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Hang Y, Liu Y, Teng Z, Cao X, Zhu H. Mesoporous nanodrug delivery system: a powerful tool for a new paradigm of remodeling of the tumor microenvironment. J Nanobiotechnology 2023; 21:101. [PMID: 36945005 PMCID: PMC10029196 DOI: 10.1186/s12951-023-01841-2] [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: 01/06/2023] [Accepted: 03/06/2023] [Indexed: 03/23/2023] Open
Abstract
Tumor microenvironment (TME) plays an important role in tumor progression, metastasis and therapy resistance. Remodeling the TME has recently been deemed an attractive tumor therapeutic strategy. Due to its complexity and heterogeneity, remodeling the TME still faces great challenges. With the great advantage of drug loading ability, tumor accumulation, multifactor controllability, and persistent guest molecule release ability, mesoporous nanodrug delivery systems (MNDDSs) have been widely used as effective antitumor drug delivery tools as well as remolding TME. This review summarizes the components and characteristics of the TME, as well as the crosstalk between the TME and cancer cells and focuses on the important role of drug delivery strategies based on MNDDSs in targeted remodeling TME metabolic and synergistic anticancer therapy.
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Affiliation(s)
- Yinhui Hang
- Department of Medical Imaging, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, People's Republic of China
- Institute of Medical Imaging and Artificial Intelligence, Jiangsu University, Zhenjiang, 212001, People's Republic of China
| | - Yanfang Liu
- Laboratory of Medical Imaging, The First People's Hospital of Zhenjiang, Zhenjiang, 212001, People's Republic of China
| | - Zhaogang Teng
- Key Laboratory for Organic Electronics and Information Displays & Jiangsu Key Laboratory for Biosensors, Institute of Advanced Materials (IAM), Nanjing University of Posts and Telecommunications, Nanjing, 210023, People's Republic of China.
| | - Xiongfeng Cao
- Department of Medical Imaging, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, People's Republic of China.
- Institute of Medical Imaging and Artificial Intelligence, Jiangsu University, Zhenjiang, 212001, People's Republic of China.
| | - Haitao Zhu
- Department of Medical Imaging, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, People's Republic of China.
- Institute of Medical Imaging and Artificial Intelligence, Jiangsu University, Zhenjiang, 212001, People's Republic of China.
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Alvarez P, Rouzé S, Miga MI, Payan Y, Dillenseger JL, Chabanas M. A hybrid, image-based and biomechanics-based registration approach to markerless intraoperative nodule localization during video-assisted thoracoscopic surgery. Med Image Anal 2021; 69:101983. [PMID: 33588119 DOI: 10.1016/j.media.2021.101983] [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: 04/28/2020] [Revised: 01/16/2021] [Accepted: 01/26/2021] [Indexed: 12/09/2022]
Abstract
The resection of small, low-dense or deep lung nodules during video-assisted thoracoscopic surgery (VATS) is surgically challenging. Nodule localization methods in clinical practice typically rely on the preoperative placement of markers, which may lead to clinical complications. We propose a markerless lung nodule localization framework for VATS based on a hybrid method combining intraoperative cone-beam CT (CBCT) imaging, free-form deformation image registration, and a poroelastic lung model with allowance for air evacuation. The difficult problem of estimating intraoperative lung deformations is decomposed into two more tractable sub-problems: (i) estimating the deformation due the change of patient pose from preoperative CT (supine) to intraoperative CBCT (lateral decubitus); and (ii) estimating the pneumothorax deformation, i.e. a collapse of the lung within the thoracic cage. We were able to demonstrate the feasibility of our localization framework with a retrospective validation study on 5 VATS clinical cases. Average initial errors in the range of 22 to 38 mm were reduced to the range of 4 to 14 mm, corresponding to an error correction in the range of 63 to 85%. To our knowledge, this is the first markerless lung deformation compensation method dedicated to VATS and validated on actual clinical data.
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Affiliation(s)
- Pablo Alvarez
- Univ. Rennes 1, Inserm, LTSI - UMR 1099, Rennes F-35000, France; Univ. Grenoble Alpes, CNRS, Grenoble INP, TIMC-IMAG, Grenoble F-38000, France.
| | - Simon Rouzé
- Univ. Rennes 1, Inserm, LTSI - UMR 1099, Rennes F-35000, France; CHU Rennes, Department of Cardio-Thoracic and Vascular Surgery, Rennes F-35000, France.
| | - Michael I Miga
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville, TN, USA.
| | - Yohan Payan
- Univ. Grenoble Alpes, CNRS, Grenoble INP, TIMC-IMAG, Grenoble F-38000, France.
| | | | - Matthieu Chabanas
- Univ. Grenoble Alpes, CNRS, Grenoble INP, TIMC-IMAG, Grenoble F-38000, France; Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville, TN, USA.
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Narasimhan S, Weis JA, Luo M, Simpson AL, Thompson RC, Miga MI. Accounting for intraoperative brain shift ascribable to cavity collapse during intracranial tumor resection. J Med Imaging (Bellingham) 2020; 7:031506. [PMID: 32613027 DOI: 10.1117/1.jmi.7.3.031506] [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: 02/05/2020] [Accepted: 06/05/2020] [Indexed: 11/14/2022] Open
Abstract
Purpose: For many patients with intracranial tumors, accurate surgical resection is a mainstay of their treatment paradigm. During surgical resection, image guidance is used to aid in localization and resection. Intraoperative brain shift can invalidate these guidance systems. One cause of intraoperative brain shift is cavity collapse due to tumor resection, which will be referred to as "debulking." We developed an imaging-driven finite element model of debulking to create a comprehensive simulation data set to reflect possible intraoperative changes. The objective was to create a method to account for brain shift due to debulking for applications in image-guided neurosurgery. We hypothesized that accounting for tumor debulking in a deformation atlas data framework would improve brain shift predictions, which would enhance image-based surgical guidance. Approach: This was evaluated in a six-patient intracranial tumor resection intraoperative data set. The brain shift deformation atlas data framework consisted of n = 756 simulated deformations to account for effects due to gravity-induced and hyperosmotic drug-induced brain shift, which reflects previous developments. An additional complement of n = 84 deformations involving simulated tumor growth followed by debulking was created to capture observed intraoperative effects not previously included. Results: In five of six patient cases evaluated, inclusion of debulking mechanics improved brain shift correction by capturing global mass effects resulting from the resected tumor. Conclusions: These findings suggest imaging-driven brain shift models used to create a deformation simulation data framework of observed intraoperative events can be used to assist in more accurate image-guided surgical navigation in the brain.
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Affiliation(s)
- Saramati Narasimhan
- Vanderbilt University Medical Center, Department of Neurological Surgery, Nashville, Tennessee, United States
| | - Jared A Weis
- Wake Forest School of Medicine, Department of Biomedical Engineering, Winston-Salem, North Carolina, United States
| | - Ma Luo
- Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States
| | - Amber L Simpson
- Queen's University, Department of Biomedical and Molecular Sciences, Ontario, Canada
| | - Reid C Thompson
- Vanderbilt University Medical Center, Department of Neurological Surgery, Nashville, Tennessee, United States
| | - Michael I Miga
- Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States
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Narasimhan S, Johnson HB, Nickles TM, Miga MI, Rana N, Attia A, Weis JA. Biophysical model-based parameters to classify tumor recurrence from radiation-induced necrosis for brain metastases. Med Phys 2019; 46:2487-2496. [PMID: 30816555 DOI: 10.1002/mp.13461] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 01/30/2019] [Accepted: 02/20/2019] [Indexed: 12/16/2022] Open
Abstract
PURPOSE Stereotactic radiosurgery (SRS) is used for local control treatment of patients with intracranial metastases. As a result of SRS, some patients develop radiation-induced necrosis. Radiographically, radiation-induced necrosis can appear similar to tumor recurrence in magnetic resonance (MR) T1 -weighted contrast-enhanced imaging, T2 -weighted MR imaging, and Fluid-Attenuated Inversion Recovery (FLAIR) MR imaging. Radiographic ambiguities often necessitate invasive brain biopsies to determine lesion etiology or cause delayed subsequent therapy initiation. We use a biomechanically coupled tumor growth model to estimate patient-specific model parameters and model-derived measures to noninvasively classify etiology of enhancing lesions in this patient population. METHODS In this initial, preliminary retrospective study, we evaluated five patients with tumor recurrence and five with radiation-induced necrosis. Longitudinal patient-specific MR imaging data were used in conjunction with the model to parameterize tumor cell proliferation rate and tumor cell diffusion coefficient, and Dice correlation coefficients were used to quantify degree of correlation between model-estimated mechanical stress fields and edema visualized from MR imaging. RESULTS Results found four statistically relevant parameters which can differentiate tumor recurrence and radiation-induced necrosis. CONCLUSIONS This preliminary investigation suggests potential of this framework to noninvasively determine the etiology of enhancing lesions in patients who previously underwent SRS for intracranial metastases.
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Affiliation(s)
- Saramati Narasimhan
- Department of Biomedical Engineering, Vanderbilt University, 5824 Stevenson Center, Nashville, TN, 37235, USA
| | - Haley B Johnson
- Department of Biomedical Engineering, Wake Forest School of Medicine, Wake Forest Baptist Medical Center, Medical Center Boulevard, Winston-Salem, NC, 27157, USA
| | - Tanner M Nickles
- Department of Biomedical Engineering, Wake Forest School of Medicine, Wake Forest Baptist Medical Center, Medical Center Boulevard, Winston-Salem, NC, 27157, USA
| | - Michael I Miga
- Department of Biomedical Engineering, Vanderbilt University, 5824 Stevenson Center, Nashville, TN, 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Nashville, TN, USA
| | - Nitesh Rana
- Radiation Oncology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Albert Attia
- Radiation Oncology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jared A Weis
- Department of Biomedical Engineering, Wake Forest School of Medicine, Wake Forest Baptist Medical Center, Medical Center Boulevard, Winston-Salem, NC, 27157, USA
- Comprehensive Cancer Center, Wake Forest Baptist Medical Center, Medical Center Boulevard, Winston-Salem, NC, 27157, USA
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