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Haseljić H, Chatterjee S, Frysch R, Kulvait V, Semshchikov V, Hensen B, Wacker F, Brüsch I, Werncke T, Speck O, Nürnberger A, Rose G. Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging. Comput Biol Med 2023; 154:106539. [PMID: 36689856 DOI: 10.1016/j.compbiomed.2023.106539] [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: 07/20/2022] [Revised: 11/30/2022] [Accepted: 01/10/2023] [Indexed: 01/15/2023]
Abstract
Model-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be segmented for proper visualisation and interpretation of perfusion maps. This research proposes Turbolift learning, which trains a modified version of the multi-scale Attention UNet on different liver segmentation tasks serially, following the order of the trainings CT, CBCT, CBCT TST - making the previous trainings act as pre-training stages for the subsequent ones - addressing the problem of limited number of datasets for training. For the final task of liver segmentation from CBCT TST, the proposed method achieved an overall Dice scores of 0.874±0.031 and 0.905±0.007 in 6-fold and 4-fold cross-validation experiments, respectively - securing statistically significant improvements over the model, which was trained only for that task. Experiments revealed that Turbolift not only improves the overall performance of the model but also makes it robust against artefacts originating from the embolisation materials and truncation artefacts. Additionally, in-depth analyses confirmed the order of the segmentation tasks. This paper shows the potential of segmenting the liver from CT, CBCT, and CBCT TST, learning from the available limited training data, which can possibly be used in the future for the visualisation and evaluation of the perfusion maps for the treatment evaluation of liver diseases.
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Affiliation(s)
- Hana Haseljić
- Institute for Medical Engineering, Otto von Guericke University Magdeburg, Germany; Research Campus STIMULATE, Otto von Guericke University Magdeburg, Germany
| | - Soumick Chatterjee
- Faculty of Computer Science, Otto von Guericke University Magdeburg, Germany; Data and Knowledge Engineering Group, Otto von Guericke University Magdeburg, Germany; Biomedical Magnetic Resonance, Otto von Guericke University Magdeburg, Germany; Research Campus STIMULATE, Otto von Guericke University Magdeburg, Germany; Genomics Research Centre, Human Technopole, Milan, Italy.
| | - Robert Frysch
- Institute for Medical Engineering, Otto von Guericke University Magdeburg, Germany; Research Campus STIMULATE, Otto von Guericke University Magdeburg, Germany
| | - Vojtěch Kulvait
- Institute of Materials Physics, Helmholtz-Zentrum hereon, Geesthacht, Germany
| | - Vladimir Semshchikov
- Institute for Medical Engineering, Otto von Guericke University Magdeburg, Germany
| | - Bennet Hensen
- Research Campus STIMULATE, Otto von Guericke University Magdeburg, Germany; Institute of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany
| | - Frank Wacker
- Research Campus STIMULATE, Otto von Guericke University Magdeburg, Germany; Institute of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany
| | - Inga Brüsch
- Research Campus STIMULATE, Otto von Guericke University Magdeburg, Germany; Institute for Laboratory Animal Science, Hannover Medical School, Hannover, Germany
| | - Thomas Werncke
- Research Campus STIMULATE, Otto von Guericke University Magdeburg, Germany; Institute of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany
| | - Oliver Speck
- Biomedical Magnetic Resonance, Otto von Guericke University Magdeburg, Germany; Research Campus STIMULATE, Otto von Guericke University Magdeburg, Germany; German Center for Neurodegenerative Disease, Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Andreas Nürnberger
- Faculty of Computer Science, Otto von Guericke University Magdeburg, Germany; Data and Knowledge Engineering Group, Otto von Guericke University Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Georg Rose
- Institute for Medical Engineering, Otto von Guericke University Magdeburg, Germany; Research Campus STIMULATE, Otto von Guericke University Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany
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Zeng D, Zeng C, Zeng Z, Li S, Deng Z, Chen S, Bian Z, Ma J. Basis and current state of computed tomography perfusion imaging: a review. Phys Med Biol 2022; 67. [PMID: 35926503 DOI: 10.1088/1361-6560/ac8717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 08/04/2022] [Indexed: 12/30/2022]
Abstract
Computed tomography perfusion (CTP) is a functional imaging that allows for providing capillary-level hemodynamics information of the desired tissue in clinics. In this paper, we aim to offer insight into CTP imaging which covers the basics and current state of CTP imaging, then summarize the technical applications in the CTP imaging as well as the future technological potential. At first, we focus on the fundamentals of CTP imaging including systematically summarized CTP image acquisition and hemodynamic parameter map estimation techniques. A short assessment is presented to outline the clinical applications with CTP imaging, and then a review of radiation dose effect of the CTP imaging on the different applications is presented. We present a categorized methodology review on known and potential solvable challenges of radiation dose reduction in CTP imaging. To evaluate the quality of CTP images, we list various standardized performance metrics. Moreover, we present a review on the determination of infarct and penumbra. Finally, we reveal the popularity and future trend of CTP imaging.
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Affiliation(s)
- Dong Zeng
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Cuidie Zeng
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Zhixiong Zeng
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Sui Li
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Zhen Deng
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Sijin Chen
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Zhaoying Bian
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Jianhua Ma
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
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Kulvait V, Hoelter P, Frysch R, Haseljić H, Doerfler A, Rose G. A novel use of time separation technique to improve flat detector CT perfusion imaging in stroke patients. Med Phys 2022; 49:3624-3637. [PMID: 35396720 DOI: 10.1002/mp.15640] [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: 08/11/2021] [Revised: 03/07/2022] [Accepted: 03/15/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND CT perfusion imaging (CTP) is used in the diagnostic workup of acute ischemic stroke (AIS). CTP may be performed within the angio suite using flat detector CT (FDCT) to help reduce patient management time. PURPOSE In order to significantly improve FDCT perfusion (FDCTP) imaging, data-processing algorithms need to be able to compensate for the higher levels of noise, slow rotation speed, and a lower frame rate of current FDCT devices. METHODS We performed a realistic simulation of FDCTP acquisition based on CTP data from seven subjects. We used the time separation technique (TST) as a model-based approach for FDCTP data processing. We propose a novel dimension reduction in which we approximate the time attenuation curves by a linear combination of trigonometric functions. Our goal was to show that the TST can be used even without prior assumptions on the shape of the attenuation profiles. RESULTS We first demonstrated that a trigonometric basis is suitable for dimension reduction of perfusion data. Using simulated FDCTP data, we have shown that a trigonometric basis in the TST provided better results than the classical straightforward processing even with additional noise. Average correlation coefficients of perfusion maps were improved for cerebral blood flow (CBF), cerebral blood volume, mean transit time (MTT) maps. In a moderate noise scenario, the average Pearson's coefficient for the CBF map was improved using the TST from 0.76 to 0.81. For the MTT map, it was improved from 0.37 to 0.45. Furthermore, we achieved a total processing time from the reconstruction of FDCTP data to the generation of perfusion maps of under 5 min. CONCLUSIONS In our study cohort, perfusion maps created from FDCTP data using the TST with a trigonometric basis showed equivalent perfusion deficits to classic CT perfusion maps. It follows, that this novel FDCTP technique has potential to provide fast and accurate FDCTP imaging for AIS patients.
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Affiliation(s)
- Vojtěch Kulvait
- Institute for Medical Engineering and Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany.,Institute of Materials Physics, Helmholtz-Zentrum Hereon, Geesthacht, Germany
| | - Philip Hoelter
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Erlangen, Germany
| | - Robert Frysch
- Institute for Medical Engineering and Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany
| | - Hana Haseljić
- Institute for Medical Engineering and Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany
| | - Arnd Doerfler
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Erlangen, Germany
| | - Georg Rose
- Institute for Medical Engineering and Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany
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He G, Wei L, Lu H, Li Y, Zhao Y, Zhu Y. Advances in imaging acute ischemic stroke: evaluation before thrombectomy. Rev Neurosci 2021; 32:495-512. [PMID: 33600678 DOI: 10.1515/revneuro-2020-0061] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 08/05/2020] [Indexed: 11/15/2022]
Abstract
Recent advances in neuroimaging have demonstrated significant assessment benefits and appropriate triage of patients based on specific clinical and radiological features in the acute stroke setting. Endovascular thrombectomy is arguably the most important aspect of acute stroke management with an extended time window. Imaging-based physiological information may potentially shift the treatment paradigm from a rigid time-based model to a more flexible and individualized, tissue-based approach, increasing the proportion of patients amenable to treatment. Various imaging modalities are routinely used in the diagnosis and management of acute ischemic stroke, including multimodal computed tomography (CT) and magnetic resonance imaging (MRI). Therefore, these imaging methods should provide information beyond the presence or absence of intracranial hemorrhage as well as the presence and extent of the ischemic core, collateral circulation and penumbra in patients with neurological symptoms. Target mismatch may optimize selection of patients with late or unknown symptom onset who would potentially be eligible for revascularization therapy. The purpose of this study was to provide a comprehensive review of the current evidence about efficacy and theoretical basis of present imaging modalities, and explores future directions for imaging in the management of acute ischemic stroke.
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Affiliation(s)
- Guangchen He
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, No. 600, Yishan Road, Shanghai200233, China
| | - Liming Wei
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, No. 600, Yishan Road, Shanghai200233, China
| | - Haitao Lu
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, No. 600, Yishan Road, Shanghai200233, China
| | - Yuehua Li
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, No. 600, Yishan Road, Shanghai200233, China
| | - Yuwu Zhao
- Department of Neurology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, No. 600, Yishan Road, Shanghai200233, China
| | - Yueqi Zhu
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, No. 600, Yishan Road, Shanghai200233, China
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