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Zhang S, Simard M, Lapointe A, Filion É, Campeau MP, Vu TTT, Roberge D, Carrier JF, Blais D, Bedwani S, Bahig H. Evaluation of Radiation Dose Effect on Lung Function Using Iodine Maps Derived From Dual-Energy Computed Tomography. Int J Radiat Oncol Biol Phys 2024:S0360-3016(24)00609-6. [PMID: 38705488 DOI: 10.1016/j.ijrobp.2024.04.069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/04/2024] [Accepted: 04/25/2024] [Indexed: 05/07/2024]
Abstract
PURPOSE There is interest in using dual-energy computed tomography (DECT) to evaluate organ function before and after radiation therapy (RT). The purpose of this study (trial identifier: NCT04863027) is to assess longitudinal changes in lung perfusion using iodine maps derived from DECT in patients with lung cancer treated with conventional or stereotactic RT. METHODS AND MATERIALS For 48 prospectively enrolled patients with lung cancer, a contrast-enhanced DECT using a dual-source CT simulator was acquired pretreatment and at 6 and 12 months posttreatment. Pulmonary functions tests (PFT) were obtained at baseline and at 6 and 12 months posttreatment. Iodine maps were extracted from the DECT images using a previously described 2-material decomposition framework. Longitudinal iodine maps were normalized using a reference region defined as all voxels with perfusion in the top 10% outside of the 5 Gy isodose volume. Normalized functional responses (NFR) were calculated for 3 dose ranges: <5, 5 to 20, and >20 Gy. Mixed model analysis was used to assess the correlation between dose metrics and NFR. Pearson correlation was used to assess if NFRs were correlated with PFT changes. RESULTS Out of the 48 patients, 21 (44%) were treated with stereotactic body RT and 27 (56%) were treated with conventionally fractionated intensity-modulated RT. Thirty-one out of these 48 patients were ultimately included in data analysis. It was found that NFR is linearly correlated with dose (P < .001) for both groups. The number of months elapsed post-RT was also found to correlate with NFR (P = .029), although this correlation was not observed for the stereotactic body RT subgroup. The NFR was not found to correlate with PFT changes. CONCLUSIONS DECT-derived iodine maps are a promising method for detailed anatomic evaluation of radiation effect on lung function, including potentially subclinical changes.
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Affiliation(s)
- Shen Zhang
- Département de radio-oncologie, Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada
| | - Mikaël Simard
- Centre de recherche du Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada; Département de physique, Université de Montréal, Montréal, Quebec, Canada; Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Andréanne Lapointe
- Département de radio-oncologie, Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada; Centre de recherche du Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada
| | - Édith Filion
- Département de radio-oncologie, Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada
| | - Marie-Pierre Campeau
- Département de radio-oncologie, Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada
| | - Thi Trinh Thuc Vu
- Département de radio-oncologie, Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada
| | - David Roberge
- Département de radio-oncologie, Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada
| | - Jean-François Carrier
- Département de radio-oncologie, Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada; Centre de recherche du Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada; Département de physique, Université de Montréal, Montréal, Quebec, Canada
| | - Danis Blais
- Département de radio-oncologie, Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada; Centre de recherche du Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada
| | - Stéphane Bedwani
- Département de radio-oncologie, Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada; Centre de recherche du Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada
| | - Houda Bahig
- Département de radio-oncologie, Centre Hospitalier de l'Université de Montréal, Montréal, Quebec, Canada.
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Kaur G, Roy B. Decoding Tumor Angiogenesis for Therapeutic Advancements: Mechanistic Insights. Biomedicines 2024; 12:827. [PMID: 38672182 PMCID: PMC11048662 DOI: 10.3390/biomedicines12040827] [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: 03/15/2024] [Revised: 04/05/2024] [Accepted: 04/08/2024] [Indexed: 04/28/2024] Open
Abstract
Tumor angiogenesis, the formation of new blood vessels within the tumor microenvironment, is considered a hallmark of cancer progression and represents a crucial target for therapeutic intervention. The tumor microenvironment is characterized by a complex interplay between proangiogenic and antiangiogenic factors, regulating the vascularization necessary for tumor growth and metastasis. The study of angiogenesis involves a spectrum of techniques, spanning from biomarker assessment to advanced imaging modalities. This comprehensive review aims to provide insights into the molecular intricacies, regulatory dynamics, and clinical implications of tumor angiogenesis. By delving into these aspects, we gain a deeper understanding of the processes driving vascularization in tumors, paving the way for the development of novel and effective antiangiogenic therapies in the fight against cancer.
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Affiliation(s)
- Geetika Kaur
- Integrative Biosciences Center, Wayne State University, Detroit, MI 48202, USA;
- Department of Ophthalmology, Visual and Anatomical Sciences, Wayne State University School of Medicine, Detroit, MI 48202, USA
| | - Bipradas Roy
- Division of Cardiology, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA
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Darami M, Mahmoudian B, Ljungberg M, Pirayesh Islamian J. Impact of Wolfmet Tungsten Alloys as Parallel-Hole Collimator Material on Single-Photon Emission Computed Tomography Image Quality and Functional Parameters: A Simulating Medical Imaging Nuclear Detectors Monte Carlo Study. World J Nucl Med 2023; 22:217-225. [PMID: 37854088 PMCID: PMC10581757 DOI: 10.1055/s-0043-1771287] [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] [Indexed: 10/20/2023] Open
Abstract
Objectives Collimators have a significant role in image quality and detectability in single-photon emission computed tomography (SPECT) imaging. Using an appropriate alloy that effectively absorbs scattered photons, without induced secondary x-rays, and with proper rigidity and weight may provide an effective approach to the image improvement that conventionally collimators made of lead (Pb). Materials and Methods A Siemens E.CAM SPECT imaging system equipped with low-energy high-resolution (LEHR) collimator was simulated by the Simulating Medical Imaging Nuclear Detectors Monte Carlo program. Experimental and simulated data were compared based on a 2-mm 99m Tc point source in an acrylic cylindrical Deluxe phantom (Data Spectrum, Inc). Seven types of tungsten (W) alloys (Wolfmet), with W content from 90 to 97% by weight, were then used as collimator materials of the simulated system. Camera parameters, such as energy- and spatial resolution, image contrast, and collimator-related parameters, such as fraction of septal penetration, scatter-to-primary ratios, and percentage of induced secondary x-rays, due to interactions in the collimator, were evaluated. Results Acceptable conformity was found for the simulated and experiment systems in terms of energy spectra, 10.113 and 10.140%, full width at half-maximum (FWHM) of the point spread function (PSF) curves, 8.78 and 9.06 mm, sensitivity, 78.46 and 78.34 cps/MBq, and contrast in images of 19.1 mm cold spheres in the Deluxe phantom, 79.17 and 78.97%, respectively. Results on the parameters of the simulated system with LEHR collimator made from the alloys showed that the alloy consisting of 90% W, 6% nickel, and 4% copper provided an FWHM of 8.76 mm, resulting in a 0.2% improvement in spatial resolution. Furthermore, all the Wolfmet collimators showed a 48% reduction in the amount of X-rays production compared to the Pb. Conclusion A Wolfmet LEHR collimator, made by a combination of W (90%), Ni (6%), and Cu (6%) provides a better image quality and detectability compared to the Pb.
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Affiliation(s)
- Maryam Darami
- Medical Radiation Sciences Research Team, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Babak Mahmoudian
- Department of Nuclear Medicine, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | | | - Jalil Pirayesh Islamian
- Department of Medical Physics, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
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Chakraborty K, Mondal J, An JM, Park J, Lee YK. Advances in Radionuclides and Radiolabelled Peptides for Cancer Therapeutics. Pharmaceutics 2023; 15:pharmaceutics15030971. [PMID: 36986832 PMCID: PMC10054444 DOI: 10.3390/pharmaceutics15030971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/13/2023] [Accepted: 03/15/2023] [Indexed: 03/19/2023] Open
Abstract
Radiopharmaceutical therapy, which can detect and treat tumours simultaneously, was introduced more than 80 years ago, and it has changed medical strategies with respect to cancer. Many radioactive radionuclides have been developed, and functional, molecularly modified radiolabelled peptides have been used to produce biomolecules and therapeutics that are vastly utilised in the field of radio medicine. Since the 1990s, they have smoothly transitioned into clinical application, and as of today, a wide variety of radiolabelled radionuclide derivatives have been examined and evaluated in various studies. Advanced technologies, such as conjugation of functional peptides or incorporation of radionuclides into chelating ligands, have been developed for advanced radiopharmaceutical cancer therapy. New radiolabelled conjugates for targeted radiotherapy have been designed to deliver radiation directly to cancer cells with improved specificity and minimal damage to the surrounding normal tissue. The development of new theragnostic radionuclides, which can be used for both imaging and therapy purposes, allows for more precise targeting and monitoring of the treatment response. The increased use of peptide receptor radionuclide therapy (PRRT) is also important in the targeting of specific receptors which are overexpressed in cancer cells. In this review, we provide insights into the development of radionuclides and functional radiolabelled peptides, give a brief background, and describe their transition into clinical application.
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Affiliation(s)
- Kushal Chakraborty
- Department of IT and Energy Convergence (BK21 FOUR), Korea National University of Transportation, Chungju 27469, Republic of Korea
| | - Jagannath Mondal
- Department of Green Bio Engineering, Graduate School, Korea National University of Transportation, Chungju 27469, Republic of Korea
- 4D Convergence Technology Institute, Korea National University of Transportation, Jeungpyeong 27909, Republic of Korea
| | - Jeong Man An
- Department of Bioengineering, College of Engineering, Hanyang University, Seoul 04763, Republic of Korea
| | - Jooho Park
- Department of Applied Life Science, Graduate School, BK21 Program, Konkuk University, Chungju 27478, Republic of Korea
- Research Institute for Biomedical & Health Science, Konkuk University, Chungju 27478, Republic of Korea
- Correspondence: (J.P.); (Y.-K.L.); Tel.: +82-43-841-5224 (Y.-K.L.)
| | - Yong-Kyu Lee
- Department of Green Bio Engineering, Graduate School, Korea National University of Transportation, Chungju 27469, Republic of Korea
- 4D Convergence Technology Institute, Korea National University of Transportation, Jeungpyeong 27909, Republic of Korea
- Correspondence: (J.P.); (Y.-K.L.); Tel.: +82-43-841-5224 (Y.-K.L.)
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Xenon-Enhanced Ventilation Computed Tomography for Functional Lung Avoidance Radiation Therapy in Patients With Lung Cancer. Int J Radiat Oncol Biol Phys 2023; 115:356-365. [PMID: 36029910 DOI: 10.1016/j.ijrobp.2022.07.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 06/22/2022] [Accepted: 07/19/2022] [Indexed: 01/14/2023]
Abstract
PURPOSE This phase 2 trial aimed to determine whether xenon-enhanced ventilation computed tomography (XeCT)-guided functional-lung-avoidance radiation therapy could reduce the radiation pneumonitis (RP) rate in patients with lung cancer undergoing definitive chemoradiation therapy. METHODS AND MATERIALS Functional lung ventilation was measured via pulmonary function testing (PFT) and XeCT. A standard plan (SP) without reference to XeCT and a functional-lung-avoidance plan (fAP) optimized for lowering the radiation dose to the functional lung at the guidance of XeCT were designed. Dosimetric parameters and predicted RP risks modeled by biological evaluation were compared between the 2 plans in a treatment planning system (TPS). All patients received the approved fAP. The primary endpoint was the rate of grade ≥2 RP, and the secondary endpoints were the survival outcomes. The study hypothesis was that fAP could reduce the rate of grade ≥2 RP to 12% compared with a 30% historical rate. RESULTS Thirty-six patients were evaluated. Xenon-enhanced total functional lung volumes positively correlated with PFT ventilation parameters (forced vital capacity, P = .012; forced expiratory volume in 1 second, P = .035), whereas they were not correlated with the diffusion capacity parameter. We observed a 17% rate of grade ≥2 RP (6 of 36 patients), which was significantly different (P = .040) compared with the historical control. Compared with the SP, the fAP significantly spared the total ventilated lung, leading to a reduction in predicted grade ≥2 RP (P = .001) by TPS biological evaluation. The median follow-up was 15.2 months. The 1-year local control (LC), disseminated failure-free survival (DFFS), and overall survival (OS) rates were 88%, 66%, and 91%, respectively. The median LC and OS were not reached, and the median DFFS was 24.0 months (95% confidence interval, 15.7-32.3 months). CONCLUSIONS This report of XeCT-guided functional-lung-avoidance radiation therapy provided evidence showing its feasibility in clinical practice. Its benefit should be assessed in a broader multicenter trial setting.
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Chen Z, Huang YH, Kong FM, Ho WY, Ren G, Cai J. A super-voxel-based method for generating surrogate lung ventilation images from CT. Front Physiol 2023; 14:1085158. [PMID: 37179833 PMCID: PMC10171197 DOI: 10.3389/fphys.2023.1085158] [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: 10/31/2022] [Accepted: 04/06/2023] [Indexed: 05/15/2023] Open
Abstract
Purpose: This study aimed to develop and evaluate CTVISVD , a super-voxel-based method for surrogate computed tomography ventilation imaging (CTVI). Methods and Materials: The study used four-dimensional CT (4DCT) and single-photon emission computed tomography (SPECT) images and corresponding lung masks from 21 patients with lung cancer obtained from the Ventilation And Medical Pulmonary Image Registration Evaluation dataset. The lung volume of the exhale CT for each patient was segmented into hundreds of super-voxels using the Simple Linear Iterative Clustering (SLIC) method. These super-voxel segments were applied to the CT and SPECT images to calculate the mean density values (D mean) and mean ventilation values (Vent mean), respectively. The final CT-derived ventilation images were generated by interpolation from the D mean values to yield CTVISVD. For the performance evaluation, the voxel- and region-wise differences between CTVISVD and SPECT were compared using Spearman's correlation and the Dice similarity coefficient index. Additionally, images were generated using two deformable image registration (DIR)-based methods, CTVIHU and CTVIJac, and compared with the SPECT images. Results: The correlation between the D mean and Vent mean of the super-voxel was 0.59 ± 0.09, representing a moderate-to-high correlation at the super-voxel level. In the voxel-wise evaluation, the CTVISVD method achieved a stronger average correlation (0.62 ± 0.10) with SPECT, which was significantly better than the correlations achieved with the CTVIHU (0.33 ± 0.14, p < 0.05) and CTVIJac (0.23 ± 0.11, p < 0.05) methods. For the region-wise evaluation, the Dice similarity coefficient of the high functional region for CTVISVD (0.63 ± 0.07) was significantly higher than the corresponding values for the CTVIHU (0.43 ± 0.08, p < 0.05) and CTVIJac (0.42 ± 0.05, p < 0.05) methods. Conclusion: The strong correlation between CTVISVD and SPECT demonstrates the potential usefulness of this novel method of ventilation estimation for surrogate ventilation imaging.
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Affiliation(s)
- Zhi Chen
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Yu-Hua Huang
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Feng-Ming Kong
- Department of Clinical Oncology, Queen Mary Hospital, Hong Kong, China
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
| | - Wai Yin Ho
- Department of Nuclear Medicine, Queen Mary Hospital, Hong Kong, China
| | - Ge Ren
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
- *Correspondence: Ge Ren, ; Jing Cai,
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
- *Correspondence: Ge Ren, ; Jing Cai,
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Zhou PX, Zhang SX. Functional lung imaging in thoracic tumor radiotherapy: Application and progress. Front Oncol 2022; 12:908345. [PMID: 36212454 PMCID: PMC9544588 DOI: 10.3389/fonc.2022.908345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 08/17/2022] [Indexed: 12/12/2022] Open
Abstract
Radiotherapy plays an irreplaceable and unique role in treating thoracic tumors, but the occurrence of radiation-induced lung injury has limited the increase in tumor target doses and has influenced patients’ quality of life. However, the introduction of functional lung imaging has been incorporating functional lungs into radiotherapy planning. The design of the functional lung protection plan, while meeting the target dose requirements and dose limitations of the organs at risk (OARs), minimizes the radiation dose to the functional lung, thus reducing the occurrence of radiation-induced lung injury. In this manuscript, we mainly reviewed the lung ventilation or/and perfusion functional imaging modalities, application, and progress, as well as the results based on the functional lung protection planning in thoracic tumors. In addition, we also discussed the problems that should be explored and further studied in the practical application based on functional lung radiotherapy planning.
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Affiliation(s)
- Pi-Xiao Zhou
- Radiotherapy Center, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
- Department of Oncology, The First People's Hospital of Changde City, Changde, China
| | - Shu-Xu Zhang
- Radiotherapy Center, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
- *Correspondence: Shu-Xu Zhang,
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Ding Y, Yang L, Zhou Q, Bi J, Li Y, Pi G, Wei W, Hu D, Rao Q, Li H, Zhao L, Liu A, Du D, Wang X, Zhou X, Han G, Qing K. A pilot study of function-based radiation therapy planning for lung cancer using hyperpolarized xenon-129 ventilation MRI. J Appl Clin Med Phys 2022; 23:e13502. [PMID: 35045204 PMCID: PMC8906214 DOI: 10.1002/acm2.13502] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/01/2021] [Accepted: 11/29/2021] [Indexed: 11/05/2022] Open
Abstract
PURPOSE Radiation-induced lung injury (RILI) is a common side effect in patients with non-small cell lung cancer (NSCLC) treated with radiotherapy. Minimizing irradiation into highly functional areas of the lung may reduce the occurrence of RILI. The aim of this study is to evaluate the feasibility and utility of hyperpolarized xenon-129 magnetic resonance imaging (MRI), an imaging tool for evaluation of the pulmonary function, to guide radiotherapy planning. METHODS Ten locally advanced NSCLC patients were recruited. Each patient underwent a simulation computed tomography (CT) scan and hyperpolarized xenon-129 MRI, then received 64 Gyin 32 fractions for radiotherapy. Clinical contours were drawn on CT. Lung regions with good ventilation were contoured based on the MRI. Two intensity-modulated radiation therapy plans were made for each patient: an anatomic plan (Plan-A) based on CT alone and a function-based plan (Plan-F) based on CT and MRI results. Compared to Plan-A, Plan-F was generated with two additional steps: (1) beam angles were carefully chosen to minimize direct radiation entering well-ventilated areas, and (2) additional optimization criteria were applied to well-ventilated areas to minimize dose exposure. V20Gy , V10Gy , V5Gy , and the mean dose in the lung were compared between the two plans. RESULTS Plan-A and Plan-F were both clinically acceptable and met similar target coverage and organ-at-risk constraints (p > 0.05) except for the ventilated lungs. Compared with Plan-A, V5Gy (Plan-A: 30.7 ± 11.0%, Plan-F: 27.2 ± 9.3%), V10Gy (Plan-A: 22.0 ± 8.6%, Plan-F: 19.3 ± 7.0%), and V20Gy (Plan-A: 12.5 ± 5.6%, Plan-F: 11.0 ± 4.1%) for well-ventilated lung areas were significantly reduced in Plan-F (p < 0.05). CONCLUSION In this pilot study, function-based radiotherapy planning using hyperpolarized xenon-129 MRI is demonstrated to be feasible in 10 patients with NSCLC with the potential to reduce radiation exposure in well-ventilated areas of the lung defined by hyperpolarized xenon-129 MRI.
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Affiliation(s)
- Yi Ding
- Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lu Yang
- Department of Radiation Oncology, Renmin Hospital, Wuhan University, Wuhan, China
| | - Qian Zhou
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Wuhan National Laboratory for Optoelectronics, Chinese Academy of Sciences, Wuhan, China
| | - Jianping Bi
- Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Li
- Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Guoliang Pi
- Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Wei
- Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Desheng Hu
- Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qiuchen Rao
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Wuhan National Laboratory for Optoelectronics, Chinese Academy of Sciences, Wuhan, China
| | - Haidong Li
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Wuhan National Laboratory for Optoelectronics, Chinese Academy of Sciences, Wuhan, China
| | - Li Zhao
- Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - An Liu
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte, California, USA
| | - Dongsu Du
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte, California, USA
| | - Xiao Wang
- Department of Radiation Oncology, Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey, USA
| | - Xin Zhou
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Wuhan National Laboratory for Optoelectronics, Chinese Academy of Sciences, Wuhan, China
| | - Guang Han
- Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kun Qing
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte, California, USA
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Recent Progress in Technetium-99m-Labeled Nanoparticles for Molecular Imaging and Cancer Therapy. NANOMATERIALS 2021; 11:nano11113022. [PMID: 34835786 PMCID: PMC8618883 DOI: 10.3390/nano11113022] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 11/05/2021] [Accepted: 11/06/2021] [Indexed: 12/12/2022]
Abstract
Nanotechnology has played a tremendous role in molecular imaging and cancer therapy. Over the last decade, scientists have worked exceptionally to translate nanomedicine into clinical practice. However, although several nanoparticle-based drugs are now clinically available, there is still a vast difference between preclinical products and clinically approved drugs. An efficient translation of preclinical results to clinical settings requires several critical studies, including a detailed, highly sensitive, pharmacokinetics and biodistribution study, and selective and efficient drug delivery to the target organ or tissue. In this context, technetium-99m (99mTc)-based radiolabeling of nanoparticles allows easy, economical, non-invasive, and whole-body in vivo tracking by the sensitive clinical imaging technique single-photon emission computed tomography (SPECT). Hence, a critical analysis of the radiolabeling strategies of potential drug delivery and therapeutic systems used to monitor results and therapeutic outcomes at the preclinical and clinical levels remains indispensable to provide maximum benefit to the patient. This review discusses up-to-date 99mTc radiolabeling strategies of a variety of important inorganic and organic nanoparticles and their application to preclinical imaging studies.
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Guo H, Xu K, Duan G, Wen L, He Y. Progress and future prospective of FDG-PET/CT imaging combined with optimized procedures in lung cancer: toward precision medicine. Ann Nucl Med 2021; 36:1-14. [PMID: 34727331 DOI: 10.1007/s12149-021-01683-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/30/2021] [Indexed: 12/19/2022]
Abstract
With a 5-year overall survival of approximately 20%, lung cancer has always been the number one cancer-specific killer all over the world. As a fusion of positron emission computed tomography (PET) and computed tomography (CT), PET/CT has revolutionized cancer imaging over the past 20 years. In this review, we focused on the optimization of the function of 18F-flurodeoxyglucose (FDG)-PET/CT in diagnosis, prognostic prediction and therapy management of lung cancers by computer programs. FDG-PET/CT has demonstrated a surprising role in development of therapeutic biomarkers, prediction of therapeutic responses and long-term survival, which could be conducive to solving existing dilemmas. Meanwhile, novel tracers and optimized procedures are also developed to control the quality and improve the effect of PET/CT. With the continuous development of some new imaging agents and their clinical applications, application value of PET/CT has broad prospects in this area.
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Affiliation(s)
- Haoyue Guo
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China
- School of Medicine, Tongji University, No. 1239 Siping Road, Shanghai, 200092, China
| | - Kandi Xu
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China
- School of Medicine, Tongji University, No. 1239 Siping Road, Shanghai, 200092, China
| | - Guangxin Duan
- State Key Laboratory of Radiation Medicine and Protection, School for Radiological and Interdisciplinary Sciences (RAD-X), Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Soochow University, Suzhou, 215123, China
| | - Ling Wen
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215000, China.
| | - Yayi He
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China.
- School of Medicine, Tongji University, No. 1239 Siping Road, Shanghai, 200092, China.
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Porter EM, Myziuk NK, Quinn TJ, Lozano D, Peterson AB, Quach DM, Siddiqui ZA, Guerrero TM. Synthetic pulmonary perfusion images from 4DCT for functional avoidance using deep learning. Phys Med Biol 2021; 66. [PMID: 34293726 DOI: 10.1088/1361-6560/ac16ec] [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: 02/02/2021] [Accepted: 07/22/2021] [Indexed: 01/14/2023]
Abstract
Purpose.To develop and evaluate the performance of a deep learning model to generate synthetic pulmonary perfusion images from clinical 4DCT images for patients undergoing radiotherapy for lung cancer.Methods. A clinical data set of 58 pre- and post-radiotherapy99mTc-labeled MAA-SPECT perfusion studies (32 patients) each with contemporaneous 4DCT studies was collected. Using the inhale and exhale phases of the 4DCT, a 3D-residual network was trained to create synthetic perfusion images utilizing the MAA-SPECT as ground truth. The training process was repeated for a 50-imaging study, five-fold validation with twenty model instances trained per fold. The highest performing model instance from each fold was selected for inference upon the eight-study test set. A manual lung segmentation was used to compute correlation metrics constrained to the voxels within the lungs. From the pre-treatment test cases (N = 5), 50th percentile contours of well-perfused lung were generated from both the clinical and synthetic perfusion images and the agreement was quantified.Results. Across the hold-out test set, our deep learning model predicted perfusion with a Spearman correlation coefficient of 0.70 (IQR: 0.61-0.76) and a Pearson correlation coefficient of 0.66 (IQR: 0.49-0.73). The agreement of the functional avoidance contour pairs was Dice of 0.803 (IQR: 0.750-0.810) and average surface distance of 5.92 mm (IQR: 5.68-7.55).Conclusion. We demonstrate that from 4DCT alone, a deep learning model can generate synthetic perfusion images with potential application in functional avoidance treatment planning.
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Affiliation(s)
- Evan M Porter
- Department of Medical Physics, Wayne State University, Detroit, MI, United States of America.,Beaumont Artificial Intelligence Research Laboratory, Beaumont Health, Royal Oak, MI, United States of America.,Department of Radiation Oncology, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
| | - Nicholas K Myziuk
- Beaumont Artificial Intelligence Research Laboratory, Beaumont Health, Royal Oak, MI, United States of America.,Department of Radiation Oncology, Beaumont Health, Royal Oak, MI, United States of America
| | - Thomas J Quinn
- Beaumont Artificial Intelligence Research Laboratory, Beaumont Health, Royal Oak, MI, United States of America.,Department of Radiation Oncology, Beaumont Health, Royal Oak, MI, United States of America
| | - Daniela Lozano
- Beaumont Artificial Intelligence Research Laboratory, Beaumont Health, Royal Oak, MI, United States of America.,Oakland University William Beaumont School of Medicine, Oakland University, Rochester, MI, United States of America
| | - Avery B Peterson
- Department of Medical Physics, Wayne State University, Detroit, MI, United States of America.,Beaumont Artificial Intelligence Research Laboratory, Beaumont Health, Royal Oak, MI, United States of America
| | - Duyen M Quach
- Beaumont Artificial Intelligence Research Laboratory, Beaumont Health, Royal Oak, MI, United States of America.,Oakland University William Beaumont School of Medicine, Oakland University, Rochester, MI, United States of America
| | - Zaid A Siddiqui
- Beaumont Artificial Intelligence Research Laboratory, Beaumont Health, Royal Oak, MI, United States of America.,Department of Radiation Oncology, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
| | - Thomas M Guerrero
- Beaumont Artificial Intelligence Research Laboratory, Beaumont Health, Royal Oak, MI, United States of America.,Department of Radiation Oncology, Beaumont Health, Royal Oak, MI, United States of America.,Oakland University William Beaumont School of Medicine, Oakland University, Rochester, MI, United States of America
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Ebert MA, Gulliford S, Acosta O, de Crevoisier R, McNutt T, Heemsbergen WD, Witte M, Palma G, Rancati T, Fiorino C. Spatial descriptions of radiotherapy dose: normal tissue complication models and statistical associations. Phys Med Biol 2021; 66:12TR01. [PMID: 34049304 DOI: 10.1088/1361-6560/ac0681] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 05/28/2021] [Indexed: 12/20/2022]
Abstract
For decades, dose-volume information for segmented anatomy has provided the essential data for correlating radiotherapy dosimetry with treatment-induced complications. Dose-volume information has formed the basis for modelling those associations via normal tissue complication probability (NTCP) models and for driving treatment planning. Limitations to this approach have been identified. Many studies have emerged demonstrating that the incorporation of information describing the spatial nature of the dose distribution, and potentially its correlation with anatomy, can provide more robust associations with toxicity and seed more general NTCP models. Such approaches are culminating in the application of computationally intensive processes such as machine learning and the application of neural networks. The opportunities these approaches have for individualising treatment, predicting toxicity and expanding the solution space for radiation therapy are substantial and have clearly widespread and disruptive potential. Impediments to reaching that potential include issues associated with data collection, model generalisation and validation. This review examines the role of spatial models of complication and summarises relevant published studies. Sources of data for these studies, appropriate statistical methodology frameworks for processing spatial dose information and extracting relevant features are described. Spatial complication modelling is consolidated as a pathway to guiding future developments towards effective, complication-free radiotherapy treatment.
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Affiliation(s)
- Martin A Ebert
- School of Physics, Mathematics and Computing, University of Western Australia, Crawley, Western Australia, Australia
- Department of Radiation Oncology, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- 5D Clinics, Claremont, Western Australia, Australia
| | - Sarah Gulliford
- Department of Radiotherapy Physics, University College Hospitals London, United Kingdom
- Department of Medical Physics and Bioengineering, University College London, United Kingdom
| | - Oscar Acosta
- Univ Rennes, CLCC Eugène Marquis, INSERM, LTSI-UMR 1099, F-35000 Rennes, France
| | | | - Todd McNutt
- Johns Hopkins University, Baltimore, Maryland, United States of America
| | | | - Marnix Witte
- The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Giuseppe Palma
- Institute of Biostructures and Bioimaging, National Research Council, Napoli, Italy
| | - Tiziana Rancati
- Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Claudio Fiorino
- Medical Physics, San Raffaele Scientific Institute, Milano, Italy
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