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Kamel P, Khalid M, Steger R, Kanhere A, Kulkarni P, Parekh V, Yi PH, Gandhi D, Bodanapally U. Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024:10.1007/s10278-024-01294-5. [PMID: 39384719 DOI: 10.1007/s10278-024-01294-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Revised: 09/13/2024] [Accepted: 10/03/2024] [Indexed: 10/11/2024]
Abstract
Ischemic changes are not visible on non-contrast head CT until several hours after infarction, though deep convolutional neural networks have shown promise in the detection of subtle imaging findings. This study aims to assess if dual-energy CT (DECT) acquisition can improve early infarct visibility for machine learning. The retrospective dataset consisted of 330 DECTs acquired up to 48 h prior to confirmation of a DWI positive infarct on MRI between 2016 and 2022. Infarct segmentation maps were generated from the MRI and co-registered to the CT to serve as ground truth for segmentation. A self-configuring 3D nnU-Net was trained for segmentation on (1) standard 120 kV mixed-images (2) 190 keV virtual monochromatic images and (3) 120 kV + 190 keV images as dual channel inputs. Algorithm performance was assessed with Dice scores with paired t-tests on a test set. Global aggregate Dice scores were 0.616, 0.645, and 0.665 for standard 120 kV images, 190 keV, and combined channel inputs respectively. Differences in overall Dice scores were statistically significant with highest performance for combined channel inputs (p < 0.01). Small but statistically significant differences were observed for infarcts between 6 and 12 h from last-known-well with higher performance for larger infarcts. Volumetric accuracy trended higher with combined inputs but differences were not statistically significant (p = 0.07). Supplementation of standard head CT images with dual-energy data provides earlier and more accurate segmentation of infarcts for machine learning particularly between 6 and 12 h after last-known-well.
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Affiliation(s)
- Peter Kamel
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA.
- University of Maryland Medical Intelligent Imaging (UM2ii) Center, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA.
| | - Mazhar Khalid
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Rachel Steger
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - Adway Kanhere
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA
- University of Maryland Medical Intelligent Imaging (UM2ii) Center, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA
| | - Pranav Kulkarni
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA
- University of Maryland Medical Intelligent Imaging (UM2ii) Center, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA
| | - Vishwa Parekh
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA
- University of Maryland Medical Intelligent Imaging (UM2ii) Center, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA
| | - Paul H Yi
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA
- University of Maryland Medical Intelligent Imaging (UM2ii) Center, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA
| | - Dheeraj Gandhi
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA
| | - Uttam Bodanapally
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD, 21201, USA
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Asmundo L, Zanardo M, Cressoni M, Ambrogi F, Bet L, Giatsidis F, Di Leo G, Sardanelli F, Vitali P. Ischemic core detection threshold of computed tomography perfusion (CTP) in acute stroke. LA RADIOLOGIA MEDICA 2024; 129:1522-1529. [PMID: 39162940 DOI: 10.1007/s11547-024-01868-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 08/01/2024] [Indexed: 08/21/2024]
Abstract
PURPOSE This study aimed to determine the accuracy of detecting ischemic core volume using computed tomography perfusion (CTP) in patients with suspected acute ischemic stroke compared to diffusion-weighted magnetic resonance imaging (DW-MRI) as the reference standard. METHODS This retrospective monocentric study included patients who underwent CTP and DW-MRI for suspected acute ischemic stroke. The ischemic core size was measured at DW-MRI. The detectability threshold volume was defined as the lowest volume detected by each method. Clinical data on revascularization therapy, along with the clinical decision that influenced the choice, were collected. Volumes of the ischemic cores were compared using the Mann-Whitney U test. RESULTS Of 83 patients who underwent CTP, 52 patients (median age 73 years, IQR 63-80, 36 men) also had DW-MRI and were included, with a total of 70 ischemic cores. Regarding ischemic cores, only 18/70 (26%) were detected by both CTP and DW-MRI, while 52/70 (74%) were detected only by DW-MRI. The median volume of the 52 ischemic cores undetected on CTP (0.6 mL, IQR 0.2-1.3 mL) was significantly lower (p < 0.001) than that of the 18 ischemic cores detected on CTP (14.2 mL, IQR 7.0-18.4 mL). The smallest ischemic core detected on CTP had a volume of 5.0 mL. Among the 20 patients with undetected ischemic core on CTP, only 10% (2/20) received thrombolysis treatment. CONCLUSIONS CTP maps failed in detecting ischemic cores smaller than 5 mL. DW-MRI remains essential for suspected small ischemic brain lesions to guide a correct treatment decision-making.
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Affiliation(s)
- Luigi Asmundo
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy
| | - Moreno Zanardo
- Radiology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy.
| | - Massimo Cressoni
- Radiology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Federico Ambrogi
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Via Della Commenda 19, 20122, Milan, Italy
- Scientific Directorate, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Luciano Bet
- Neurology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy
| | - Fabio Giatsidis
- Neurology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Giovanni Di Leo
- Radiology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Francesco Sardanelli
- Radiology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy
| | - Paolo Vitali
- Radiology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy
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Jiang J, Sheng K, Li M, Zhao H, Guan B, Dai L, Li Y. A dual-energy computed tomography-based radiomics nomogram for predicting time since stroke onset: a multicenter study. Eur Radiol 2024:10.1007/s00330-024-10802-8. [PMID: 38834786 DOI: 10.1007/s00330-024-10802-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 03/25/2024] [Accepted: 04/06/2024] [Indexed: 06/06/2024]
Abstract
OBJECTIVES We aimed to develop and validate a radiomics nomogram based on dual-energy computed tomography (DECT) images and clinical features to classify the time since stroke (TSS), which could facilitate stroke decision-making. MATERIALS AND METHODS This retrospective three-center study consecutively included 488 stroke patients who underwent DECT between August 2016 and August 2022. The eligible patients were divided into training, test, and validation cohorts according to the center. The patients were classified into two groups based on an estimated TSS threshold of ≤ 4.5 h. Virtual images optimized the visibility of early ischemic lesions with more CT attenuation. A total of 535 radiomics features were extracted from polyenergetic, iodine concentration, virtual monoenergetic, and non-contrast images reconstructed using DECT. Demographic factors were assessed to build a clinical model. A radiomics nomogram was a tool that the Rad score and clinical factors to classify the TSS using multivariate logistic regression analysis. Predictive performance was evaluated using receiver operating characteristic (ROC) analysis, and decision curve analysis (DCA) was used to compare the clinical utility and benefits of different models. RESULTS Twelve features were used to build the radiomics model. The nomogram incorporating both clinical and radiomics features showed favorable predictive value for TSS. In the validation cohort, the nomogram showed a higher AUC than the radiomics-only and clinical-only models (AUC: 0.936 vs 0.905 vs 0.824). DCA demonstrated the clinical utility of the radiomics nomogram model. CONCLUSIONS The DECT-based radiomics nomogram provides a promising approach to predicting the TSS of patients. CLINICAL RELEVANCE STATEMENT The findings support the potential clinical use of DECT-based radiomics nomograms for predicting the TSS. KEY POINTS Accurately determining the TSS onset is crucial in deciding a treatment approach. The radiomics-clinical nomogram showed the best performance for predicting the TSS. Using the developed model to identify patients at different times since stroke can facilitate individualized management.
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Affiliation(s)
- Jingxuan Jiang
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Kai Sheng
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Minda Li
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, China
| | - Huilin Zhao
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Baohui Guan
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lisong Dai
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuehua Li
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Steffen P, Winkelmeier L, Kniep H, Geest V, Soltanipanah S, Fiehler J, Broocks G. Quantification of ischemic brain edema after mechanical thrombectomy using dual-energy computed tomography in patients with ischemic stroke. Sci Rep 2024; 14:4148. [PMID: 38378795 PMCID: PMC10879140 DOI: 10.1038/s41598-024-54600-0] [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: 09/27/2023] [Accepted: 02/14/2024] [Indexed: 02/22/2024] Open
Abstract
Net water uptake (NWU) is a quantitative imaging biomarker used to assess cerebral edema resulting from ischemia via Computed Tomography (CT)-densitometry. It serves as a strong predictor of clinical outcome. Nevertheless, NWU measurements on follow-up CT scans after mechanical thrombectomy (MT) can be affected by contrast staining. To improve the accuracy of edema estimation, virtual non-contrast images (VNC-I) from dual-energy CT scans (DECT) were compared to conventional polychromatic CT images (CP-I) in this study. We examined NWU measurements derived from VNC-I and CP-I to assess their agreement and predictive value in clinical outcome. 88 consecutive patients who received DECT as follow-up after MT were included. NWU was quantified on CP-I (cNWU) and VNC-I (vNWU). The clinical endpoint was functional independence at discharge. cNWU and vNWU were highly correlated (r = 0.71, p < 0.0001). The median difference between cNWU and vNWU was 8.7% (IQR: 4.5-14.1%), associated with successful vessel recanalization (mTICI2b-3) (ß: 11.6%, 95% CI 2.9-23.0%, p = 0.04), and age (ß: 4.2%, 95% CI 1.3-7.0%, p = 0.005). The diagnostic accuracy to classify outcome between cNWU and vNWU was similar (AUC:0.78 versus 0.77). Although there was an 8.7% median difference, indicating potential edema underestimation on CP-I, it did not have short-term clinical implications.
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Affiliation(s)
- Paul Steffen
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany.
| | - Laurens Winkelmeier
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany
| | - Helge Kniep
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany
| | - Vincent Geest
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany
| | - Setareh Soltanipanah
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany
| | - Gabriel Broocks
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany
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Jingxuan J, Baohui G, Jingyi Z, Hongmei G, Minda L, Ye H, Yuehua L. Dual-energy computed tomography angiography-based quantification of lesion net water uptake to identify stroke onset time. Heliyon 2024; 10:e23540. [PMID: 38169834 PMCID: PMC10758880 DOI: 10.1016/j.heliyon.2023.e23540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 12/03/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024] Open
Abstract
Objectives To explore whether dual-energy computed tomography (DECT) angiography can provide reliable quantitative information on net water uptake (NWU) of ischemic brain to identify stroke patients within 4.5 h. Methods We retrospectively reviewed 142 patients with stroke occurrence and who underwent DECT angiography between August 2016 and May 2022. DECT angiography manual drawn the ischemic area by referring to the normal area of the contralateral hemisphere and follow-up images. The NWU in the ischemic area was determined using virtual non-contrast and monoenergetic (VNC &VM) images acquired from DECT angiography. The NWU values in the ischemic area were compared between stroke patients within and beyond 4.5 h. The diagnostic performance of the NWU values derived from the VNC and VM images was assessed through receiver operating characteristic curve analysis. Additionally, Furthermore, we examined the correlation between the NWU values and the stroke onset time. Results Seventy-eight (54.93 %) stroke patients underwent DECT angiography and within 4.5 h. These patients with lower median National Institute of Health stroke scale (NIHSS) scores on admission than those beyond 4.5 h (p < 0.05). Furthermore, the group within 4.5 h had lower NWU values than did the group beyond 4.5 h on all VNC and VM images (p < 0.001). The analysis revealed that the NWU values determined using the VM (60 keV) images had the highest predictive efficiency (AUC, 0.95; sensitivity, 100 %; and specificity, 89.06 %) and showed the strongest positive correlation with stroke onset time (r-value = 0.58, p < 0.001). Conclusions Our findings showed that DECT angiography-based quantification of NWU helps identify the stroke patients within 4.5 h with high predictive efficiency. Thus, NWU values determined using VM (60 keV) images could serve as a significant biomarker for stroke onset time.
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Affiliation(s)
- Jiang Jingxuan
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guan Baohui
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhou Jingyi
- Department of Radiology, Kunshan second People's Hospital, Kunshan, China
| | - Gu Hongmei
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, China
| | - Li Minda
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, China
| | - Hua Ye
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, China
| | - Li Yuehua
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Demehri S, Baffour FI, Klein JG, Ghotbi E, Ibad HA, Moradi K, Taguchi K, Fritz J, Carrino JA, Guermazi A, Fishman EK, Zbijewski WB. Musculoskeletal CT Imaging: State-of-the-Art Advancements and Future Directions. Radiology 2023; 308:e230344. [PMID: 37606571 PMCID: PMC10477515 DOI: 10.1148/radiol.230344] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/28/2023] [Accepted: 05/15/2023] [Indexed: 08/23/2023]
Abstract
CT is one of the most widely used modalities for musculoskeletal imaging. Recent advancements in the field include the introduction of four-dimensional CT, which captures a CT image during motion; cone-beam CT, which uses flat-panel detectors to capture the lower extremities in weight-bearing mode; and dual-energy CT, which operates at two different x-ray potentials to improve the contrast resolution to facilitate the assessment of tissue material compositions such as tophaceous gout deposits and bone marrow edema. Most recently, photon-counting CT (PCCT) has been introduced. PCCT is a technique that uses photon-counting detectors to produce an image with higher spatial and contrast resolution than conventional multidetector CT systems. In addition, postprocessing techniques such as three-dimensional printing and cinematic rendering have used CT data to improve the generation of both physical and digital anatomic models. Last, advancements in the application of artificial intelligence to CT imaging have enabled the automatic evaluation of musculoskeletal pathologies. In this review, the authors discuss the current state of the above CT technologies, their respective advantages and disadvantages, and their projected future directions for various musculoskeletal applications.
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Affiliation(s)
- Shadpour Demehri
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - Francis I. Baffour
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - Joshua G. Klein
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - Elena Ghotbi
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - Hamza Ahmed Ibad
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - Kamyar Moradi
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - Katsuyuki Taguchi
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - Jan Fritz
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - John A. Carrino
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - Ali Guermazi
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - Elliot K. Fishman
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
| | - Wojciech B. Zbijewski
- From the Russell H. Morgan Department of Radiology and Radiological
Science (S.D., J.G.K., E.G., H.A.I., K.M., K.T., E.K.F.) and Department of
Biomedical Engineering (W.B.Z.), Johns Hopkins University School of Medicine,
601 N Carolina St, Baltimore, MD 21287; Division of Musculoskeletal Imaging,
Department of Radiology, Mayo Clinic, Rochester, Minn (F.I.B.); Department of
Radiology, New York University Grossman School of Medicine, New York, NY (J.F.);
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY
(J.A.C.); and Department of Radiology, Quantitative Imaging Center, Boston
University School of Medicine, Boston, Mass (A.G.)
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7
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Duprez T, Vlassenbroek A, Peeters A, Poncelet PA, Levecque E, Austein F, Pahn G, Nae Y, Abdallah S, Coche E. Preliminary experience of CT imaging of the ischaemic brain penumbra through spectral processing of multiphasic CTA datasets. Sci Rep 2023; 13:11431. [PMID: 37454162 PMCID: PMC10349801 DOI: 10.1038/s41598-023-38370-9] [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: 01/03/2023] [Accepted: 07/07/2023] [Indexed: 07/18/2023] Open
Abstract
To assess ischaemic penumbra through the post-processing of the spectral multiphasic CT Angiography (mCTA) data in acute ischaemic stroke (AIS) patients. Thirty one consecutive patients strongly suspected of severe Middle Cerebral Artery AIS presenting less than 6 h after onset of symptoms or with unknown time of onset of symptoms underwent a standardized CT protocol in spectral mode including Non Contrast CT, mCTA, and Perfusion CT (CTP) on a dual-layer MDCT system. Areas disclosing delayed enhancement on iodine density (ID) maps were highlighted by subtraction of the serial mCTA datasets. Two neuroradiologists independently rated the correspondence between delayed enhancing areas at mCTA and the penumbral/infarcted areas delineated by two validated CTP applications using a 5-levels scoring scale. Interobserver agreement between observers was evaluated by kappa statistics. Dose delivery was recorded for each acquisition. Averaged correspondence score between penumbra delineation using subtracted mCTA-derived ID maps and CTP ones was 2.76 for one application and 2.9 for the other with best interobserver agreement kappa value at 0.59. All 6 stroke mimics out of the 31 patients' cohort were correctly identified. Average dose delivery was 7.55 mSv for the whole procedure of which CTP accounted for 39.7%. Post-processing of spectral mCTA data could allow clinically relevant assessment of the presence or absence of ischaemic penumbra in AIS-suspected patients if results of this proof-of-concept study should be confirmed in larger patients'series.
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Affiliation(s)
- T Duprez
- Department of Radiology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain (UCLouvain), Avenue Hippocrate 10, 1200, Brussels, Belgium
| | - A Vlassenbroek
- CT/AMI Clinical Science, Philips Health Systems, Avenue du Bourgmestre Etienne Demunter 1, 1090, Brussels, Belgium.
| | - A Peeters
- Department of Neurology, Stroke Unit, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain (UCLouvain), Avenue Hippocrate 10, 1200, Brussels, Belgium
| | - P A Poncelet
- Department of Medical Imaging, Grand Hôpital de Charleroi (GHdC), Grand'Rue, 3, 6000, Charleroi, Belgium
| | - E Levecque
- Department of Neurology, Stroke Unit, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain (UCLouvain), Avenue Hippocrate 10, 1200, Brussels, Belgium
| | - F Austein
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20426, Hamburg, Germany
| | - G Pahn
- PD CT/AMI Clinical Science, Philips GmbH Market DACH, Röntgenstraße 22-24, 22335, Hamburg, Germany
| | - Y Nae
- CT/AMI Clinical Science, Advanced Technologies Center, Philips Medical Systems Technologies Ltd., Building No. 34, P.O. Box 325, 3100202, Haifa, Israel
| | - S Abdallah
- CT/AMI Clinical Science, Advanced Technologies Center, Philips Medical Systems Technologies Ltd., Building No. 34, P.O. Box 325, 3100202, Haifa, Israel
| | - E Coche
- Department of Radiology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain (UCLouvain), Avenue Hippocrate 10, 1200, Brussels, Belgium
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8
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Multi-Energy CT Applications. Radiol Clin North Am 2023; 61:1-21. [DOI: 10.1016/j.rcl.2022.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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9
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Tran NA, Sodickson AD, Gupta R, Potter CA. Clinical applications of dual-energy computed tomography in neuroradiology. Semin Ultrasound CT MR 2022; 43:280-292. [PMID: 35738814 DOI: 10.1053/j.sult.2022.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Dual-energy computed tomography (DECT) has developed into a robust set of techniques with increasingly validated clinical applications in neuroradiology. We review some of the most common applications in neuroimaging along with demonstrative case examples that showcase the use of this technology in intracranial hemorrhage, stroke imaging, trauma imaging, artifact reduction, and tumor characterization.
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Affiliation(s)
- Ngoc-Anh Tran
- Department of Radiology, Brigham and Women's Hospital, Boston, MA.
| | - Aaron D Sodickson
- Division of Emergency Medicine, Department of Radiology, Brigham and Women's Hospital, Boston, MA
| | - Rajiv Gupta
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital, Boston, MA
| | - Christopher A Potter
- Division of Emergency Medicine, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Division of Neuroradiology, Department of Radiology, Brigham and Women's Hospital, Boston, MA
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10
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Gaddam DS, Dattwyler M, Fleiter TR, Bodanapally UK. Principles and Applications of Dual Energy Computed Tomography in Neuroradiology. Semin Ultrasound CT MR 2021; 42:418-433. [PMID: 34537112 DOI: 10.1053/j.sult.2021.07.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Dual-energy computed tomography (DE CT) is a promising tool with many current and evolving applications. Available DE CT scanners usually consist of one or two tubes, or use layered detectors for spectral separation. Most DE CT scanners can be used in single energy or dual-energy mode, except for the layered detector scanners that always acquire data in dual-energy mode. However, the layered detector scanners can retrospectively integrate the data from two layers to obtain conventional single energy images. DE CT mode enables generation of virtual monochromatic images, blended images, iodine quantification, improving conspicuity of iodinated contrast enhancement, and material decomposition maps or more sophisticated quantitative analysis not possible with conventional SE CT acquisition with an acceptable or even lower dose than the SE CT. This article reviews the basic principles of dual-energy CT and highlights many of its clinical applications in the evaluation of neurological conditions.
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Affiliation(s)
- Durga Sivacharan Gaddam
- Department of Diagnostic Radiology and Nuclear Medicine, R Adams Cowley Shock Trauma Center, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD
| | - Matthew Dattwyler
- Department of Diagnostic Radiology and Nuclear Medicine, R Adams Cowley Shock Trauma Center, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD
| | - Thorsten R Fleiter
- Department of Diagnostic Radiology and Nuclear Medicine, R Adams Cowley Shock Trauma Center, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD
| | - Uttam K Bodanapally
- Department of Diagnostic Radiology and Nuclear Medicine, R Adams Cowley Shock Trauma Center, University of Maryland School of Medicine, 22 S. Greene Street, Baltimore, MD.
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11
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Steffen P, Austein F, Lindner T, Meyer L, Bechstein M, Rümenapp J, Klintz T, Jansen O, Gellißen S, Hanning U, Fiehler J, Broocks G. Value of Dual-Energy Dual-Layer CT After Mechanical Recanalization for the Quantification of Ischemic Brain Edema. Front Neurol 2021; 12:668030. [PMID: 34349718 PMCID: PMC8326321 DOI: 10.3389/fneur.2021.668030] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 06/10/2021] [Indexed: 11/13/2022] Open
Abstract
Background and Purpose: Ischemic brain edema can be measured in computed tomography (CT) using quantitative net water uptake (NWU), a recently established imaging biomarker. NWU determined in follow-up CT after mechanical thrombectomy (MT) has shown to be a strong predictor of functional outcome. However, disruption of the blood-brain barrier after MT may also lead to contrast staining, increasing the density on CT scans, and hence, directly impairing measurements of NWU. The purpose of this study was to determine whether dual-energy dual-layer CT (DDCT) after MT can improve the quantification of NWU by measuring NWU in conventional polychromatic CT images (CP-I) and virtual non-contrast images (VNC-I). We hypothesized that VNC-based NWU (vNWU) differs from NWU in conventional CT (cNWU). Methods: Ten patients with middle cerebral artery occlusion who received a DDCT follow-up scan after MT were included. NWU was quantified in conventional and VNC images as previously published and was compared using paired sample t-tests. Results: The mean cNWU was 3.3% (95%CI: 0-0.41%), and vNWU was 11% (95%CI: 1.3-23.4), which was not statistically different (p = 0.09). Two patients showed significant differences between cNWU and vNWU (Δ = 24% and Δ = 36%), while the agreement of cNWU/vNWU in 8/10 patients was high (difference 2.3%, p = 0.23). Conclusion: NWU may be quantified precisely on conventional CT images, as the underestimation of ischemic edema due to contrast staining was low. However, a proportion of patients after MT might show significant contrast leakage resulting in edema underestimation. Further research is needed to validate these findings and investigate clinical implications.
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Affiliation(s)
- Paul Steffen
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Friederike Austein
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Thomas Lindner
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Lukas Meyer
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthias Bechstein
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Johanna Rümenapp
- Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Tristan Klintz
- Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Olav Jansen
- Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Susanne Gellißen
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Uta Hanning
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gabriel Broocks
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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12
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Wolman DN, Pulli B, Heit JJ. The Promise of Dual-Energy CT in Stroke and Neurovascular Imaging. World Neurosurg 2021; 146:379-380. [PMID: 33607724 DOI: 10.1016/j.wneu.2020.12.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Dylan N Wolman
- Department of Neuroimaging and Neurointervention, Stanford University Hospital, Palo Alto, California, USA
| | - Benjamin Pulli
- Department of Neuroimaging and Neurointervention, Stanford University Hospital, Palo Alto, California, USA
| | - Jeremy J Heit
- Department of Neuroimaging and Neurointervention, Stanford University Hospital, Palo Alto, California, USA
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13
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Wolman DN, van Ommen F, Tong E, Kauw F, Dankbaar JW, Bennink E, de Jong HWAM, Molvin L, Wintermark M, Heit JJ. Non-contrast dual-energy CT virtual ischemia maps accurately estimate ischemic core size in large-vessel occlusive stroke. Sci Rep 2021; 11:6745. [PMID: 33762589 PMCID: PMC7991428 DOI: 10.1038/s41598-021-85143-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Accepted: 02/22/2021] [Indexed: 02/06/2023] Open
Abstract
Dual-energy CT (DECT) material decomposition techniques may better detect edema within cerebral infarcts than conventional non-contrast CT (NCCT). This study compared if Virtual Ischemia Maps (VIM) derived from non-contrast DECT of patients with acute ischemic stroke due to large-vessel occlusion (AIS-LVO) are superior to NCCT for ischemic core estimation, compared against reference-standard DWI-MRI. Only patients whose baseline ischemic core was most likely to remain stable on follow-up MRI were included, defined as those with excellent post-thrombectomy revascularization or no perfusion mismatch. Twenty-four consecutive AIS-LVO patients with baseline non-contrast DECT, CT perfusion (CTP), and DWI-MRI were analyzed. The primary outcome measure was agreement between volumetric manually segmented VIM, NCCT, and automatically segmented CTP estimates of the ischemic core relative to manually segmented DWI volumes. Volume agreement was assessed using Bland–Altman plots and comparison of CT to DWI volume ratios. DWI volumes were better approximated by VIM than NCCT (VIM/DWI ratio 0.68 ± 0.35 vs. NCCT/DWI ratio 0.34 ± 0.35; P < 0.001) or CTP (CTP/DWI ratio 0.45 ± 0.67; P < 0.001), and VIM best correlated with DWI (rVIM = 0.90; rNCCT = 0.75; rCTP = 0.77; P < 0.001). Bland–Altman analyses indicated significantly greater agreement between DWI and VIM than NCCT core volumes (mean bias 0.60 [95%AI 0.39–0.82] vs. 0.20 [95%AI 0.11–0.30]). We conclude that DECT VIM estimates the ischemic core in AIS-LVO patients more accurately than NCCT.
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Affiliation(s)
- Dylan N Wolman
- Department of Neuroimaging and Neurointervention, Stanford University Hospital, 300 Pasteur Drive, Room S-047, Stanford, CA, 94305, USA.
| | - Fasco van Ommen
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Elizabeth Tong
- Department of Neuroimaging and Neurointervention, Stanford University Hospital, 300 Pasteur Drive, Room S-047, Stanford, CA, 94305, USA
| | - Frans Kauw
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jan Willem Dankbaar
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Edwin Bennink
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hugo W A M de Jong
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lior Molvin
- Department of Radiology, Stanford University Hospital, 300 Pasteur Drive, Room S-047, Stanford, CA, 94505, USA
| | - Max Wintermark
- Department of Neuroimaging and Neurointervention, Stanford University Hospital, 300 Pasteur Drive, Room S-047, Stanford, CA, 94305, USA
| | - Jeremy J Heit
- Department of Neuroimaging and Neurointervention, Stanford University Hospital, 300 Pasteur Drive, Room S-047, Stanford, CA, 94305, USA.
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14
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Mangesius S, Grams AE. Dual energy computed tomomgraphy in acute stroke, where are we and where are we going? J Neuroradiol 2021; 48:71-74. [PMID: 33607169 DOI: 10.1016/j.neurad.2021.02.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 02/11/2021] [Accepted: 02/13/2021] [Indexed: 12/11/2022]
Affiliation(s)
- S Mangesius
- Department of Neuroradiology, Medical University of Innsbruck, 6020 Innsbruck, Austria.
| | - A E Grams
- Department of Neuroradiology, Medical University of Innsbruck, 6020 Innsbruck, Austria.
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15
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Ståhl F, Gontu V, Almqvist H, Mazya MV, Falk Delgado A. Performance of dual layer dual energy CT virtual monoenergetic images to identify early ischemic changes in patients with anterior circulation large vessel occlusion. J Neuroradiol 2020; 48:75-81. [PMID: 33340643 DOI: 10.1016/j.neurad.2020.12.002] [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: 10/08/2020] [Revised: 12/07/2020] [Accepted: 12/07/2020] [Indexed: 10/22/2022]
Abstract
BACKGROUND AND PURPOSE Dual energy CT is increasingly available and used in the standard diagnostic setting of ischemic stroke patients. We aimed to evaluate how different dual energy CT virtual monoenergetic energy levels impact identification of early ischemic changes, compared to conventional polyenergetic CT images. MATERIALS AND METHODS This retrospective single-center study included patients presenting with acute ischemic stroke caused by an occlusion of the intracranial internal carotid artery or proximal middle cerebral artery. Data was gathered on consecutive patients admitted to our institution who underwent initial diagnostic stroke imaging with dual layer dual energy CT and a subsequent follow-up CT one to three days after admission. Automated ASPECTS results from conventional polyenergetic and different virtual monoenergetic energy level reconstructions at admission were generated and compared to reference standard ASPECTS. Confidence intervals (CI) for sensitivity, specificity, negative and positive predictive value were calculated. RESULTS A total of 24 patients were included. Virtual monoenergetic reconstructions of 70 keV had the highest region-based ASPECTS accuracy, 0.90 (sensitivity 0.82 (95% CI 0.72-0.93), specificity 0.92 (0.88-0.97), negative predictive value 0.94 (0.90-0.96)), whereas virtual monoenergetic reconstructions of 40 keV had the lowest, 0.77 (sensitivity 0.34 (0.26-0.42), specificity 0.90 (0.89-0.96), negative predictive value 0.80 (0.77-0.83)). CONCLUSIONS Automated 70 keV ASPECTS had the highest diagnostic accuracy, sensitivity and negative predictive value overall. Our results indicate that virtual monoenergetic energy levels impact the identification of early ischemic changes on CT.
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Affiliation(s)
- Fredrik Ståhl
- Department of Neuroradiology, Karolinska University Hospital, Eugeniavaegen 3, 17176 Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Vamsi Gontu
- Department of Neuroradiology, Karolinska University Hospital, Eugeniavaegen 3, 17176 Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Håkan Almqvist
- Department of Neuroradiology, Karolinska University Hospital, Eugeniavaegen 3, 17176 Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Michael V Mazya
- Department of Neurology, Karolinska University Hospital, Eugeniavaegen 3, 17176 Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Anna Falk Delgado
- Department of Neuroradiology, Karolinska University Hospital, Eugeniavaegen 3, 17176 Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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16
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Dual-energy computed tomography in acute ischemic stroke: state-of-the-art. Eur Radiol 2020; 31:4138-4147. [PMID: 33319330 PMCID: PMC8128835 DOI: 10.1007/s00330-020-07543-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 10/31/2020] [Accepted: 11/18/2020] [Indexed: 12/15/2022]
Abstract
Abstract Dual-energy computed tomography (DECT) allows distinguishing between tissues with similar X-ray attenuation but different atomic numbers. Recent studies demonstrated that this technique has several areas of application in patients with ischemic stroke and a potential impact on patient management. After endovascular stroke therapy (EST), hyperdense areas can represent either hemorrhage or contrast staining due to blood-brain barrier disruption, which can be differentiated reliably by DECT. Further applications are improved visualization of early infarctions, compared to single-energy computed tomography, and prediction of transformation into infarction or hemorrhage in contrast-enhancing areas. In addition, DECT allows detection and evaluation of the material composition of intra-arterial clots after EST. This review summarizes the clinical state-of-the-art of DECT in patients with stroke, and features some prospects for future developments. Key points • Dual-energy computed tomography (DECT) allows differentiation between tissues with similar X-ray attenuation but differentatomic numbers. • DECT has several areas of application in patients with ischemic stroke and a potential impact on patient management. • Prospects for future developments in DECT may improve treatment decision-making.
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17
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van Ommen F, Dankbaar JW, Zhu G, Wolman DN, Heit JJ, Kauw F, Bennink E, de Jong HWAM, Wintermark M. Virtual monochromatic dual-energy CT reconstructions improve detection of cerebral infarct in patients with suspicion of stroke. Neuroradiology 2020; 63:41-49. [PMID: 32728777 PMCID: PMC7803871 DOI: 10.1007/s00234-020-02492-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 07/05/2020] [Indexed: 12/12/2022]
Abstract
Purpose Early infarcts are hard to diagnose on non-contrast head CT. Dual-energy CT (DECT) may potentially increase infarct differentiation. The optimal DECT settings for differentiation were identified and evaluated. Methods One hundred and twenty-five consecutive patients who presented with suspected acute ischemic stroke (AIS) and underwent non-contrast DECT and subsequent DWI were retrospectively identified. The DWI was used as reference standard. First, virtual monochromatic images (VMI) of 25 patients were reconstructed from 40 to 140 keV and scored by two readers for acute infarct. Sensitivity, specificity, positive, and negative predictive values for infarct detection were compared and a subset of VMI energies were selected. Next, for a separate larger cohort of 100 suspected AIS patients, conventional non-contrast CT (NCT) and selected VMI were scored by two readers for the presence and location of infarct. The same statistics for infarct detection were calculated. Infarct location match was compared per vascular territory. Subgroup analyses were dichotomized by time from last-seen-well to CT imaging. Results A total of 80–90 keV VMI were marginally more sensitive (36.3–37.3%) than NCT (32.4%; p > 0.680), with marginally higher specificity (92.2–94.4 vs 91.1%; p > 0.509) for infarct detection. Location match was superior for VMI compared with NCT (28.7–27.4 vs 19.5%; p < 0.010). Within 4.5 h from last-seen-well, 80 keV VMI more accurately detected infarct (58.0 vs 54.0%) and localized infarcts (27.1 vs 11.9%; p = 0.004) than NCT, whereas after 4.5 h, 90 keV VMI was more accurate (69.3 vs 66.3%). Conclusion Non-contrast 80–90 keV VMI best differentiates normal from infarcted brain parenchyma. Electronic supplementary material The online version of this article (10.1007/s00234-020-02492-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Fasco van Ommen
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, E01.132, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
| | - Jan Willem Dankbaar
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, E01.132, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
| | - Guangming Zhu
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
| | - Dylan N. Wolman
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
| | - Jeremy J. Heit
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
| | - Frans Kauw
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, E01.132, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
| | - Edwin Bennink
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, E01.132, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Hugo W. A. M. de Jong
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, E01.132, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Max Wintermark
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
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18
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Gibney B, Redmond CE, Byrne D, Mathur S, Murray N. A Review of the Applications of Dual-Energy CT in Acute Neuroimaging. Can Assoc Radiol J 2020; 71:253-265. [PMID: 32106693 DOI: 10.1177/0846537120904347] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Dual-energy computed tomography (CT) is a promising tool with increasing availability and multiple emerging and established clinical applications in neuroradiology. With its ability to allow characterization of materials based on their differential attenuation when imaged at two different energy levels, dual-energy CT can help identify the composition of brain, neck, and spinal components. Virtual monoenergetic imaging allows a range of simulated single energy-level reconstructions to be created with postprocessing. Low-energy reconstructions can aid identification of edema, ischemia, and subtle lesions due to increased soft tissue contrast as well as increasing contrast-to-noise ratios on angiographic imaging. Higher energy reconstructions can reduce image artifact from dental amalgam, aneurysm clips and coils, spinal hardware, dense contrast, and dense bones. Differentiating iodine from hemorrhage may help guide management of patients after thrombectomy and aid diagnosis of enhancing tumors within parenchymal hemorrhages. Iodine quantification may predict hematoma expansion in aneurysmal bleeds and outcomes in traumatic brain injury. Calcium and bone subtraction can be used to distinguish hemorrhage from brain parenchymal mineralization as well as improving visualization of extra-axial lesions and vessels adjacent to dense plaque or skull. This article reviews the basics of dual-energy CT and highlights many of its clinical applications in the evaluation of acute neurological presentations.
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Affiliation(s)
- Brian Gibney
- Division of Emergency Radiology, Vancouver General Hospital, Vancouver, British Columbia, Canada
| | - Ciaran E Redmond
- Division of Emergency Radiology, Vancouver General Hospital, Vancouver, British Columbia, Canada
| | - Danielle Byrne
- Division of Neuroradiology, Vancouver General Hospital, Vancouver, British Columbia, Canada
| | - Shobhit Mathur
- Department of Medical Imaging, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Nicolas Murray
- Division of Emergency Radiology, Vancouver General Hospital, Vancouver, British Columbia, Canada
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20
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Ji X, Zhang R, Chen GH, Li K. Task-driven optimization of the non-spectral mode of photon counting CT for intracranial hemorrhage assessment. Phys Med Biol 2019; 64:215014. [PMID: 31509812 DOI: 10.1088/1361-6560/ab43a6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Non-contrast CT (NCCT) is widely employed as the first-line imaging test to evaluate intracranial hemorrhage (ICH). Advances in mutidetector CT (MDCT) technology have greatly improved the image quality of NCCT for the detection of established, relatively large, and acute ICHs. Meanwhile, the reliability of MDCT in detecting microbleeds and chronic hemorrhage, and in predicting hemorrhagic transformation needs to be further improved. The purpose of this work was to investigate the potential use of non-spectral photon counting CT (PCCT) to address these challenges in ICH imaging. Towards this goal, the NCCT protocol of an experimental PCCT system that simulates the geometry of a general-purpose MDCT was optimized. The optimization was driven by three imaging tasks: detection of a 4.0 mm intraparenchymal hemorrhage, detection of a 1.5 mm subarachnoid hemorrhage, and discrimination of a sulcus in the insular cortex from the parenchymal background. These imaging tasks were custom-built into an anthropomorphic head phantom. Under the guidance of the frequency-dependent noise equivalent quanta and the ideal observer model detectability index [Formula: see text], the optimal PCD detection mode, energy threshold, and reconstruction kernel were found to be the anti-charge sharing mode, 15 keV, and an apodized ramp kernel, respectively. Compared with a clinical MDCT operated with an ICH protocol and at a matched dose level, the PCCT system provided at least 20% improvements in [Formula: see text] for all three ICH imaging tasks. These results demonstrated the potential benefits of non-spectral PCCT in ICH assessment.
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Affiliation(s)
- Xu Ji
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States of America
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