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Demyashkin G, Koryakin S, Parshenkov M, Skovorodko P, Vadyukhin M, Uruskhanova Z, Stepanova Y, Shchekin V, Mirontsev A, Rostovskaya V, Ivanov S, Shegay P, Kaprin A. Morphofunctional Features of Glomeruli and Nephrons After Exposure to Electrons at Different Doses: Oxidative Stress, Inflammation, Apoptosis. Curr Issues Mol Biol 2024; 46:12608-12632. [PMID: 39590342 PMCID: PMC11593091 DOI: 10.3390/cimb46110748] [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: 09/30/2024] [Revised: 10/27/2024] [Accepted: 11/05/2024] [Indexed: 11/28/2024] Open
Abstract
Kidney disease has emerged as a significant global health issue, projected to become the fifth-leading cause of years of life lost by 2040. The kidneys, being highly radiosensitive, are vulnerable to damage from various forms of radiation, including gamma (γ) and X-rays. However, the effects of electron radiation on renal tissues remain poorly understood. Given the localized energy deposition of electron beams, this study seeks to investigate the dose-dependent morphological and molecular changes in the kidneys following electron irradiation, aiming to address the gap in knowledge regarding its impact on renal structures. The primary aim of this study is to conduct a detailed morphological and molecular analysis of the kidneys following localized electron irradiation at different doses, to better understand the dose-dependent effects on renal tissue structure and function in an experimental model. Male Wistar rats (n = 75) were divided into five groups, including a control group and four experimental groups receiving 2, 4, 6, or 8 Gray (Gy) of localized electron irradiation to the kidneys. Biochemical markers of inflammation (interleukin-1 beta [IL-1β], interleukin-6 [IL-6], interleukin-10 [IL-10], tumor necrosis factor-alpha [TNF-α]) and oxidative stress (malondialdehyde [MDA], superoxide dismutase [SOD], glutathione [GSH]) were measured, and morphological changes were assessed using histological and immunohistochemical techniques (TUNEL assay, caspase-3). The study revealed a significant dose-dependent increase in oxidative stress, inflammation, and renal tissue damage. Higher doses of irradiation resulted in increased apoptosis, early stages of fibrosis (at high doses), and morphological changes in renal tissue. This study highlights the dose-dependent effects of electrons on renal structures, emphasizing the need for careful consideration of the dosage in clinical use to minimize adverse effects on renal function.
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Affiliation(s)
- Grigory Demyashkin
- Department of Digital Oncomorphology, National Medical Research Centre of Radiology, 2nd Botkinsky Pass., 3, 125284 Moscow, Russia
- Laboratory of Histology and Immunohistochemistry, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University (Sechenov University), Trubetskaya St., 8/2, 119048 Moscow, Russia; (M.P.)
| | - Sergey Koryakin
- Department of Digital Oncomorphology, National Medical Research Centre of Radiology, 2nd Botkinsky Pass., 3, 125284 Moscow, Russia
| | - Mikhail Parshenkov
- Laboratory of Histology and Immunohistochemistry, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University (Sechenov University), Trubetskaya St., 8/2, 119048 Moscow, Russia; (M.P.)
| | - Polina Skovorodko
- Department of Digital Oncomorphology, National Medical Research Centre of Radiology, 2nd Botkinsky Pass., 3, 125284 Moscow, Russia
| | - Matvey Vadyukhin
- Department of Digital Oncomorphology, National Medical Research Centre of Radiology, 2nd Botkinsky Pass., 3, 125284 Moscow, Russia
| | - Zhanna Uruskhanova
- Laboratory of Histology and Immunohistochemistry, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University (Sechenov University), Trubetskaya St., 8/2, 119048 Moscow, Russia; (M.P.)
| | - Yulia Stepanova
- Department of Digital Oncomorphology, National Medical Research Centre of Radiology, 2nd Botkinsky Pass., 3, 125284 Moscow, Russia
| | - Vladimir Shchekin
- Department of Digital Oncomorphology, National Medical Research Centre of Radiology, 2nd Botkinsky Pass., 3, 125284 Moscow, Russia
- Research and Educational Resource Center for Immunophenotyping, Digital Spatial Profiling and Ultrastructural Analysis Innovative Technologies, Peoples’ Friendship University of Russia (RUDN University), Miklukho-Maklaya St., 6, 117198 Moscow, Russia
| | - Artem Mirontsev
- Laboratory of Histology and Immunohistochemistry, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University (Sechenov University), Trubetskaya St., 8/2, 119048 Moscow, Russia; (M.P.)
| | - Vera Rostovskaya
- Laboratory of Histology and Immunohistochemistry, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University (Sechenov University), Trubetskaya St., 8/2, 119048 Moscow, Russia; (M.P.)
| | - Sergey Ivanov
- Department of Digital Oncomorphology, National Medical Research Centre of Radiology, 2nd Botkinsky Pass., 3, 125284 Moscow, Russia
| | - Petr Shegay
- Department of Digital Oncomorphology, National Medical Research Centre of Radiology, 2nd Botkinsky Pass., 3, 125284 Moscow, Russia
| | - Andrei Kaprin
- Department of Digital Oncomorphology, National Medical Research Centre of Radiology, 2nd Botkinsky Pass., 3, 125284 Moscow, Russia
- Department of Urology and Operative Nephrology, Peoples’ Friendship University of Russia (RUDN University), Miklukho-Maklaya St., 6, 117198 Moscow, Russia
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Kasat PR, Kashikar SV, Parihar P, Sachani P, Shrivastava P, Mapari SA, Pradeep U, Bedi GN, Bhangale PN. Advances in Imaging for Metastatic Epidural Spinal Cord Compression: A Comprehensive Review of Detection, Diagnosis, and Treatment Planning. Cureus 2024; 16:e70110. [PMID: 39449880 PMCID: PMC11501474 DOI: 10.7759/cureus.70110] [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: 09/08/2024] [Accepted: 09/24/2024] [Indexed: 10/26/2024] Open
Abstract
Metastatic epidural spinal cord compression (MESCC) is a critical oncologic emergency caused by the invasion of metastatic tumors into the spinal epidural space, leading to compression of the spinal cord. If not promptly diagnosed and treated, MESCC can result in irreversible neurological deficits, including paralysis, significantly impacting the patient's quality of life. Early detection and timely intervention are crucial to prevent permanent damage. Imaging modalities play a pivotal role in the diagnosis, assessment of disease extent, and treatment planning for MESCC. Magnetic resonance imaging (MRI) is the current gold standard due to its superior ability to visualize the spinal cord, epidural space, and metastatic lesions. However, recent advances in imaging technologies have enhanced the detection and management of MESCC. Innovations such as functional MRI, diffusion-weighted imaging (DWI), and hybrid techniques like positron emission tomography-computed tomography (PET-CT) and PET-MRI have improved the accuracy of diagnosis, particularly in detecting early metastatic changes and guiding therapeutic interventions. This review provides a comprehensive analysis of the evolution of imaging techniques for MESCC, focusing on their roles in detection, diagnosis, and treatment planning. It also discusses the impact of these advances on clinical outcomes and future research directions in imaging modalities for MESCC. Understanding these advancements is critical for optimizing the management of MESCC and improving patient prognosis.
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Affiliation(s)
- Paschyanti R Kasat
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Shivali V Kashikar
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Pratapsingh Parihar
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Pratiksha Sachani
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Priyal Shrivastava
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Smruti A Mapari
- Obstetrics and Gynecology, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Utkarsh Pradeep
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Gautam N Bedi
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Paritosh N Bhangale
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
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Du S, Gong G, Liu R, Meng K, Yin Y. Advances in determining the gross tumor target volume for radiotherapy of brain metastases. Front Oncol 2024; 14:1338225. [PMID: 38779095 PMCID: PMC11109437 DOI: 10.3389/fonc.2024.1338225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 04/19/2024] [Indexed: 05/25/2024] Open
Abstract
Brain metastases (BMs) are the most prevalent intracranial malignant tumors in adults and are the leading cause of mortality attributed to malignant brain diseases. Radiotherapy (RT) plays a critical role in the treatment of BMs, with local RT techniques such as stereotactic radiosurgery (SRS)/stereotactic body radiotherapy (SBRT) showing remarkable therapeutic effectiveness. The precise determination of gross tumor target volume (GTV) is crucial for ensuring the effectiveness of SRS/SBRT. Multimodal imaging techniques such as CT, MRI, and PET are extensively used for the diagnosis of BMs and GTV determination. With the development of functional imaging and artificial intelligence (AI) technology, there are more innovative ways to determine GTV for BMs, which significantly improve the accuracy and efficiency of the determination. This article provides an overview of the progress in GTV determination for RT in BMs.
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Affiliation(s)
- Shanshan Du
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Guanzhong Gong
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Rui Liu
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Kangning Meng
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Yong Yin
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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Latreche A, Dissaux G, Querellou S, Mazouz Fatmi D, Lucia F, Bordron A, Vu A, Touati R, Nguyen V, Hamya M, Dissaux B, Bourbonne V. Correlation between rCBV Delineation Similarity and Overall Survival in a Prospective Cohort of High-Grade Gliomas Patients: The Hidden Value of Multimodal MRI? Biomedicines 2024; 12:789. [PMID: 38672146 PMCID: PMC11048661 DOI: 10.3390/biomedicines12040789] [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: 03/08/2024] [Revised: 03/18/2024] [Accepted: 03/26/2024] [Indexed: 04/28/2024] Open
Abstract
PURPOSE The accuracy of target delineation in radiation treatment planning of high-grade gliomas (HGGs) is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Magnetic resonance imaging (MRI) represents the standard imaging modality for delineation of gliomas with inherent limitations in accurately determining the microscopic extent of tumors. The purpose of this study was to assess the survival impact of multi-observer delineation variability of multiparametric MRI (mpMRI) and [18F]-FET PET/CT. MATERIALS AND METHODS Thirty prospectively included patients with histologically confirmed HGGs underwent a PET/CT and mpMRI including diffusion-weighted imaging (DWI: b0, b1000, ADC), contrast-enhanced T1-weighted imaging (T1-Gado), T2-weighted fluid-attenuated inversion recovery (T2Flair), and perfusion-weighted imaging with computation of relative cerebral blood volume (rCBV) and K2 maps. Nine radiation oncologists delineated the PET/CT and MRI sequences. Spatial similarity (Dice similarity coefficient: DSC) was calculated between the readers for each sequence. Impact of the DSC on progression-free survival (PFS) and overall survival (OS) was assessed using Kaplan-Meier curves and the log-rank test. RESULTS The highest DSC mean values were reached for morphological sequences, ranging from 0.71 +/- 0.18 to 0.84 +/- 0.09 for T2Flair and T1Gado, respectively, while metabolic volumes defined by PET/CT achieved a mean DSC of 0.75 +/- 0.11. rCBV variability (mean DSC0.32 +/- 0.20) significantly impacted PFS (p = 0.02) and OS (p = 0.002). CONCLUSIONS Our data suggest that the T1-Gado and T2Flair sequences were the most reproducible sequences, followed by PET/CT. Reproducibility for functional sequences was low, but rCBV inter-reader similarity significantly impacted PFS and OS.
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Affiliation(s)
- Amina Latreche
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Gurvan Dissaux
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Solène Querellou
- Nuclear Medicine Department, University Hospital, 29200 Brest, France;
- Groupe d’Etude de la Thrombose Occidentale GETBO (INSERM UMR 1304), Université de Bretagne Occidentale, 29200 Brest, France
| | | | - François Lucia
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
- LaTIM UMR 1101, INSERM, Université de Bretagne Occidentale, 29200 Brest, France
| | - Anais Bordron
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Alicia Vu
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Ruben Touati
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Victor Nguyen
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Mohamed Hamya
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Brieg Dissaux
- Groupe d’Etude de la Thrombose Occidentale GETBO (INSERM UMR 1304), Université de Bretagne Occidentale, 29200 Brest, France
- Radiology Department, University Hospital, 29200 Brest, France;
| | - Vincent Bourbonne
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
- LaTIM UMR 1101, INSERM, Université de Bretagne Occidentale, 29200 Brest, France
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Elliott A, Villemoes E, Farhat M, Klingberg E, Langshaw H, Svensson S, Chung C. Development and benchmarking diffusion magnetic resonance imaging analysis for integration into radiation treatment planning. Med Phys 2024; 51:2108-2118. [PMID: 37633837 DOI: 10.1002/mp.16670] [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: 03/12/2022] [Revised: 02/20/2023] [Accepted: 04/28/2023] [Indexed: 08/28/2023] Open
Abstract
PURPOSE The rising promise in the utility of advanced multi-parametric magnetic resonance (MR) imaging in radiotherapy (RT) treatment planning creates a necessity for testing and enhancing the accuracy of quantitative imaging analysis. Standardizing the analysis of diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) to generate meaningful and reproducible apparent diffusion coefficient (ADC) and fractional anisotropy (FA) lays the requisite needed for clinical integration. The aim of the demonstrated work is to benchmark the generation of the ADC and FA parametric map analyses using integrated tools in a commercial treatment planning system against the currently used ones. METHODS Three software packages were used for generating ADC and FA maps in this study; one tool was developed within a commercial treatment planning system, another by the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library FSL (Analysis Group, FMRIB, Oxford, United Kingdom), and an in-house tool developed at the M.D. Anderson Cancer Center. The ADC and FA maps generated by all three packages for 35 subjects were subtracted from one another, and the standard deviation of the images' differences was used to compare the reproducibility. The reproducibility of the ADC maps was compared with the Quantitative Imaging Biomarkers Alliance (QIBA) protocol, while that of the FA maps was compared to data in published literature. RESULTS Results show that the discrepancies between the ADC maps calculated for each patient using the three different software algorithms are less than 2% which meets the 3.6% recommended QIBA requirement. Except for a small number of isolated points, the majority of differences in FA maps for each patient produced by the three methods did not exceed 0.02 which is 10 times lower than the differences seen in healthy gray and white matter. The results were also compared to the maps generated by existing MR Imaging consoles and showed that the robustness of console generated ADC and FA maps is largely dependent on the correct application of scaling factors, that only if correctly placed; the differences between the three tested methods and the console generated values were within the recommended QIBA guidelines. CONCLUSIONS Cross-comparison difference maps demonstrated that quantitative reproducibility of ADC and FA metrics generated using our tested commercial treatment planning system were comparable to in-house and established tools as benchmarks. This integrated approach facilitates the clinical utility of diffusion imaging in radiation treatment planning workflow.
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Affiliation(s)
- Andrew Elliott
- Department Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
| | | | - Maguy Farhat
- Department Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
| | | | - Holly Langshaw
- Department Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
| | | | - Caroline Chung
- Department Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
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Liu W, Zuo B, Liu W, Huo Y, Zhang N, Yang M. Long non-coding RNAs in non-small cell lung cancer: implications for preventing therapeutic resistance. Biochim Biophys Acta Rev Cancer 2023; 1878:188982. [PMID: 37734560 DOI: 10.1016/j.bbcan.2023.188982] [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: 06/21/2023] [Revised: 08/14/2023] [Accepted: 08/15/2023] [Indexed: 09/23/2023]
Abstract
Lung cancer has the highest mortality and morbidity rates among all cancers worldwide. Despite many complex treatment options, including radiotherapy, chemotherapy, targeted drugs, immunotherapy, and combinations of these treatments, efficacy is low in cases of resistance to therapy, metastasis, and advanced disease, contributing to low overall survival. There is a pressing need for the discovery of novel biomarkers and therapeutic targets for the early diagnosis of lung cancer and to determine the efficacy and outcomes of drug treatments. There is now substantial evidence for the diagnostic and prognostic value of long noncoding RNAs (lncRNAs). This review briefly discusses recent findings on the roles and mechanisms of action of lncRNAs in the responses to therapy in non-small cell lung cancer.
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Affiliation(s)
- Wenjuan Liu
- Shandong Provincial Key Laboratory of Radiation Oncology, Cancer Research Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong Province 250117, China
| | - Bingli Zuo
- Human Resources Department, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong Province 250117, China
| | - Wenting Liu
- Department of Neurology, Weifang People's Hospital, Weifang, Shandong Province 261041, China
| | - Yanfei Huo
- Shandong Provincial Key Laboratory of Radiation Oncology, Cancer Research Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong Province 250117, China
| | - Nasha Zhang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong Province 250117, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu Province 211166, China.
| | - Ming Yang
- Shandong Provincial Key Laboratory of Radiation Oncology, Cancer Research Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong Province 250117, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu Province 211166, China.
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Xu T, Feng Y, Hong H, Xu Y, Chen J, Qiu X, Ding J, Huang C, Li L, Chen C, Fei Z. Biological target volume based on fluorine-18-fluorode-oxyglucose positron emission tomography/computed tomography imaging: a spurious proposition? Radiat Oncol 2023; 18:32. [PMID: 36810119 PMCID: PMC9942280 DOI: 10.1186/s13014-023-02225-4] [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: 11/25/2022] [Accepted: 02/12/2023] [Indexed: 02/23/2023] Open
Abstract
PURPOSE To assess whether the high metabolic region of fluorine-18-fluorode-oxyglucose (18F-FDG) in the primary lesion is the crux for recurrence in patients with nasopharyngeal carcinoma (NPC), to assess the feasibility and rationale for use of biological target volume (BTV) based on 18F-FDG positron emission tomography/computed tomography (18F-FDG-PET/CT). METHODS The retrospective study included 33 patients with NPC who underwent 18F-FDG-PET/CT at the time of initial diagnosis as well as the time of diagnosis of local recurrence. Paired 18F-FDG-PET/CT images for primary and recurrent lesion were matched by deformation coregistration method to determine the cross-failure rate between two lesions. RESULTS The median volume of the Vpri (primary tumor volume using the SUV thresholds of 2.5), the Vhigh (the volume of high FDG uptake using the SUV50%max isocontour), and the Vrecur (the recurrent tumor volume using the SUV thresholds of 2.5) were 22.85, 5.57, and 9.98 cm3, respectively. The cross-failure rate of Vrecur∩high showed that 82.82% (27/33) of local recurrent lesions had < 50% overlap volume with the region of high FDG uptake. The cross-failure rate of Vrecur∩pri showed that 96.97% (32/33) of local recurrent lesions had > 20% overlap volume with the primary tumor lesions and the median cross rate was up to 71.74%. CONCLUSION 18F-FDG-PET/CT may be a powerful tool for automatic target volume delineation, but it may not be the optimal imaging modality for dose escalation radiotherapy based on applicable isocontour. The combination of other functional imaging could delineate the BTV more accurately.
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Affiliation(s)
- Ting Xu
- grid.415110.00000 0004 0605 1140Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014 Fujian People’s Republic of China
| | - Ye Feng
- grid.415110.00000 0004 0605 1140Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014 Fujian People’s Republic of China
| | - Huiling Hong
- grid.415110.00000 0004 0605 1140Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014 Fujian People’s Republic of China
| | - Yiying Xu
- grid.415110.00000 0004 0605 1140Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014 Fujian People’s Republic of China
| | - Jiawei Chen
- grid.415110.00000 0004 0605 1140Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014 Fujian People’s Republic of China
| | - Xiufang Qiu
- grid.415110.00000 0004 0605 1140Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014 Fujian People’s Republic of China
| | - Jianming Ding
- grid.415110.00000 0004 0605 1140Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014 Fujian People’s Republic of China
| | - Chaoxiong Huang
- grid.415110.00000 0004 0605 1140Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014 Fujian People’s Republic of China
| | - Li Li
- grid.415110.00000 0004 0605 1140Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014 Fujian People’s Republic of China
| | - Chuanben Chen
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014, Fujian, People's Republic of China.
| | - Zhaodong Fei
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuma Road, Fuzhou, 350014, Fujian, People's Republic of China.
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Hardy SJ, Finkelstein AJ, Tivarus M, Culakova E, Mohile N, Weber M, Lin E, Zhong J, Usuki K, Schifitto G, Milano M, Janelsins-Benton MC. Cognitive and neuroimaging outcomes in individuals with benign and low-grade brain tumours receiving radiotherapy: a protocol for a prospective cohort study. BMJ Open 2023; 13:e066458. [PMID: 36792323 PMCID: PMC9933762 DOI: 10.1136/bmjopen-2022-066458] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 01/27/2023] [Indexed: 02/17/2023] Open
Abstract
INTRODUCTION Radiation-induced cognitive decline (RICD) occurs in 50%-90% of adult patients 6 months post-treatment. In patients with low-grade and benign tumours with long expected survival, this is of paramount importance. Despite advances in radiation therapy (RT) treatment delivery, better understanding of structures important for RICD is necessary to improve cognitive outcomes. We hypothesise that RT may affect network topology and microstructural integrity on MRI prior to any gross anatomical or apparent cognitive changes. In this longitudinal cohort study, we aim to determine the effects of RT on brain structural and functional integrity and cognition. METHODS AND ANALYSIS This study will enroll patients with benign and low-grade brain tumours receiving partial brain radiotherapy. Patients will receive either hypofractionated (>2 Gy/fraction) or conventionally fractionated (1.8-2 Gy/fraction) RT. All participants will be followed for 12 months, with MRIs conducted pre-RT and 6-month and 12 month post-RT, along with a battery of neurocognitive tests and questionnaires. The study was initiated in late 2018 and will continue enrolling through 2024 with final follow-ups completing in 2025. The neurocognitive battery assesses visual and verbal memory, attention, executive function, processing speed and emotional cognition. MRI protocols incorporate diffusion tensor imaging and resting state fMRI to assess structural connectivity and functional connectivity, respectively. We will estimate the association between radiation dose, imaging metrics and cognitive outcomes. ETHICS AND DISSEMINATION This study has been approved by the Research Subjects Review Board at the University of Rochester (STUDY00001512: Cognitive changes in patients receiving partial brain radiation). All results will be published in peer-reviewed journals and at scientific conferences. TRIAL REGISTRATION NUMBER ClinicalTrials.gov NCT04390906.
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Affiliation(s)
- Sara J Hardy
- Department of Radiation Oncology, University of Rochester Medical Center, Rochester, New York, USA
- Department of Neurology, University of Rochester Medical Center, Rochester, New York, USA
| | - Alan J Finkelstein
- Department of Biomedical Engineering, University of Rochester, Rochester, New York, USA
- Center for Advanced Brain Imaging and Neurophysiology, University of Rochester Medical Center, Rochester, New York, USA
| | - Madalina Tivarus
- Center for Advanced Brain Imaging and Neurophysiology, University of Rochester Medical Center, Rochester, New York, USA
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York, USA
| | - Eva Culakova
- Department of Surgery, University of Rochester Medical Center, Rochester, New York, USA
| | - Nimish Mohile
- Department of Neurology, University of Rochester Medical Center, Rochester, New York, USA
| | - Miriam Weber
- Department of Neurology, University of Rochester Medical Center, Rochester, New York, USA
- Department of Obstetrics and Gynecology, University of Rochester Medical Center, Rochester, New York, USA
| | - Edward Lin
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York, USA
| | - Jianhui Zhong
- Department of Biomedical Engineering, University of Rochester, Rochester, New York, USA
- Center for Advanced Brain Imaging and Neurophysiology, University of Rochester Medical Center, Rochester, New York, USA
| | - Kenneth Usuki
- Department of Radiation Oncology, University of Rochester Medical Center, Rochester, New York, USA
| | - Giovanni Schifitto
- Department of Neurology, Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York, USA
| | - Michael Milano
- Department of Radiation Oncology, University of Rochester Medical Center, Rochester, New York, USA
| | - M C Janelsins-Benton
- Department of Radiation Oncology, University of Rochester Medical Center, Rochester, New York, USA
- Department of Surgery, University of Rochester Medical Center, Rochester, New York, USA
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9
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Moore-Palhares D, Ho L, Lu L, Chugh B, Vesprini D, Karam I, Soliman H, Symons S, Leung E, Loblaw A, Myrehaug S, Stanisz G, Sahgal A, Czarnota GJ. Clinical implementation of magnetic resonance imaging simulation for radiation oncology planning: 5 year experience. Radiat Oncol 2023; 18:27. [PMID: 36750891 PMCID: PMC9903411 DOI: 10.1186/s13014-023-02209-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 01/16/2023] [Indexed: 02/09/2023] Open
Abstract
PURPOSE Integrating magnetic resonance (MR) into radiotherapy planning has several advantages. This report details the clinical implementation of an MR simulation (MR-planning) program for external beam radiotherapy (EBRT) in one of North America's largest radiotherapy programs. METHODS AND MATERIALS An MR radiotherapy planning program was developed and implemented at Sunnybrook Health Sciences Center in 2016 with two dedicated wide-bore MR platforms (1.5 and 3.0 Tesla). Planning MR was sequentially implemented every 3 months for separate treatment sites, including the central nervous system (CNS), gynecologic (GYN), head and neck (HN), genitourinary (GU), gastrointestinal (GI), breast, and brachial plexus. Essential protocols and processes were detailed in this report, including clinical workflow, optimized MR-image acquisition protocols, MR-adapted patient setup, strategies to overcome risks and challenges, and an MR-planning quality assurance program. This study retrospectively reviewed simulation site data for all MR-planning sessions performed for EBRT over the past 5 years. RESULTS From July 2016 to December 2021, 8798 MR-planning sessions were carried out, which corresponds to 25% of all computer tomography (CT) simulations (CT-planning) performed during the same period at our institution. There was a progressive rise from 80 MR-planning sessions in 2016 to 1126 in 2017, 1492 in 2018, 1824 in 2019, 2040 in 2020, and 2236 in 2021. As a result, the relative number of planning MR/CT increased from 3% of all planning sessions in 2016 to 36% in 2021. The most common site of MR-planning was CNS (49%), HN (13%), GYN (12%), GU (12%), and others (8%). CONCLUSION Detailed clinical processes and protocols of our MR-planning program were presented, which have been improved over more than 5 years of robust experience. Strategies to overcome risks and challenges in the implementation process are highlighted. Our work provides details that can be used by institutions interested in implementing an MR-planning program.
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Affiliation(s)
- Daniel Moore-Palhares
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Ling Ho
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada
| | - Lin Lu
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada
| | - Brige Chugh
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Danny Vesprini
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Irene Karam
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Hany Soliman
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Sean Symons
- grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada ,grid.413104.30000 0000 9743 1587Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Eric Leung
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Andrew Loblaw
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Sten Myrehaug
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Greg Stanisz
- grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Arjun Sahgal
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Gregory J. Czarnota
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada ,grid.17063.330000 0001 2157 2938Department of Medical Biophysics, University of Toronto, Toronto, Canada
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10
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Radiotherapy Target Volume Definition in Newly Diagnosed High-Grade Glioma Using 18F-FET PET Imaging and Multiparametric MRI: An Inter Observer Agreement Study. Tomography 2022; 8:2030-2041. [PMID: 36006068 PMCID: PMC9415495 DOI: 10.3390/tomography8040170] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 07/29/2022] [Accepted: 08/09/2022] [Indexed: 11/29/2022] Open
Abstract
Background: The aim of this prospective monocentric study was to assess the inter-observer agreement for tumor volume delineations by multiparametric MRI and 18-F-FET-PET/CT in newly diagnosed, untreated high-grade glioma (HGG) patients. Methods: Thirty patients HGG underwent O-(2-[18F]-fluoroethyl)-l-tyrosine(18F-FET) positron emission tomography (PET), and multiparametric MRI with computation of rCBV map and K2 map. Three nuclear physicians and three radiologists with different levels of experience delineated the 18-F-FET-PET/CT and 6 MRI sequences, respectively. Spatial similarity (Dice and Jaccard: DSC and JSC) and overlap (Overlap: OV) coefficients were calculated between the readers for each sequence. Results: DSC, JSC, and OV were high for 18F-FET PET/CT, T1-GD, and T2-FLAIR (>0.67). The Spearman correlation coefficient between readers was ≥0.6 for these sequences. Cross-comparison of similarity and overlap parameters showed significant differences for DSC and JSC between 18F-FET PET/CT and T2-FLAIR and for JSC between 18F-FET PET/CT and T1-GD with higher values for 18F-FET PET/CT. No significant difference was found between T1-GD and T2-FLAIR. rCBV, K2, b1000, and ADC showed correlation coefficients between readers <0.6. Conclusion: The interobserver agreements for tumor volume delineations were high for 18-F-FET-PET/CT, T1-GD, and T2-FLAIR. The DWI (b1000, ADC), rCBV, and K2-based sequences, as performed, did not seem sufficiently reproducible to be used in daily practice.
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11
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Lefebvre TL, Brown E, Hacker L, Else T, Oraiopoulou ME, Tomaszewski MR, Jena R, Bohndiek SE. The Potential of Photoacoustic Imaging in Radiation Oncology. Front Oncol 2022; 12:803777. [PMID: 35311156 PMCID: PMC8928467 DOI: 10.3389/fonc.2022.803777] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 02/07/2022] [Indexed: 12/16/2022] Open
Abstract
Radiotherapy is recognized globally as a mainstay of treatment in most solid tumors and is essential in both curative and palliative settings. Ionizing radiation is frequently combined with surgery, either preoperatively or postoperatively, and with systemic chemotherapy. Recent advances in imaging have enabled precise targeting of solid lesions yet substantial intratumoral heterogeneity means that treatment planning and monitoring remains a clinical challenge as therapy response can take weeks to manifest on conventional imaging and early indications of progression can be misleading. Photoacoustic imaging (PAI) is an emerging modality for molecular imaging of cancer, enabling non-invasive assessment of endogenous tissue chromophores with optical contrast at unprecedented spatio-temporal resolution. Preclinical studies in mouse models have shown that PAI could be used to assess response to radiotherapy and chemoradiotherapy based on changes in the tumor vascular architecture and blood oxygen saturation, which are closely linked to tumor hypoxia. Given the strong relationship between hypoxia and radio-resistance, PAI assessment of the tumor microenvironment has the potential to be applied longitudinally during radiotherapy to detect resistance at much earlier time-points than currently achieved by size measurements and tailor treatments based on tumor oxygen availability and vascular heterogeneity. Here, we review the current state-of-the-art in PAI in the context of radiotherapy research. Based on these studies, we identify promising applications of PAI in radiation oncology and discuss the future potential and outstanding challenges in the development of translational PAI biomarkers of early response to radiotherapy.
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Affiliation(s)
- Thierry L. Lefebvre
- Department of Physics, University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Emma Brown
- Department of Physics, University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Lina Hacker
- Department of Physics, University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Thomas Else
- Department of Physics, University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Mariam-Eleni Oraiopoulou
- Department of Physics, University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Michal R. Tomaszewski
- Department of Cancer Physiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
| | - Rajesh Jena
- Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Sarah E. Bohndiek
- Department of Physics, University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
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