathologies, emphasizing the strengths and pitfalls of the technique and its main applications in general and in specific organs.
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Affiliation(s)
- Sharon Z Adam
- Department of Diagnostic Radiology, Tel Aviv Sourasky Medical Center, 6 Weizmann St., 6423906, Tel Aviv, Israel. .,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Aviad Rabinowich
- Department of Diagnostic Radiology, Tel Aviv Sourasky Medical Center, 6 Weizmann St., 6423906, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Rivka Kessner
- Department of Diagnostic Radiology, Tel Aviv Sourasky Medical Center, 6 Weizmann St., 6423906, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Arye Blachar
- Department of Diagnostic Radiology, Tel Aviv Sourasky Medical Center, 6 Weizmann St., 6423906, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
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Wu LD, Wen K, Cheng ZR, Alwalid O, Han P. Retroperitoneal bronchogenic cyst in suprarenal region treated by laparoscopic resection: A case report. World J Clin Cases 2021; 9:7245-7250. [PMID: 34540985 PMCID: PMC8409186 DOI: 10.12998/wjcc.v9.i24.7245] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 06/10/2021] [Accepted: 07/02/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Bronchogenic cysts (BCs) are benign congenital foregut malformations that are mostly present in the mediastinum and pulmonary parenchyma but rarely seen in the retroperitoneum.
CASE SUMMARY We report the case of 17-year-old girl who complained of epigastric pain. A cystic lesion was found in the left suprarenal region on spectral computed tomography. The ovoid, well-defined, and homogeneous cystic lesion revealed slightly enhancement on conventional imaging but no enhancement on 40 KeV virtual mono-energetic images. The iodine density value of the lesion was 0.001 mg/mL and the Z-effective value was 7.25, which were close to those of fluid material in in vitro experiments. Magnetic resonance imaging revealed a cystic mass of intermediate signal intensity on T1-weighted imaging and high signal intensity on T2-weighted imaging. A laparoscopic surgery was carried out. Intraoperatively, a cystic lesion with a smooth surface was found in the left retroperitoneum. And the cystic wall was completely resected after intracystic fluid was suctioned. The histopathological examination findings of the lesion were compatible with BC. The patient recovered uneventfully without sighs of recurrence during a 10-mo follow-up period.
CONCLUSION Radiological examinations play a significant role in the diagnosis of suprarenal BCs and spectral images offer additional spectral parameters. Accurate preoperative diagnoses of retroperitoneal BCs based on thorough imaging examinations are beneficial to the operation of laparoscopic resection.
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Affiliation(s)
- Lei-Di Wu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, Hubei Province, China
| | - Kan Wen
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, Hubei Province, China
| | - Zi-Rui Cheng
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, Hubei Province, China
| | - Osamah Alwalid
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, Hubei Province, China
| | - Ping Han
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, Hubei Province, China
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Yoon JH, Lee JM, Kim JH, Lee KB, Kim H, Hong SK, Yi NJ, Lee KW, Suh KS. Hepatic fibrosis grading with extracellular volume fraction from iodine mapping in spectral liver CT. Eur J Radiol 2021; 137:109604. [PMID: 33618210 DOI: 10.1016/j.ejrad.2021.109604] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 01/28/2021] [Accepted: 02/11/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE To determine whether hepatic extracellular volume fraction (ECV) obtained from iodine density map (ECV-iodine) can be used to estimate hepatic fibrosis grade and to compare performance with ECV measured using Hounsfield units (ECV-HU). METHODS From December 2016 to March 2019, patients who underwent liver resection or biopsy within four weeks after spectral liver CT were included. ECV-iodine and ECV-HU were calculated using the equilibrium phase. Within each of these, comparison of ECVs was made for different fibrosis grades (F0 - 1 vs. F2 - 3 vs. F4) and also for patients with compensated and decompensated cirrhosis. The diagnostic performance of ECVs in detecting clinically significant fibrosis (≥ F2) and cirrhosis (F4) was assessed using ROC analysis. RESULTS A total of 144 patients (men = 98, mean age 58.1 ± 11.5 years) were included. The ECV-iodine value was significantly higher in cirrhosis (33.6 ± 6.8 %) than those with F0 - 1 (25.0 ± 3.7 %) or F2 - 3 (28.3 ± 3.4 %, P < 0.001 for all). It was significantly higher in decompensated cirrhosis than those with compensated cirrhosis (36.5 ± 7.2 % vs. 30.7 ± 5.0 %, respectively; P < 0.001). The AUC of ECV-iodine was 0.82 for detecting F2 or above (cut-off value, > 26.9 %) and 0.81 for detecting cirrhosis (cut-off value, > 29 %). ECV-iodine had a significantly higher AUC than ECV-HU for detecting F2 or above (AUC: 0.69, P < 0.001) and cirrhosis (AUC: 0.74, P = 0.04). CONCLUSIONS ECV-iodine from spectral CT was able to detect clinically significant hepatic fibrosis and cirrhosis.
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Affiliation(s)
- Jeong Hee Yoon
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea.
| | - Jae Hyun Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
| | - Kyoung-Bun Lee
- Department of Pathology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
| | - Haeryoung Kim
- Department of Pathology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
| | - Suk Kyun Hong
- Department of Surgery, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
| | - Nam-Joon Yi
- Department of Surgery, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
| | - Kwang-Woong Lee
- Department of Surgery, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
| | - Kyung-Suk Suh
- Department of Surgery, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
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Iwano S, Kamiya S, Ito R, Nakamura S, Naganawa S. Iodine-related attenuation in contrast-enhanced dual-energy computed tomography in small-sized solid-type lung cancers is associated with the postoperative prognosis. Cancer Imaging 2021; 21:7. [PMID: 33413669 PMCID: PMC7791656 DOI: 10.1186/s40644-020-00368-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 12/11/2020] [Indexed: 01/07/2023] Open
Abstract
Background To investigate the correlation between iodine-related attenuation in contrast-enhanced dual-energy computed tomography (DE-CT) and the postoperative prognosis of surgically resected solid-type small-sized lung cancers. Methods We retrospectively reviewed the DE-CT findings and postoperative course of solid-type lung cancers ≤3 cm in diameter. After injection of iodinated contrast media, arterial phases were scanned using 140-kVp and 80-kVp tube voltages. Three-dimensional iodine-related attenuation (3D-IRA) of primary tumors at the arterial phase was computed using the “lung nodule” application software. The corrected 3D-IRA normalized to the patient’s body weight and contrast medium concentration was then calculated. Results A total of 120 resected solid-type lung cancers ≤3 cm in diameter were selected for analysis (82 males and 38 females; mean age, 67 years). During the observation period (median, 47 months), 32 patients showed postoperative recurrence. Recurrent tumors had significantly lower 3D-IRA and corrected 3D-IRA at early phase compared to non-recurrent tumors (p = 0.046 and p = 0.027, respectively). The area under the receiver operating characteristic curve for postoperative recurrence was 0.624 for the corrected 3D-IRA at early phase (p = 0.025), and the cutoff value was 5.88. Kaplan–Meier curves for disease-free survival indicated that patients showing tumors with 3D-IRA > 5.88 had a significantly better prognosis than those with tumors showing 3D-IRA < 5.88 (p = 0.017). Conclusions The 3D-IRA of small-sized solid-type lung cancers on contrast-enhanced DE-CT was significantly associated with postoperative prognosis, and low 3D-IRA tumors showed a higher TNM stage and a significantly poorer prognosis.
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Affiliation(s)
- Shingo Iwano
- Department of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan.
| | - Shinichiro Kamiya
- Department of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Rintaro Ito
- Department of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Shota Nakamura
- Department of Thoracic Surgery, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Shinji Naganawa
- Department of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
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Tunlayadechanont P, Panyaping T, Kaewkerd B. Role of Quantitative Spectral CT Analysis for Differentiation of Orbital Lymphoma and Other Orbital Lymphoproliferative Disease. Eur J Radiol 2020; 133:109372. [PMID: 33130359 DOI: 10.1016/j.ejrad.2020.109372] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 10/08/2020] [Accepted: 10/19/2020] [Indexed: 11/27/2022]
Abstract
PURPOSE To investigate the value of quantitative parameters from spectral computed tomography for the differentiation of orbital lymphoma from other lymphoproliferative disease, including idiopathic orbital inflammatory disease (IOID) and IgG4-related disease (IgG4-RD). METHODS Patients with orbital masses who underwent pre-treatment contrast-enhanced spectral CT were enrolled in this retrospective study. The subjects were divided into lymphoma and other orbital lymphoproliferative disease groups. Qualitative imaging features (margin, location, enhancement pattern, cranial nerves, soft tissue, and bone involvement) were reviewed. Quantitative parameters (iodine density and spectral attenuation curve slope) derived from spectral CT were measured. RESULTS Eleven patients had orbital lymphoma and 11 had other orbital lymphoproliferative diseases (idiopathic orbital inflammatory disease (IOID), n = 5; IgG4-related disease (IgG4-RD), n = 6). Qualitative analysis showed no significant difference between the two groups. There was significantly higher iodine density in orbital lymphoma (1.24 ± 0.24 mg/ml) than in IOID/IgG4-RD (0.83 ± 0.23 mg/ml; P = 0.001). An iodine density threshold of 1.0 mg/ml gave sensitivity, specificity, and accuracy of 81.8%, with an area under the curve of 0.876 (P = 0.0003). Orbital lymphoma had a significantly higher iodine spectral attenuation curve slope (2.44 ± 0.51 HU/keV) than IOID/IgG4-RD (1.66 ± 0.47 HU/keV; P = 0.001). A threshold of 1.99 HU/keV for the spectral attenuation curve slope of 40-70 keV gave sensitivity, specificity, and accuracy of 81.8%, with an area under the curve of 0.884 (P = 0.0002). CONCLUSIONS Quantitative spectral CT parameters can help differentiate orbital lymphoma from other orbital lymphoproliferative disease, with lymphoma having a significantly higher iodine density value and spectral attenuation curve slope than IOID/IgG4-RD.
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Affiliation(s)
- Padcha Tunlayadechanont
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, 270 Rama VI Road, Ratchathewi, Bangkok, 10400, Thailand.
| | - Theeraphol Panyaping
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, 270 Rama VI Road, Ratchathewi, Bangkok, 10400, Thailand.
| | - Boonyarat Kaewkerd
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, 270 Rama VI Road, Ratchathewi, Bangkok, 10400, Thailand.
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Wu J, Zhang Q, Zhao Y, Liu Y, Chen A, Li X, Wu T, Li J, Guo Y, Liu A. Radiomics Analysis of Iodine-Based Material Decomposition Images With Dual-Energy Computed Tomography Imaging for Preoperatively Predicting Microsatellite Instability Status in Colorectal Cancer. Front Oncol 2019; 9:1250. [PMID: 31824843 PMCID: PMC6883423 DOI: 10.3389/fonc.2019.01250] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 10/30/2019] [Indexed: 12/11/2022] Open
Abstract
Purpose: The aim of this study was to investigate the value of radiomics analysis of iodine-based material decomposition (MD) images with dual-energy computed tomography (DECT) imaging for preoperatively predicting microsatellite instability (MSI) status in colorectal cancer (CRC). Methods: This study included 102 CRC patients proved by postoperative pathology, and their MSI status was confirmed by immunohistochemistry staining. All patients underwent preoperative DECT imaging scanned on either a Revolution CT or Discovery CT 750HD scanner, and the iodine-based MD images in the venous phase were reconstructed. The clinical, CT-reported, and radiomics features were obtained and analyzed. Data from the Revolution CT scanner were used to establish a radiomics model to predict MSI status (70% samples were randomly selected as the training set, and the remaining samples were used to validate); and data from the Discovery CT 750HD scanner were used to test the radiomics model. The stable radiomics features with both inter-user and intra-user stability were selected for the next analysis. The feature dimension reduction was performed by using Student's t-test or Mann–Whitney U-test, Spearman's rank correlation test, min–max standardization, one-hot encoding, and least absolute shrinkage and selection operator selection method. The multiparameter logistic regression model was established to predict MSI status. The model performances were evaluated: The discrimination performance was accessed by receiver operating characteristic (ROC) curve analysis; the calibration performance was tested by calibration curve accompanied by Hosmer–Lemeshow test; the clinical utility was assessed by decision curve analysis. Results: Nine top-ranked features were finally selected to construct the radiomics model. In the training set, the area under the ROC curve (AUC) was 0.961 (accuracy: 0.875; sensitivity: 1.000; specificity: 0.812); in the validation set, the AUC was 0.918 (accuracy: 0.875; sensitivity: 0.875; specificity: 0.857). In the testing set, the diagnostic performance was slightly lower with AUC of 0.875 (accuracy: 0.788; sensitivity: 0.909; specificity: 0.727). A nomogram based on clinical factors and radiomics score was generated via the proposed logistic regression model. Good calibration and clinical utility were observed using the calibration and decision curve analyses, respectively. Conclusion: Radiomics analysis of iodine-based MD images with DECT imaging holds great potential to predict MSI status in CRC patients.
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Affiliation(s)
- Jingjun Wu
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Qinhe Zhang
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Ying Zhao
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Yijun Liu
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Anliang Chen
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Xin Li
- Translational Medicine Team, GE Healthcare (China), Shanghai, China
| | - Tingfan Wu
- Translational Medicine Team, GE Healthcare (China), Shanghai, China
| | | | - Yan Guo
- GE Healthcare (China), Shanghai, China
| | - Ailian Liu
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
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