1
|
Hill MA, Staut N, Thompson JM, Verhaegen F. Dosimetric validation of SmART-RAD Monte Carlo modelling for x-ray cabinet radiobiology irradiators. Phys Med Biol 2024; 69:095014. [PMID: 38518380 PMCID: PMC11031639 DOI: 10.1088/1361-6560/ad3720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 02/23/2024] [Accepted: 03/22/2024] [Indexed: 03/24/2024]
Abstract
Objective. Accuracy and reproducibility in the measurement of radiation dose and associated reporting are critically important for the validity of basic and preclinical radiobiological studies performed with kilovolt x-ray radiation cabinets. This is essential to enable results of radiobiological studies to be repeated, as well as enable valid comparisons between laboratories. In addition, the commonly used single point dose value hides the 3D dose heterogeneity across the irradiated sample. This is particularly true for preclinical rodent models, and is generally difficult to measure directly. Radiation transport simulations integrated in an easy to use application could help researchers improve quality of dosimetry and reporting.Approach. This paper describes the use and dosimetric validation of a newly-developed Monte Carlo (MC) tool, SmART-RAD, to simulate the x-ray field in a range of standard commercial x-ray cabinet irradiators used for preclinical irradiations. Comparisons are made between simulated and experimentally determined dose distributions for a range of configurations to assess the potential use of this tool in determining dose distributions through samples, based on more readily available air-kerma calibration point measurements.Main results. Simulations gave very good dosimetric agreement with measured depth dose distributions in phantoms containing both water and bone equivalent materials. Good spatial and dosimetric agreement between simulated and measured dose distributions was obtained when using beam-shaping shielding.Significance. The MC simulations provided by SmART-RAD provide a useful tool to go from a limited number of dosimetry measurements to detailed 3D dose distributions through a non-homogeneous irradiated sample. This is particularly important when trying to determine the dose distribution in more complex geometries. The use of such a tool can improve reproducibility and dosimetry reporting in preclinical radiobiological research.
Collapse
Affiliation(s)
- Mark A Hill
- MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, ORCRB Roosevelt Drive, Oxford OX3 7DQ, United Kingdom
| | - Nick Staut
- SmART Scientific Solutions BV, Maastricht, The Netherlands
| | - James M Thompson
- MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, ORCRB Roosevelt Drive, Oxford OX3 7DQ, United Kingdom
| | - Frank Verhaegen
- SmART Scientific Solutions BV, Maastricht, The Netherlands
- Department of Radiation Oncology (Maastro), Research Institute for Oncology & Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
| |
Collapse
|
2
|
Bider RC, Sheehan B, Bock N, McNeill FE. The feasibility of K XRF bone lead measurements in mice assessed using 3D-printed phantoms. Biomed Phys Eng Express 2024; 10:035027. [PMID: 38447224 DOI: 10.1088/2057-1976/ad30ca] [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: 08/21/2023] [Accepted: 03/06/2024] [Indexed: 03/08/2024]
Abstract
This article describes the development of a system forin vivomeasurements of lead body burden in mice using109Cd K x-ray fluorescence (XRF). This K XRF system could facilitate early-stage studies on interventions that ameliorate or reverse organ tissue damage from lead poisoning by reducing animal numbers through a cross-sectional study approach. A novel mouse phantom was developed based on a mouse atlas and 3D-printed using PLA plastic with plaster of Paris 'bone' inserts. PLA plastic was found to be a good surrogate for soft tissue in XRF measurements and the phantoms were found to be good models of mice. As expected, lead detection limits varied with mouse size, mouse orientation, and mouse position with respect to the source and detector. The work suggests that detection limits of 10 to 20μg Pb per g bone mineral may be possible for a 2 to 3 hour XRF measurement in a single animal, an adequate limit for some pre-clinical studies. The109Cd K XRF mouse measurement system was also modeled using the Monte Carlo code MCNP. The combination of experiment and modeling found that contrary to expectation, accurate measurements of lead levels in mice required calibration using mouse-specific calibration standards due to the coherent scatter peak normalization failing when small animals are measured. MCNP modeling determined that this was because the coherent scatter signal from soft tissue, which until now has been assumed negligible, becomes significant when compared to the coherent scatter signal in bone in small animals. This may have implications for some human measurements. This work suggests that109Cd K x-ray fluorescence measurements of lead body burden are precise enough to make the system feasible for small animals if appropriately calibrated. Further work to validate the technology's measurement accuracy and performancein vivowill be required.
Collapse
Affiliation(s)
- R C Bider
- McMaster University - Department of Physics and Astronomy, 1280 Main Street West, Hamilton, Ontario, L8S 4K1, Canada
| | - B Sheehan
- McMaster University - Department of Physics and Astronomy, 1280 Main Street West, Hamilton, Ontario, L8S 4K1, Canada
- McMaster University - Radiation Sciences Graduate Program, 1280 Main Street West, Hamilton, Ontario, L8S 4K1, Canada
| | - N Bock
- McMaster University - Department of Psychology, Neuroscience and Behaviour 1280 Main Street West, Hamilton, Ontario, L8S 4K1, Canada
| | - F E McNeill
- McMaster University - Department of Physics and Astronomy, 1280 Main Street West, Hamilton, Ontario, L8S 4K1, Canada
- McMaster University - Radiation Sciences Graduate Program, 1280 Main Street West, Hamilton, Ontario, L8S 4K1, Canada
| |
Collapse
|
3
|
Nguyen H, Schubert KE, Pohling C, Chang E, Yamamoto V, Zeng Y, Nie Y, Van Buskirk S, Schulte RW, Patel CB. Impact of glioma peritumoral edema, tumor size, and tumor location on alternating electric fields (AEF) therapy in realistic 3D rat glioma models: a computational study. Phys Med Biol 2024; 69:085015. [PMID: 38417178 DOI: 10.1088/1361-6560/ad2e6c] [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: 10/20/2023] [Accepted: 02/28/2024] [Indexed: 03/01/2024]
Abstract
Objective.Alternating electric fields (AEF) therapy is a treatment modality for patients with glioblastoma. Tumor characteristics such as size, location, and extent of peritumoral edema may affect the AEF strength and distribution. We evaluated the sensitivity of the AEFs in a realistic 3D rat glioma model with respect to these properties.Approach.The electric properties of the peritumoral edema were varied based on calculated and literature-reported values. Models with different tumor composition, size, and location were created. The resulting AEFs were evaluated in 3D rat glioma models.Main results.In all cases, a pair of 5 mm diameter electrodes induced an average field strength >1 V cm-1. The simulation results showed that a negative relationship between edema conductivity and field strength was found. As the tumor core size was increased, the average field strength increased while the fraction of the shell achieving >1.5 V cm-1decreased. Increasing peritumoral edema thickness decreased the shell's mean field strength. Compared to rostrally/caudally, shifting the tumor location laterally/medially and ventrally (with respect to the electrodes) caused higher deviation in field strength.Significance.This study identifies tumor properties that are key drivers influencing AEF strength and distribution. The findings might be potential preclinical implications.
Collapse
Affiliation(s)
- Ha Nguyen
- Baylor University, Waco, TX, 76706, United States of America
| | | | - Christoph Pohling
- Loma Linda University, Loma Linda, CA, 92350, United States of America
| | - Edwin Chang
- Stanford University, Stanford, CA, 94305, United States of America
| | - Vicky Yamamoto
- University of Southern California-Keck School of Medicine, Los Angeles, CA, 90033, United States of America
| | - Yuping Zeng
- University of Delaware, Newark, DE, 19716, United States of America
| | - Ying Nie
- Loma Linda University, Loma Linda, CA, 92350, United States of America
| | - Samuel Van Buskirk
- University of Texas at San Antonio, San Antonio, TX, 78249, United States of America
| | | | - Chirag B Patel
- The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, United States of America
- The University of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences at Houston, Houston, TX, 77030, United States of America
| |
Collapse
|
4
|
Groen JA, Crezee J, van Laarhoven HWM, Coolen BF, Strijkers GJ, Bijlsma MF, Kok HP. Robust, planning-based targeted locoregional tumour heating in small animals. Phys Med Biol 2024; 69:085017. [PMID: 38471172 DOI: 10.1088/1361-6560/ad3324] [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: 09/25/2023] [Accepted: 03/12/2024] [Indexed: 03/14/2024]
Abstract
Objective.To improve hyperthermia in clinical practice, pre-clinical hyperthermia research is essential to investigate hyperthermia effects and assess novel treatment strategies. Translating pre-clinical hyperthermia findings into clinically viable protocols requires laboratory animal treatment techniques similar to clinical hyperthermia techniques. The ALBA micro8 electromagnetic heating system (Med-logix SRL, Rome, Italy) has recently been developed to provide the targeted locoregional tumour heating currently lacking for pre-clinical research. This study evaluates the heat focusing properties of this device and its ability to induce robust locoregional tumour heating under realistic physiological conditions using simulations.Approach.Simulations were performed using the Plan2Heat treatment planning package (Amsterdam UMC, the Netherlands). First, the specific absorption rate (SAR) focus was characterised using a homogeneous phantom. Hereafter, a digital mouse model was used for the characterisation of heating robustness in a mouse. Device settings were optimised for treatment of a pancreas tumour and tested for varying circumstances. The impact of uncertainties in tissue property and perfusion values was evaluated using polynomial chaos expansion. Treatment quality and robustness were evaluated based on SAR and temperature distributions.Main results.The SAR distributions within the phantom are well-focused and can be adjusted to target any specific location. The focus size (full-width half-maximum) is a spheroid with diameters 9 mm (radially) and 20 mm (axially). The mouse model simulations show strong robustness against respiratory motion and intestine and stomach filling (∆T90≤0.14°C).Mouse positioning errors in the cranial-caudal direction lead to∆T90≤0.23°C. Uncertainties in tissue property and perfusion values were found to impact the treatment plan up to 0.56 °C (SD), with a variation onT90of 0.32 °C (1 SD).Significance.Our work shows that the pre-clinical phased-array system can provide adequate and robust locoregional heating of deep-seated target regions in mice. Using our software, robust treatment plans can be generated for pre-clinical hyperthermia research.
Collapse
Affiliation(s)
- Jort A Groen
- Amsterdam UMC location University of Amsterdam, Radiation Oncology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, The Netherlands
| | - Johannes Crezee
- Amsterdam UMC location University of Amsterdam, Radiation Oncology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, The Netherlands
| | - Hanneke W M van Laarhoven
- Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, The Netherlands
- Amsterdam UMC location University of Amsterdam, Department of Medical Oncology, Amsterdam, The Netherlands
| | - Bram F Coolen
- Amsterdam UMC location University of Amsterdam, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Amsterdam UMC location University of Amsterdam, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Maarten F Bijlsma
- Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, The Netherlands
- Amsterdam UMC location University of Amsterdam, Center for Experimental and Molecular Medicine, Laboratory for Experimental Oncology and Radiobiology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and biomarkers, Amsterdam, the Netherlands
- Oncode Institute, Amsterdam, The Netherlands
| | - H Petra Kok
- Amsterdam UMC location University of Amsterdam, Radiation Oncology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, The Netherlands
| |
Collapse
|
5
|
Evin M, Koumeir C, Bongrand A, Delpon G, Haddad F, Mouchard Q, Potiron V, Saade G, Servagent N, Villoing D, Métivier V, Chiavassa S. Methodology for small animals targeted irradiations at conventional and ultra-high dose rates 65 MeV proton beam. Phys Med 2024; 120:103332. [PMID: 38518627 DOI: 10.1016/j.ejmp.2024.103332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 02/20/2024] [Accepted: 03/11/2024] [Indexed: 03/24/2024] Open
Abstract
As part of translational research projects, mice may be irradiated on radiobiology platforms such as the one at the ARRONAX cyclotron. Generally, these platforms do not feature an integrated imaging system. Moreover, in the context of ultra-high dose-rate radiotherapy (FLASH-RT), treatment planning should consider potential changes in the beam characteristics and internal movements in the animal. A patient-like set-up and methodology has been implemented to ensure target coverage during conformal irradiations of the brain, lungs and intestines. In addition, respiratory cycle amplitudes were quantified by fluoroscopic acquisitions on a mouse, to ensure organ coverage and to assess the impact of respiration during FLASH-RT using the 4D digital phantom MOBY. Furthermore, beam incidence direction was studied from mice µCBCT and Monte Carlo simulations. Finally,in vivodosimetry with dose-rate independent radiochromic films (OC-1) and their LET dependency were investigated. The immobilization system ensures that the animal is held in a safe and suitable position. The geometrical evaluation of organ coverage, after the addition of the margins around the organs, was satisfactory. Moreover, no measured differences were found between CONV and FLASH beams enabling a single model of the beamline for all planning studies. Finally, the LET-dependency of the OC-1 film was determined and experimentally verified with phantoms, as well as the feasibility of using these filmsin vivoto validate the targeting. The methodology developed ensures accurate and reproducible preclinical irradiations in CONV and FLASH-RT without in-room image guidance in terms of positioning, dose calculation andin vivodosimetry.
Collapse
Affiliation(s)
- Manon Evin
- Nantes Université, IMT Atlantique, CNRS/IN2P3, SUBATECH, F-44000 Nantes, France.
| | - Charbel Koumeir
- Nantes Université, IMT Atlantique, CNRS/IN2P3, SUBATECH, F-44000 Nantes, France; GIP ARRONAX, Saint-Herblain, France
| | - Arthur Bongrand
- GIP ARRONAX, Saint-Herblain, France; Institut de Cancérologie de l'Ouest, site de Saint-Herblain, France
| | - Gregory Delpon
- Nantes Université, IMT Atlantique, CNRS/IN2P3, SUBATECH, F-44000 Nantes, France; Institut de Cancérologie de l'Ouest, site de Saint-Herblain, France
| | - Ferid Haddad
- Nantes Université, IMT Atlantique, CNRS/IN2P3, SUBATECH, F-44000 Nantes, France; GIP ARRONAX, Saint-Herblain, France
| | - Quentin Mouchard
- Nantes Université, IMT Atlantique, CNRS/IN2P3, SUBATECH, F-44000 Nantes, France
| | - Vincent Potiron
- Institut de Cancérologie de l'Ouest, site de Saint-Herblain, France; Nantes Université, CNRS, US2B, UMR 6286, F-44000 Nantes, France
| | - Gaëlle Saade
- Nantes Université, CNRS, US2B, UMR 6286, F-44000 Nantes, France
| | - Noël Servagent
- Nantes Université, IMT Atlantique, CNRS/IN2P3, SUBATECH, F-44000 Nantes, France
| | - Daphnée Villoing
- Institut de Cancérologie de l'Ouest, site de Saint-Herblain, France
| | - Vincent Métivier
- Nantes Université, IMT Atlantique, CNRS/IN2P3, SUBATECH, F-44000 Nantes, France
| | - Sophie Chiavassa
- Nantes Université, IMT Atlantique, CNRS/IN2P3, SUBATECH, F-44000 Nantes, France; Institut de Cancérologie de l'Ouest, site de Saint-Herblain, France
| |
Collapse
|
6
|
Nguyen H, Schubert KE, Chang E, Nie Y, Pohling C, Van Buskirk S, Yamamoto V, Zeng Y, Schulte RW, Patel CB. Electric field distributions in realistic 3D rat head models during alternating electric field (AEF) therapy: a computational study. Phys Med Biol 2023; 68:205015. [PMID: 37703902 DOI: 10.1088/1361-6560/acf98d] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 09/13/2023] [Indexed: 09/15/2023]
Abstract
Objective.Application of alternating electrical fields (AEFs) in the kHz range is an established treatment modality for primary and recurrent glioblastoma. Preclinical studies would enable innovations in treatment monitoring and efficacy, which could then be translated to benefit patients. We present a practical translational process converting image-based data into 3D rat head models for AEF simulations and study its sensitivity to parameter choices.Approach.Five rat head models composed of up to 7 different tissue types were created, and relative permittivity and conductivity of individual tissues obtained from the literature were assigned. Finite element analysis was used to model the AEF strength and distribution in the models with different combinations of head tissues, a virtual tumor, and an electrode pair.Main results.The simulations allowed for a sensitivity analysis of the AEF distribution with respect to different tissue combinations and tissue parameter values.Significance.For a single pair of 5 mm diameter electrodes, an average AEF strength inside the tumor exceeded 1.5 V cm-1, expected to be sufficient for a relevant therapeutic outcome. This study illustrates a robust and flexible approach for simulating AEF in different tissue types, suitable for preclinical studies in rodents and translatable to clinical use.
Collapse
Affiliation(s)
- Ha Nguyen
- Baylor University, Waco, TX 76706, United States of America
| | | | - Edwin Chang
- Stanford University, Stanford, CA 94305, United States of America
| | - Ying Nie
- Loma Linda University, Loma Linda, CA 92350, United States of America
| | - Christoph Pohling
- Loma Linda University, Loma Linda, CA 92350, United States of America
| | - Samuel Van Buskirk
- University of Texas at San Antonio, San Antonio, TX 78249, United States of America
| | - Vicky Yamamoto
- University of Southern California-Keck School of Medicine, Los Angeles, CA 90033, United States of America
| | - Yuping Zeng
- University of Delaware, Newark, DE 19716, United States of America
| | | | - Chirag B Patel
- University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States of America
- The University of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences at Houston, Houston, TX 77030, United States of America
| |
Collapse
|
7
|
Ramos López D, Pugliese GMI, Iaselli G, Amoroso N, Gong C, Pascali V, Altieri S, Protti N. Study of Alternative Imaging Methods for In Vivo Boron Neutron Capture Therapy. Cancers (Basel) 2023; 15:3582. [PMID: 37509243 PMCID: PMC10377696 DOI: 10.3390/cancers15143582] [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: 05/23/2023] [Revised: 07/01/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
Boron Neutron Capture Therapy (BNCT) is an innovative and highly selective treatment against cancer. Nowadays, in vivo boron dosimetry is an important method to carry out such therapy in clinical environments. In this work, different imaging methods were tested for dosimetry and tumor monitoring in BNCT based on a Compton camera detector. A dedicated dataset was generated through Monte Carlo tools to study the imaging capabilities. We first applied the Maximum Likelihood Expectation Maximization (MLEM) iterative method to study dosimetry tomography. As well, two methods based on morphological filtering and deep learning techniques with Convolutional Neural Networks (CNN), respectively, were studied for tumor monitoring. Furthermore, clinical aspects such as the dependence on the boron concentration ratio in image reconstruction and the stretching effect along the detector position axis were analyzed. A simulated spherical gamma source was studied in several conditions (different detector distances and boron concentration ratios) using MLEM. This approach proved the possibility of monitoring the boron dose. Tumor monitoring using the CNN method shows promising results that could be enhanced by increasing the training dataset.
Collapse
Affiliation(s)
- Dayron Ramos López
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, 70125 Bari, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy
| | - Gabriella Maria Incoronata Pugliese
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, 70125 Bari, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy
| | - Giuseppe Iaselli
- Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, 70125 Bari, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy
| | - Nicola Amoroso
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125 Bari, Italy
| | - Chunhui Gong
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
- Istituto Nazionale di Fisica Nucleare, Sezione di Pavia, 27100 Pavia, Italy
| | - Valeria Pascali
- Istituto Nazionale di Fisica Nucleare, Sezione di Pavia, 27100 Pavia, Italy
- Dipartimento di Fisica, Università degli Studi di Pavia, 27100 Pavia, Italy
| | - Saverio Altieri
- Istituto Nazionale di Fisica Nucleare, Sezione di Pavia, 27100 Pavia, Italy
- Dipartimento di Fisica, Università degli Studi di Pavia, 27100 Pavia, Italy
| | - Nicoletta Protti
- Istituto Nazionale di Fisica Nucleare, Sezione di Pavia, 27100 Pavia, Italy
- Dipartimento di Fisica, Università degli Studi di Pavia, 27100 Pavia, Italy
| |
Collapse
|
8
|
Métivier C, Le Saëc P, Gaschet J, Chauvet C, Marionneau-Lambot S, Hofgaard PO, Bogen B, Pineau J, Le Bris N, Tripier R, Alliot C, Haddad F, Chérel M, Chouin N, Faivre-Chauvet A, Rbah-Vidal L. Preclinical Evaluation of a 64Cu-Based Theranostic Approach in a Murine Model of Multiple Myeloma. Pharmaceutics 2023; 15:1817. [PMID: 37514004 PMCID: PMC10385603 DOI: 10.3390/pharmaceutics15071817] [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: 05/05/2023] [Revised: 06/16/2023] [Accepted: 06/16/2023] [Indexed: 07/30/2023] Open
Abstract
Although the concept of theranostics is neither new nor exclusive to nuclear medicine, it is a particularly promising approach for the future of nuclear oncology. This approach is based on the use of molecules targeting specific biomarkers in the tumour or its microenvironment, associated with optimal radionuclides which, depending on their emission properties, allow the combination of diagnosis by molecular imaging and targeted radionuclide therapy (TRT). Copper-64 has suitable decay properties (both β+ and β- decays) for PET imaging and potentially for TRT, making it both an imaging and therapy agent. We developed and evaluated a theranostic approach using a copper-64 radiolabelled anti-CD138 antibody, [64Cu]Cu-TE1PA-9E7.4 in a MOPC315.BM mouse model of multiple myeloma. PET imaging using [64Cu]Cu-TE1PA-9E7.4 allows for high-resolution PET images. Dosimetric estimation from ex vivo biodistribution data revealed acceptable delivered doses to healthy organs and tissues, and a very encouraging tumour absorbed dose for TRT applications. Therapeutic efficacy resulting in delayed tumour growth and increased survival without inducing major or irreversible toxicity has been observed with 2 doses of 35 MBq administered at a 2-week interval. Repeated injections of [64Cu]Cu-TE1PA-9E7.4 are safe and can be effective for TRT application in this syngeneic preclinical model of MM.
Collapse
Affiliation(s)
- Cassandra Métivier
- Nantes Université, Inserm, CNRS, Université d'Angers, CRCI2NA, 44007 Nantes, France
| | - Patricia Le Saëc
- Nantes Université, Inserm, CNRS, Université d'Angers, CRCI2NA, 44007 Nantes, France
| | - Joëlle Gaschet
- Nantes Université, Inserm, CNRS, Université d'Angers, CRCI2NA, 44007 Nantes, France
| | - Catherine Chauvet
- Nantes Université, Inserm, CNRS, Université d'Angers, CRCI2NA, 44007 Nantes, France
| | | | - Peter O Hofgaard
- Department of Immunology, Oslo University Hospital, 04024 Oslo, Norway
| | - Bjarne Bogen
- Department of Immunology, Oslo University Hospital, 04024 Oslo, Norway
| | - Julie Pineau
- Univ. Brest, UMR CNRS 6521 CEMCA, 6 Avenue Victor le Gorgeu, 29200 Brest, France
| | - Nathalie Le Bris
- Univ. Brest, UMR CNRS 6521 CEMCA, 6 Avenue Victor le Gorgeu, 29200 Brest, France
| | - Raphaël Tripier
- Univ. Brest, UMR CNRS 6521 CEMCA, 6 Avenue Victor le Gorgeu, 29200 Brest, France
| | - Cyrille Alliot
- Nantes Université, Inserm, CNRS, Université d'Angers, CRCI2NA, 44007 Nantes, France
- GIP ARRONAX, 44800 Saint-Herblain, France
| | - Férid Haddad
- IMT Atlantique, Nantes Université, Subatech, 44307 Nantes, France
- GIP ARRONAX, 44800 Saint-Herblain, France
| | - Michel Chérel
- Nantes Université, Inserm, CNRS, Université d'Angers, CRCI2NA, 44007 Nantes, France
- Nuclear Medicine Department, ICO-René Gauducheau Cancer Center, 44800 Saint-Herblain, France
| | - Nicolas Chouin
- Nantes Université, Inserm, CNRS, Université d'Angers, Oniris, CRCI2NA, 44007 Nantes, France
| | - Alain Faivre-Chauvet
- Nantes Université, Inserm, CNRS, Université d'Angers, CRCI2NA, CHU Nantes, 44007 Nantes, France
| | - Latifa Rbah-Vidal
- Nantes Université, Inserm, CNRS, Université d'Angers, CRCI2NA, 44007 Nantes, France
| |
Collapse
|
9
|
He Y, Zeng L, Xu Q, Wang Z, Yu H, Shen Z, Yang Z, Zhou R. Spectral CT reconstruction via low-rank representation and structure preserving regularization. Phys Med Biol 2023; 68. [PMID: 36595335 DOI: 10.1088/1361-6560/acabf9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022]
Abstract
Objective:With the development of computed tomography (CT) imaging technology, it is possible to acquire multi-energy data by spectral CT. Being different from conventional CT, the X-ray energy spectrum of spectral CT is cut into several narrow bins which leads to the result that only a part of photon can be collected in each individual energy channel.This can severely degrade the image qualities. To address this problem, we propose a spectral CT reconstruction algorithm based on low-rank representation and structure preserving regularization in this paper.Approach:To make full use of the prior knowledge about both the inter-channel correlation and the sparsity in gradient domain of inner-channel data, this paper combines a low-rank correlation descriptor with a structure extraction operator as priori regularization terms for spectral CT reconstruction. Furthermore, a split-Bregman based iterative algorithm is developed to solve the reconstruction model. Finally, we propose a multi-channel adaptive parameters generation strategy according to CT values of each individual energy channel.Main results: Experimental results on numerical simulations and real mouse data indicate that the proposed algorithm achieves higher accuracy on both reconstruction and material decomposition than the methods based on simultaneous algebraic reconstruction technique (SART), total variation minimization (TVM), total variation with low-rank (LRTV), and spatial-spectral cube matching frame (SSCMF). Compared with SART, our algorithm improves the feature similarity (FSIM) by 40.4% on average for numerical simulation reconstruction, whereas TVM, LRTV, and SSCMF correspond to 26.1%, 28.2%, and 29.5%, respectively.Significance: We outline a multi-channel reconstruction algorithm tailored for spectral CT. The qualitative and quantitative comparisons present a significant improvement of image quality, indicating its promising potential in spectral CT imaging.
Collapse
Affiliation(s)
- Yuanwei He
- College of Mathematics and Statistics, Chongqing University, Chongqing 401331, People's Republic of China.,Engineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing 400044, People's Republic of China
| | - Li Zeng
- College of Mathematics and Statistics, Chongqing University, Chongqing 401331, People's Republic of China.,Engineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing 400044, People's Republic of China
| | - Qiong Xu
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, People's Republic of China.,Jinan Laboratory of Applied Nuclear Science, Jinan 250131, People's Republic of China
| | - Zhe Wang
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, People's Republic of China.,Jinan Laboratory of Applied Nuclear Science, Jinan 250131, People's Republic of China
| | - Haijun Yu
- Engineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing 400044, People's Republic of China.,Key Lab of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing 400044, People's Republic of China
| | - Zhaoqiang Shen
- College of Mathematics and Statistics, Chongqing University, Chongqing 401331, People's Republic of China.,Engineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing 400044, People's Republic of China
| | - Zhaojun Yang
- College of Mathematics and Statistics, Chongqing University, Chongqing 401331, People's Republic of China.,Engineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing 400044, People's Republic of China
| | - Rifeng Zhou
- Engineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing 400044, People's Republic of China.,Key Lab of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing 400044, People's Republic of China.,State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, People's Republic of China
| |
Collapse
|
10
|
Sardella D, Kristensen AM, Bordoni L, Kidmose H, Shahrokhtash A, Sutherland DS, Frische S, Schiessl IM. Serial intravital 2-photon microscopy and analysis of the kidney using upright microscopes. Front Physiol 2023; 14:1176409. [PMID: 37168225 PMCID: PMC10164931 DOI: 10.3389/fphys.2023.1176409] [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: 02/28/2023] [Accepted: 04/03/2023] [Indexed: 05/13/2023] Open
Abstract
Serial intravital 2-photon microscopy of the kidney and other abdominal organs is a powerful technique to assess tissue function and structure simultaneously and over time. Thus, serial intravital microscopy can capture dynamic tissue changes during health and disease and holds great potential to characterize (patho-) physiological processes with subcellular resolution. However, successful image acquisition and analysis require significant expertise and impose multiple potential challenges. Abdominal organs are rhythmically displaced by breathing movements which hamper high-resolution imaging. Traditionally, kidney intravital imaging is performed on inverted microscopes where breathing movements are partly compensated by the weight of the animal pressing down. Here, we present a custom and easy-to-implement setup for intravital imaging of the kidney and other abdominal organs on upright microscopes. Furthermore, we provide image processing protocols and a new plugin for the free image analysis software FIJI to process multichannel fluorescence microscopy data. The proposed image processing pipelines cover multiple image denoising algorithms, sample drift correction using 2D registration, and alignment of serial imaging data collected over several weeks using landmark-based 3D registration. The provided tools aim to lower the barrier of entry to intravital microscopy of the kidney and are readily applicable by biomedical practitioners.
Collapse
Affiliation(s)
- Donato Sardella
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- *Correspondence: Ina Maria Schiessl, ; Donato Sardella,
| | | | - Luca Bordoni
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Hanne Kidmose
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Ali Shahrokhtash
- Interdisciplinary Nanoscience Center, Aarhus University, Aarhus, Denmark
| | | | | | - Ina Maria Schiessl
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- *Correspondence: Ina Maria Schiessl, ; Donato Sardella,
| |
Collapse
|
11
|
Zvolský M, Schaar M, Seeger S, Rakers S, Rafecas M. Development of a digital zebrafish phantom and its application to dedicated small-fish PET. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac71ee] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 05/20/2022] [Indexed: 11/11/2022]
Abstract
Abstract
Objective. We are developing a small-fish positron emission tomography (PET) scanner dedicated to small aquatic animals relevant for biomedical and biological research, e.g. zebrafish. We plan to use Monte Carlo simulations to optimize its configuration and the required water-filled imaging chambers. Our objectives were: (1) to create a digital 3D zebrafish phantom using conventional micro-CT, (2) include the phantom into a simulated PET environment based on the framework GATE, and (3) investigate the effects of the water environment on the reconstructed images. Approach. To create the phantom, we performed ex vivo measurements of zebrafish specimen using a tabletop micro-CT and compared three methods to fixate the specimen. From segmented micro-CT images we created digital emission and transmission phantoms which were incorporated in GATE via tessellated volumes. Two chamber sizes were considered. For reference, a simulation with the zebrafish in air was implemented. The simulated data were reconstructed using CASToR. For attenuation correction, we used the exact attenuation information or a uniform distribution (only water). Several realizations of each scenario were performed; the reconstructed images were quantitatively evaluated. Main results. Fixation in formalin led to the best soft-tissue contrast at the cost of some specimen deformation. After attenuation correction, no significant differences were found between the reconstructed images. The PET images reflected well the higher uptake simulated in the brain and heart, despite their small size and surrounding background activity; the swim bladder (no activity) was clearly identified. The simplified attenuation map, consisting only of water, slightly worsened the images. Significance. A conventional micro-CT can provide sufficient image quality to generate numerical phantoms of small fish without contrast media. Such phantoms are useful to evaluate in-silico small aquatic animal imaging concepts and develop imaging protocols. Our results support the feasibility of zebrafish PET with an aqueous environment.
Collapse
|
12
|
van Dijk RHW, Staut N, Wolfs CJA, Verhaegen F. A novel multichannel deep learning model for fast denoising of Monte Carlo dose calculations: preclinical applications. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac8390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 07/22/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Objective. In preclinical radiotherapy with kilovolt (kV) x-ray beams, accurate treatment planning is needed to improve the translation potential to clinical trials. Monte Carlo based radiation transport simulations are the gold standard to calculate the absorbed dose distribution in external beam radiotherapy. However, these simulations are notorious for their long computation time, causing a bottleneck in the workflow. Previous studies have used deep learning models to speed up these simulations for clinical megavolt (MV) beams. For kV beams, dose distributions are more affected by tissue type than for MV beams, leading to steep dose gradients. This study aims to speed up preclinical kV dose simulations by proposing a novel deep learning pipeline. Approach. A deep learning model is proposed that denoises low precision (∼106 simulated particles) dose distributions to produce high precision (109 simulated particles) dose distributions. To effectively denoise the steep dose gradients in preclinical kV dose distributions, the model uses the novel approach to use the low precision Monte Carlo dose calculation as well as the Monte Carlo uncertainty (MCU) map and the mass density map as additional input channels. The model was trained on a large synthetic dataset and tested on a real dataset with a different data distribution. To keep model inference time to a minimum, a novel method for inference optimization was developed as well. Main results. The proposed model provides dose distributions which achieve a median gamma pass rate (3%/0.3 mm) of 98% with a lower bound of 95% when compared to the high precision Monte Carlo dose distributions from the test set, which represents a different dataset distribution than the training set. Using the proposed model together with the novel inference optimization method, the total computation time was reduced from approximately 45 min to less than six seconds on average. Significance. This study presents the first model that can denoise preclinical kV instead of clinical MV Monte Carlo dose distributions. This was achieved by using the MCU and mass density maps as additional model inputs. Additionally, this study shows that training such a model on a synthetic dataset is not only a viable option, but even increases the generalization of the model compared to training on real data due to the sheer size and variety of the synthetic dataset. The application of this model will enable speeding up treatment plan optimization in the preclinical workflow.
Collapse
|
13
|
Dose Rate Assessment Exercises with Stylized Phantom of Neon Flying Squid from Northwest Pacific. JOURNAL OF MARINE SCIENCE AND ENGINEERING 2022. [DOI: 10.3390/jmse10060782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Radiation protection for non-human marine organisms still faces many challenges. To establish a more realistic radiation dosimetry model of cephalopods, this study developed a stylized phantom of neon flying squid (Ommastrephesbartramii) containing ten organs and tissues based on magnetic resonance imaging (MRI) technology. The internal and external dose conversion coefficients for eight radionuclides (134Cs, 137Cs, 131I, 110mAg, 60Co, 54Mn, 65Zn, 95Zr) of each organ/tissue were determined with Monte Carlo simulation using the Geant4 toolkit. Furthermore, with the reported coastal seawater radioactivity levels at the coastal area of Fukushima Daiichi Nuclear Power Plant after the accident in 2011 as the source term, the radiological dose rate for O. bartramii was evaluated with the stylized phantom developed in this study and with the conventional whole-organism ellipsoidal model in the ERICA Assessment Tool. Both results showed that the dose rate for O. bartramii derived from the FDNPP accident releases exceeded the generic no-effects screening benchmark level (10 μGy h−1).
Collapse
|
14
|
Cicone F, Viertl D, Denoël T, Stabin MG, Prior JO, Gnesin S. Comparison of absorbed dose extrapolation methods for mouse-to-human translation of radiolabelled macromolecules. EJNMMI Res 2022; 12:21. [PMID: 35403982 PMCID: PMC9001797 DOI: 10.1186/s13550-022-00893-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 03/26/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Extrapolation of human absorbed doses (ADs) from biodistribution experiments on laboratory animals is used to predict the efficacy and toxicity profiles of new radiopharmaceuticals. Comparative studies between available animal-to-human dosimetry extrapolation methods are missing. We compared five computational methods for mice-to-human AD extrapolations, using two different radiopharmaceuticals, namely [111In]CHX-DTPA-scFv78-Fc and [68Ga]NODAGA-RGDyK. Human organ-specific time-integrated activity coefficients (TIACs) were derived from biodistribution studies previously conducted in our centre. The five computational methods adopted are based on simple direct application of mice TIACs to human organs (M1), relative mass scaling (M2), metabolic time scaling (M3), combined mass and time scaling (M4), and organ-specific allometric scaling (M5), respectively. For [68Ga]NODAGA-RGDyK, these methods for mice-to-human extrapolations were tested against the ADs obtained on patients, previously published by our group. Lastly, an average [68Ga]NODAGA-RGDyK-specific allometric parameter αnew was calculated from the organ-specific biological half-lives in mouse and humans and retrospectively applied to M3 and M4 to assess differences in human AD predictions with the α = 0.25 recommended by previous studies. RESULTS For both radiopharmaceuticals, the five extrapolation methods showed significantly different AD results (p < 0.0001). In general, organ ADs obtained with M3 were higher than those obtained with the other methods. For [68Ga]NODAGA-RGDyK, no significant differences were found between ADs calculated with M3 and those obtained directly on human subjects (H) (p = 0.99; average M3/H AD ratio = 1.03). All other methods for dose extrapolations resulted in ADs significantly different from those calculated directly on humans (all p ≤ 0.0001). Organ-specific allometric parameters calculated using combined experimental [68Ga]NODAGA-RGDyK mice and human biodistribution data varied significantly. ADs calculated with M3 and M4 after the application of αnew = 0.17 were significantly different from those obtained by the application of α = 0.25 (both p < 0.001). CONCLUSIONS Available methods for mouse-to-human dosimetry extrapolations provided significantly different results in two different experimental models. For [68Ga]NODAGA-RGDyK, the best approximation of human dosimetry was shown by M3, applying a metabolic scaling to the mouse organ TIACs. The accuracy of more refined extrapolation algorithms adopting model-specific metabolic scaling parameters should be further investigated.
Collapse
Affiliation(s)
- Francesco Cicone
- Department of Experimental and Clinical Medicine, and Neuroscience Research Centre, PET/MR Unit, “Magna Graecia” University of Catanzaro, Catanzaro, Italy
- Nuclear Medicine Unit, University Hospital “Mater Domini”, Catanzaro, Italy
- University of Lausanne, Lausanne, Switzerland
| | - David Viertl
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, 1011 Lausanne, Switzerland
| | - Thibaut Denoël
- Department of Experimental and Clinical Medicine, and Neuroscience Research Centre, PET/MR Unit, “Magna Graecia” University of Catanzaro, Catanzaro, Italy
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, 1011 Lausanne, Switzerland
| | | | - John O. Prior
- University of Lausanne, Lausanne, Switzerland
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, 1011 Lausanne, Switzerland
| | - Silvano Gnesin
- University of Lausanne, Lausanne, Switzerland
- Institute of Radiation Physics, Lausanne University Hospital, Lausanne, Switzerland
| |
Collapse
|
15
|
Therapeutic efficacy of heterogeneously distributed radiolabelled peptides: Influence of radionuclide choice. Phys Med 2022; 96:90-100. [DOI: 10.1016/j.ejmp.2022.02.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 02/10/2022] [Accepted: 02/21/2022] [Indexed: 12/21/2022] Open
|
16
|
Sarna NS, Marrero‐Morales L, DeGroff R, Rivera‐Rodriguez A, Liu S, Chiu‐Lam A, Good HJ, Rinaldi‐Ramos CM. An anatomically correct
3D
printed mouse phantom for magnetic particle imaging studies. Bioeng Transl Med 2022; 7:e10299. [PMID: 36176627 PMCID: PMC9472006 DOI: 10.1002/btm2.10299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 02/10/2022] [Accepted: 02/15/2022] [Indexed: 11/11/2022] Open
Abstract
We report anatomically correct 3D‐printed mouse phantoms that can be used to plan experiments and evaluate analysis protocols for magnetic particle imaging (MPI) studies. The 3D‐printed phantoms were based on the Digimouse 3D whole body mouse atlas and incorporate cavities representative of a liver, brain tumor, and orthotopic breast cancer tumor placed in anatomically correct locations, allowing evaluation of the effect of precise doses of MPI tracer. To illustrate their use, a constant tracer iron mass was present in the liver for the breast (200 μgFe) and brain tumor (10 μgFe) model, respectively, while a series of decreasing tracer iron mass was placed in the tumor region. MPI scans were acquired in 2D and 3D high sensitivity and high sensitivity/high resolution (HSHR) modes using a MOMENTUM imager. A thresholding algorithm was used to define regions of interest (ROIs) in the scans and the tracer mass in the liver and tumors was calculated by comparison of the signal in their respective ROI against that of known mass fiducials that were included in each scan. The results demonstrate that this approach to image analysis provides accurate estimates of tracer mass. Additionally, the results show how the limit of detection in MPI is sensitive to the details of tracer distribution in the subject, as we found that a greater tracer mass in the liver cavity resulted in poorer sensitivity in tumor regions. These experiments illustrate the utility of the reported 3D‐printed anatomically correct mouse phantoms in evaluating methods to analyze MPI scans and plan in vivo experiments.
Collapse
Affiliation(s)
- Nicole S. Sarna
- J. Crayton Pruitt Family Department of Biomedical Engineering University of Florida
| | | | - Ryan DeGroff
- J. Crayton Pruitt Family Department of Biomedical Engineering University of Florida
| | | | - Sitong Liu
- Department of Chemical Engineering University of Florida
| | | | - Hayden J. Good
- Department of Chemical Engineering University of Florida
| | - Carlos M. Rinaldi‐Ramos
- J. Crayton Pruitt Family Department of Biomedical Engineering University of Florida
- Department of Chemical Engineering University of Florida
| |
Collapse
|
17
|
Malimban J, Lathouwers D, Qian H, Verhaegen F, Wiedemann J, Brandenburg S, Staring M. Deep learning-based segmentation of the thorax in mouse micro-CT scans. Sci Rep 2022; 12:1822. [PMID: 35110676 PMCID: PMC8810936 DOI: 10.1038/s41598-022-05868-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 01/18/2022] [Indexed: 12/18/2022] Open
Abstract
For image-guided small animal irradiations, the whole workflow of imaging, organ contouring, irradiation planning, and delivery is typically performed in a single session requiring continuous administration of anaesthetic agents. Automating contouring leads to a faster workflow, which limits exposure to anaesthesia and thereby, reducing its impact on experimental results and on animal wellbeing. Here, we trained the 2D and 3D U-Net architectures of no-new-Net (nnU-Net) for autocontouring of the thorax in mouse micro-CT images. We trained the models only on native CTs and evaluated their performance using an independent testing dataset (i.e., native CTs not included in the training and validation). Unlike previous studies, we also tested the model performance on an external dataset (i.e., contrast-enhanced CTs) to see how well they predict on CTs completely different from what they were trained on. We also assessed the interobserver variability using the generalized conformity index ([Formula: see text]) among three observers, providing a stronger human baseline for evaluating automated contours than previous studies. Lastly, we showed the benefit on the contouring time compared to manual contouring. The results show that 3D models of nnU-Net achieve superior segmentation accuracy and are more robust to unseen data than 2D models. For all target organs, the mean surface distance (MSD) and the Hausdorff distance (95p HD) of the best performing model for this task (nnU-Net 3d_fullres) are within 0.16 mm and 0.60 mm, respectively. These values are below the minimum required contouring accuracy of 1 mm for small animal irradiations, and improve significantly upon state-of-the-art 2D U-Net-based AIMOS method. Moreover, the conformity indices of the 3d_fullres model also compare favourably to the interobserver variability for all target organs, whereas the 2D models perform poorly in this regard. Importantly, the 3d_fullres model offers 98% reduction in contouring time.
Collapse
Affiliation(s)
- Justin Malimban
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, The Netherlands.
| | - Danny Lathouwers
- Department of Radiation Science and Technology, Faculty of Applied Sciences, Delft University of Technology, 2629 JB, Delft, The Netherlands
| | - Haibin Qian
- Department of Medical Biology, Amsterdam University Medical Centers (Location AMC) and Cancer Center Amsterdam, 1105 AZ, Amsterdam, The Netherlands
| | - Frank Verhaegen
- Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Center, 6229 ER, Maastricht, The Netherlands
| | - Julia Wiedemann
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, The Netherlands
- Department of Biomedical Sciences of Cells and Systems-Section Molecular Cell Biology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, The Netherlands
| | - Sytze Brandenburg
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, The Netherlands
| | - Marius Staring
- Department of Radiology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| |
Collapse
|
18
|
Amato E, Gnesin S, Cicone F, Auditore L. Fundamentals of internal radiation dosimetry. Nucl Med Mol Imaging 2022. [DOI: 10.1016/b978-0-12-822960-6.00142-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
|
19
|
Entezam A, Fielding A, Moi D, Bradley D, Ratnayake G, Sim L, Kralik C, Fontanarosa D. Investigation of scattered dose in a mouse phantom model for pre-clinical dosimetry studies. Radiat Phys Chem Oxf Engl 1993 2021. [DOI: 10.1016/j.radphyschem.2021.109691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
|
20
|
Payne JA, Barnes RA, Downey AX, Freeman DA, Johnson LR, Rodriguez RA, Sloan MA, Valdez CM, Voorhees WB, Whitmore JN. Temperature Dynamics in Rat Brains Exposed to Near-Field Waveguide Outputs at 2.8 GHz. Bioelectromagnetics 2021; 43:14-24. [PMID: 34719046 DOI: 10.1002/bem.22377] [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: 04/12/2021] [Revised: 07/29/2021] [Accepted: 10/10/2021] [Indexed: 01/07/2023]
Abstract
Biological effects in the microwave band of the radiofrequency (RF) spectrum are thermally mediated. For acute high-power microwave exposures, these effects will depend on transient time-temperature histories within the tissue. In this article, we summarize the transient temperature response of rats exposed to RF energy emanating from an open-ended rectangular waveguide. These exposures produced specific absorption rates of approximately 36 and 203 W/kg in the whole body and brain, respectively. We then use the experimentally measured thermal data to infer the baseline perfusion rate in the brain and modify a custom thermal modeling tool based upon these findings. Finally, we compare multi-physics simulations of rat brain temperature against empirical measurements in both live and euthanized subjects and find close agreement between model and experimentation. This research revealed that baseline brain perfusion rates in rat subjects could be larger than previously assumed in the RF thermal modeling literature, and plays a significant role in the transient thermal response to high-power microwave exposures. © 2021 Bioelectromagnetics Society.
Collapse
Affiliation(s)
- Jason A Payne
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Bioeffects Division, JBSA Fort Sam Houston, TX
| | - Ronald A Barnes
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Bioeffects Division, JBSA Fort Sam Houston, TX
| | | | - David A Freeman
- General Dynamics Information Technology, JBSA Fort Sam Houston, TX
| | - Leland R Johnson
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Bioeffects Division, JBSA Fort Sam Houston, TX
| | | | - Mark A Sloan
- General Dynamics Information Technology, JBSA Fort Sam Houston, TX
| | - Christopher M Valdez
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Bioeffects Division, JBSA Fort Sam Houston, TX
| | - William B Voorhees
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Bioeffects Division, JBSA Fort Sam Houston, TX
| | - Jeffrey N Whitmore
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Bioeffects Division, JBSA Fort Sam Houston, TX
| |
Collapse
|
21
|
An in-silico method to predict and quantify the effect of gold nanoparticles in X-ray imaging. Phys Med 2021; 89:160-168. [PMID: 34380106 DOI: 10.1016/j.ejmp.2021.07.033] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Revised: 07/21/2021] [Accepted: 07/28/2021] [Indexed: 12/18/2022] Open
Abstract
PURPOSE Over the last few years studies are conducted, highlighting the feasibility of Gold Nanoparticles (GNPs) to be used in clinical CT imaging and as an efficient contrast agent for cancer research. After ensuring that GNPs formulations are appropriate for in vivo or clinical use, the next step is to determine the parameters for an X-ray system's optimal contrast for applications and to extract quantitative information. There is currently a gap and need to exploit new X-ray imaging protocols and processing algorithms, through specific models avoiding trial-and-error procedures and provide an imaging prognosis tool. Such a model can be used to confirm the accumulation of GNPs in target organs before radiotherapy treatments with a system easily available in hospitals, as low energy X-rays. METHODS In this study a complete, easy-to-use, simulation platform is designed and built, where simple parameters, as the X-ray's specifications and experimentally defined biodistributions of specific GNPs are imported. The induced contrast and images can be exported, and accurate quantification can be performed. This platform is based on the GATE Monte Carlo simulation toolkit, based on the GEANT4 toolkit and the MOBY phantom, a realistic 4D digital mouse. RESULTS We have validated this simulation platform to predict the contrast induction and minimum detectable concentration of GNPs on any given X-ray system. The study was applied to preclinical studies but is also expandable to clinical studies. CONCLUSIONS According to our knowledge, no other such validated simulation model currently exists, and this model could help radiology imaging with GNPs to be truly deployed.
Collapse
|
22
|
Shoghi KI, Badea CT, Blocker SJ, Chenevert TL, Laforest R, Lewis MT, Luker GD, Manning HC, Marcus DS, Mowery YM, Pickup S, Richmond A, Ross BD, Vilgelm AE, Yankeelov TE, Zhou R. Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine. ACTA ACUST UNITED AC 2021; 6:273-287. [PMID: 32879897 PMCID: PMC7442091 DOI: 10.18383/j.tom.2020.00023] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.
Collapse
Affiliation(s)
- Kooresh I Shoghi
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Cristian T Badea
- Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC
| | - Stephanie J Blocker
- Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC
| | | | - Richard Laforest
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Michael T Lewis
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX
| | - Gary D Luker
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | - H Charles Manning
- Vanderbilt Center for Molecular Probes-Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN
| | - Daniel S Marcus
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Yvonne M Mowery
- Department of Radiation Oncology, Duke University Medical Center, Durham, Durham, NC
| | - Stephen Pickup
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania.,Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
| | - Ann Richmond
- Department of Pharmacology, Vanderbilt School of Medicine, Nashville, TN
| | - Brian D Ross
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | - Anna E Vilgelm
- Department of Pathology, The Ohio State University, Columbus, OH
| | - Thomas E Yankeelov
- Departments of Biomedical Engineering, Diagnostic Medicine, and Oncology, Oden Institute for Computational Engineering and Sciences, Austin, TX; and.,Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX
| | - Rong Zhou
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania.,Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
| |
Collapse
|
23
|
Wang S, Wu W, Feng J, Liu F, Yu H. Low-dose spectral CT reconstruction based on image-gradient L 0-norm and adaptive spectral PICCS. Phys Med Biol 2020; 65:245005. [PMID: 32693399 DOI: 10.1088/1361-6560/aba7cf] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The photon-counting detector based spectral computed tomography (CT) is promising for lesion detection, tissue characterization, and material decomposition. However, the lower signal-to-noise ratio within multi-energy projection dataset can result in poorly reconstructed image quality. Recently, as prior information, a high-quality spectral mean image was introduced into the prior image constrained compressed sensing (PICCS) framework to suppress noise, leading to spectral PICCS (SPICCS). In the original SPICCS model, the image gradient L1-norm is employed, and it can cause blurred edge structures in the reconstructed images. Encouraged by the advantages in edge preservation and finer structure recovering, the image gradient L0-norm was incorporated into the PICCS model. Furthermore, due to the difference of energy spectrum in different channels, a weighting factor is introduced and adaptively adjusted for different channel-wise images, leading to an L0-norm based adaptive SPICCS (L0-ASPICCS) algorithm for low-dose spectral CT reconstruction. The split-Bregman method is employed to minimize the objective function. Extensive numerical simulations and physical phantom experiments are performed to evaluate the proposed method. By comparing with the state-of-the-art algorithms, such as the simultaneous algebraic reconstruction technique, total variation minimization, and SPICCS, the advantages of our proposed method are demonstrated in terms of both qualitative and quantitative evaluation results.
Collapse
Affiliation(s)
- Shaoyu Wang
- Key Lab of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing 400044, People's Republic of China. Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA 01854, United States of America. Engineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing 400044, People's Republic of China
| | | | | | | | | |
Collapse
|
24
|
Shuaib A, Bourisly AK. Effects of Irradiation Parameters and Position on Photobiomodulation Therapy for Spinal Cord Injury Rat Phantom Model: A Dosimetry Simulation Study. PHOTOBIOMODULATION PHOTOMEDICINE AND LASER SURGERY 2020; 38:661-666. [DOI: 10.1089/photob.2020.4864] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Ali Shuaib
- Biomedical Engineering Unit, Department of Physiology, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait
| | - Ali K. Bourisly
- Biomedical Engineering Unit, Department of Physiology, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait
| |
Collapse
|
25
|
Perez-Liva M, Yoganathan T, Herraiz JL, Porée J, Tanter M, Balvay D, Viel T, Garofalakis A, Provost J, Tavitian B. Ultrafast Ultrasound Imaging for Super-Resolution Preclinical Cardiac PET. Mol Imaging Biol 2020; 22:1342-1352. [PMID: 32602084 PMCID: PMC7497458 DOI: 10.1007/s11307-020-01512-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Revised: 04/13/2020] [Accepted: 05/27/2020] [Indexed: 02/07/2023]
Abstract
PURPOSE Physiological motion and partial volume effect (PVE) significantly degrade the quality of cardiac positron emission tomography (PET) images in the fast-beating hearts of rodents. Several Super-resolution (SR) techniques using a priori anatomical information have been proposed to correct motion and PVE in PET images. Ultrasound is ideally suited to capture real-time high-resolution cine images of rodent hearts. Here, we evaluated an ultrasound-based SR method using simultaneously acquired and co-registered PET-CT-Ultrafast Ultrasound Imaging (UUI) of the beating heart in closed-chest rodents. PROCEDURES The method was tested with numerical and animal data (n = 2) acquired with the non-invasive hybrid imaging system PETRUS that acquires simultaneously PET, CT, and UUI. RESULTS We showed that ultrasound-based SR drastically enhances the quality of PET images of the beating rodent heart. For the simulations, the deviations between expected and mean reconstructed values were 2 % after applying SR. For the experimental data, when using Ultrasound-based SR correction, contrast was improved by a factor of two, signal-to-noise ratio by 11 %, and spatial resolution by 56 % (~ 0.88 mm) with respect to static PET. As a consequence, the metabolic defect following an acute cardiac ischemia was delineated with much higher anatomical precision. CONCLUSIONS Our results provided a proof-of-concept that image quality of cardiac PET in fast-beating rodent hearts can be significantly improved by ultrasound-based SR, a portable low-cost technique. Improved PET imaging of the rodent heart may allow new explorations of physiological and pathological situations related with cardiac metabolism.
Collapse
Affiliation(s)
- Mailyn Perez-Liva
- Université de Paris, PARCC, INSERM, 56, rue Leblanc, 75015, Paris, France.
| | | | - Joaquin L Herraiz
- Nuclear Physics Group and IPARCOS, Complutense University of Madrid, Plaza de las Ciencias, 1, 28020, Madrid, Spain
- Health Research Institute of the Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Jonathan Porée
- Physics for Medicine Paris, Inserm/ESPCI Paris-PSL/PSL-University/CNRS, 17 rue Moreau, 75012, Paris, France
- Engineering physics department, Polytechnique Montréal, Montréal, Canada
| | - Mickael Tanter
- Physics for Medicine Paris, Inserm/ESPCI Paris-PSL/PSL-University/CNRS, 17 rue Moreau, 75012, Paris, France
| | - Daniel Balvay
- Université de Paris, PARCC, INSERM, 56, rue Leblanc, 75015, Paris, France
| | - Thomas Viel
- Université de Paris, PARCC, INSERM, 56, rue Leblanc, 75015, Paris, France
| | | | - Jean Provost
- Engineering physics department, Polytechnique Montréal, Montréal, Canada
- Montreal Heart Institute, Montréal, Canada
| | - Bertrand Tavitian
- Université de Paris, PARCC, INSERM, 56, rue Leblanc, 75015, Paris, France
- Service de Radiologie, APHP Centre, Hôpital Européen Georges Pompidou, Paris, France
| |
Collapse
|
26
|
Sung Y, Nelson B, Shanblatt ER, Gupta R, McCollough CH, Graves WS. Wave optics simulation of grating-based X-ray phase-contrast imaging using 4D Mouse Whole Body (MOBY) phantom. Med Phys 2020; 47:5761-5771. [PMID: 32969031 DOI: 10.1002/mp.14479] [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: 03/05/2020] [Revised: 08/31/2020] [Accepted: 09/01/2020] [Indexed: 12/13/2022] Open
Abstract
PURPOSE Demonstrate realistic simulation of grating-based x-ray phase-contrast imaging (GB-XPCI) using wave optics and the four-dimensional Mouse Whole Body (MOBY) phantom defined with non-uniform rational B-splines (NURBS). METHODS We use a full-wave approach, which uses wave optics for x-ray wave propagation from the source to the detector. This forward imaging model can be directly applied to NURBS-defined numerical phantoms such as MOBY. We assign the material properties (attenuation coefficient and electron density) of each model part using the data for adult human tissues. The Poisson noise is added to the simulated images based on the calculated photon flux at each pixel. RESULTS We simulate the intensity images of the MOBY phantom for eight different grating positions. From the simulated images, we calculate the absorption, differential phase, and normalized visibility contrast images. We also predict how the image quality is affected by different exposure times. CONCLUSIONS GB-XPCI can be simulated with the full-wave approach and a realistic numerical phantom defined with NURBS.
Collapse
Affiliation(s)
- Yongjin Sung
- College of Engineering & Applied Science, University of Wisconsin-Milwaukee, 3200 North Cramer Street, Milwaukee, WI, 53211, USA
| | - Brandon Nelson
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Elisabeth R Shanblatt
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Rajiv Gupta
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA, 02114, USA
| | - Cynthia H McCollough
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - William S Graves
- Department of Physics, Arizona State University, 550 East Tyler Drive, Tempe, AZ, 85287, USA
| |
Collapse
|
27
|
Silva CC, Berdeguez MB, Barboza T, Souza SA, Braz D, Silva AX, Sa LV. Preclinical radiation internal dosimetry in the development of new radiopharmaceuticals using GATE Monte Carlo simulation. Radiat Phys Chem Oxf Engl 1993 2020. [DOI: 10.1016/j.radphyschem.2020.108879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
|
28
|
Perez-Liva M, Yoganathan T, Herraiz JL, Porée J, Tanter M, Balvay D, Viel T, Garofalakis A, Provost J, Tavitian B. Ultrafast Ultrasound Imaging for Super-Resolution Preclinical Cardiac PET. Mol Imaging Biol 2020. [DOI: https://doi.org/10.1007/s11307-020-01512-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Abstract
Purpose
Physiological motion and partial volume effect (PVE) significantly degrade the quality of cardiac positron emission tomography (PET) images in the fast-beating hearts of rodents. Several Super-resolution (SR) techniques using a priori anatomical information have been proposed to correct motion and PVE in PET images. Ultrasound is ideally suited to capture real-time high-resolution cine images of rodent hearts. Here, we evaluated an ultrasound-based SR method using simultaneously acquired and co-registered PET-CT-Ultrafast Ultrasound Imaging (UUI) of the beating heart in closed-chest rodents.
Procedures
The method was tested with numerical and animal data (n = 2) acquired with the non-invasive hybrid imaging system PETRUS that acquires simultaneously PET, CT, and UUI.
Results
We showed that ultrasound-based SR drastically enhances the quality of PET images of the beating rodent heart. For the simulations, the deviations between expected and mean reconstructed values were 2 % after applying SR. For the experimental data, when using Ultrasound-based SR correction, contrast was improved by a factor of two, signal-to-noise ratio by 11 %, and spatial resolution by 56 % (~ 0.88 mm) with respect to static PET. As a consequence, the metabolic defect following an acute cardiac ischemia was delineated with much higher anatomical precision.
Conclusions
Our results provided a proof-of-concept that image quality of cardiac PET in fast-beating rodent hearts can be significantly improved by ultrasound-based SR, a portable low-cost technique. Improved PET imaging of the rodent heart may allow new explorations of physiological and pathological situations related with cardiac metabolism.
Collapse
|
29
|
Gupta A, Lee MS, Kim JH, Lee DS, Lee JS. Preclinical Voxel-Based Dosimetry in Theranostics: a Review. Nucl Med Mol Imaging 2020; 54:86-97. [PMID: 32377260 DOI: 10.1007/s13139-020-00640-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 03/27/2020] [Accepted: 03/31/2020] [Indexed: 12/22/2022] Open
Abstract
Due to the increasing use of preclinical targeted radionuclide therapy (TRT) studies for the development of novel theranostic agents, several studies have been performed to accurately estimate absorbed doses to mice at the voxel level using reference mouse phantoms and Monte Carlo (MC) simulations. Accurate dosimetry is important in preclinical theranostics to interpret radiobiological dose-response relationships and to translate results for clinical use. Direct MC (DMC) simulation is believed to produce more realistic voxel-level dose distribution with high precision because tissue heterogeneities and nonuniform source distributions in patients or animals are considered. Although MC simulation is considered to be an accurate method for voxel-based absorbed dose calculations, it is time-consuming, computationally demanding, and often impractical in daily practice. In this review, we focus on the current status of voxel-based dosimetry methods applied in preclinical theranostics and discuss the need for accurate and fast voxel-based dosimetry methods for pretherapy absorbed dose calculations to optimize the dose computation time in preclinical TRT.
Collapse
Affiliation(s)
- Arun Gupta
- 1Department of Radiology & Imaging, B.P. Koirala Institute of Health Sciences, Dharan, Nepal
| | - Min Sun Lee
- 2Department of Radiology, School of Medicine, Stanford University, Stanford, CA USA
| | - Joong Hyun Kim
- 3Center for Ionizing Radiation, Korea Research Institute of Standards and Science, Daejeon, South Korea
| | - Dong Soo Lee
- 4Department of Nuclear Medicine, College of Medicine, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080 South Korea
| | - Jae Sung Lee
- 4Department of Nuclear Medicine, College of Medicine, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080 South Korea.,5Interdisciplinary Program in Radiation Applied Life Science, Seoul National University, Seoul, South Korea.,6Department of Biomedical Sciences, College of Medicine, Seoul National University, Seoul, South Korea
| |
Collapse
|
30
|
Stenvall A, Larsson E, Holmqvist B, Strand SE, Jönsson BA. Quantitative γ-H2AX immunofluorescence method for DNA double-strand break analysis in testis and liver after intravenous administration of 111InCl 3. EJNMMI Res 2020; 10:22. [PMID: 32189079 PMCID: PMC7080928 DOI: 10.1186/s13550-020-0604-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 01/31/2020] [Indexed: 12/25/2022] Open
Abstract
Background It is well known that a severe cell injury after exposure to ionizing radiation is the induction of DNA double-strand breaks (DSBs). After exposure, an early response to DSBs is the phosphorylation of the histone H2AX molecule regions adjacent to the DSBs, referred to as γ-H2AX foci. The γ-H2AX assay after external exposure is a good tool for investigating the link between the absorbed dose and biological effect. However, less is known about DNA DSBs and γ-H2AX foci within the tissue microarchitecture after internal irradiation from radiopharmaceuticals. Therefore, in this study, we aimed to develop and validate a quantitative ex vivo model using γ-H2AX immunofluorescence staining and confocal laser scanning microscopy (CLSM) to investigate its applicability in nuclear medicine dosimetry research. Liver and testis were selected as the organs to study after intravenous administration of 111InCl3. Results In this study, we developed and validated a method that combines ex vivo γ-H2AX foci labeling of tissue sections with in vivo systemically irradiated mouse testis and liver tissues. The method includes CLSM imaging for intracellular cell-specific γ-H2AX foci detection and quantification and absorbed dose calculations. After exposure to ionizing radiation from 111InCl3, both hepatocytes and non-hepatocytes within the liver showed an absorbed dose-dependent elevation of γ-H2AX foci, whereas no such correlation was seen for the testis tissue. Conclusion It is possible to detect and quantify the radiation-induced γ-H2AX foci within the tissues of organs at risk after internal irradiation. We conclude that our method developed is an appropriate tool to study dose–response relationships in animal organs and human tissue biopsies after internal exposure to radiation.
Collapse
Affiliation(s)
- Anna Stenvall
- Department of Medical Radiation Physics, Clinical Sciences, Lund University, Lund, Sweden.
| | - Erik Larsson
- Department of Radiation Physics, Skåne University Hospital, Lund, Sweden
| | | | - Sven-Erik Strand
- Department of Medical Radiation Physics, Clinical Sciences, Lund University, Lund, Sweden
| | - Bo-Anders Jönsson
- Department of Medical Radiation Physics, Clinical Sciences, Lund University, Lund, Sweden
| |
Collapse
|
31
|
Magnetic fluid hyperthermia simulations in evaluation of SAR calculation methods. Phys Med 2020; 71:39-52. [DOI: 10.1016/j.ejmp.2020.02.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 01/21/2020] [Accepted: 02/13/2020] [Indexed: 11/21/2022] Open
|
32
|
Zhang X, Qu D, Ji Y, Xie X, Ning J. Study of rat organ dose conversion coefficients for external photon irradiation based on voxel model and Monte Carlo simulation. Appl Radiat Isot 2020; 156:109008. [DOI: 10.1016/j.apradiso.2019.109008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 11/03/2019] [Accepted: 11/23/2019] [Indexed: 10/25/2022]
|
33
|
Niu S, Lu S, Zhang Y, Huang X, Zhong Y, Yu G, Wang J. Statistical image-based material decomposition for triple-energy computed tomography using total variation regularization. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2020; 28:751-771. [PMID: 32597827 DOI: 10.3233/xst-200672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
BACKGROUND Triple-energy computed tomography (TECT) can obtain x-ray attenuation measurements at three energy spectra, thereby allowing identification of different material compositions with same or very similar attenuation coefficients. This ability is known as material decomposition, which can decompose TECT images into different basis material image. However, the basis material image would be severely degraded when material decomposition is directly performed on the noisy TECT measurements using a matrix inversion method. OBJECTIVE To achieve high quality basis material image, we present a statistical image-based material decomposition method for TECT, which uses the penalized weighted least-squares (PWLS) criteria with total variation (TV) regularization (PWLS-TV). METHODS The weighted least-squares term involves the noise statistical properties of the material decomposition process, and the TV regularization penalizes differences between local neighboring pixels in a decomposed image, thereby contributing to improving the quality of the basis material image. Subsequently, an alternating optimization method is used to minimize the objective function. RESULTS The performance of PWLS-TV is quantitatively evaluated using digital and mouse thorax phantoms. The experimental results show that PWLS-TV material decomposition method can greatly improve the quality of decomposed basis material image compared to the quality of images obtained using the competing methods in terms of suppressing noise and preserving edge and fine structure details. CONCLUSIONS The PWLS-TV method can simultaneously perform noise reduction and material decomposition in one iterative step, and it results in a considerable improvement of basis material image quality.
Collapse
Affiliation(s)
- Shanzhou Niu
- Jiangxi Key Laboratory of Numerical Simulation Technology, School of Mathematics and Computer Science, Gannan Normal University, Ganzhou, China
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Shaohui Lu
- Jiangxi Key Laboratory of Numerical Simulation Technology, School of Mathematics and Computer Science, Gannan Normal University, Ganzhou, China
| | - You Zhang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Xiaokun Huang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Yuncheng Zhong
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Gaohang Yu
- School of Science, Hangzhou Dianzi University, Hangzhou, China
| | - Jing Wang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| |
Collapse
|
34
|
Montgomery DA, Martinez NE. Dosimetric modeling of Tc-99, Cs-137, Np-237, and U-238 in the grass species Andropogon Virginicus: Development and comparison of stylized, voxel, and hybrid phantom geometry. JOURNAL OF ENVIRONMENTAL RADIOACTIVITY 2020; 211:106075. [PMID: 31627053 DOI: 10.1016/j.jenvrad.2019.106075] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 09/12/2019] [Accepted: 10/01/2019] [Indexed: 06/10/2023]
Abstract
This paper discusses the development, comparison, and application of three anatomically representative computational phantoms for the grass species Andropogon virginicus, an indigenous grass species in the Southeastern United States. Specifically, the phantoms developed in this work are: (1) a stylized phantom where plant organs (roots or shoots) are represented by simple geometric shapes, (2) a voxel phantom developed from micro-CT imagery of a plant specimen, and (3) a hybrid phantom resulting from the refinement of (2) by use of non-uniform rational basis spline (NURBS) surfaces. For each computational phantom, Monte Carlo dosimetric modeling was utilized to determine whole-organism and organ specific dose coefficients (DC) associated with external and internal exposure to 99Tc, 137Cs, 237Np, and 238U for A. virginicus. Model DCs were compared to each other and to current values for the ICRP reference wild grass in order to determine if noteworthy differences resulted from the utilization of more anatomically realistic phantom geometry. Modeled internal DCs were comparable with ICRP values. However, modeled external DCs were more variable with respect to ICRP values; this is proposed to be primarily due to differences in organism and source geometry definitions. Overall, the three anatomical phantoms were reasonably consistent. Some noticeable differences in internal DCs were observed between the stylized model and the voxel or hybrid models for external DCs for shoots and for cases of crossfire between plant organs. Additionally, uptake data from previous hydroponic (HP) experiments was applied in conjunction with hybrid model DCs to determine dose rates to the plant from individual radionuclides as an example of practical application. Although the models within are applied to a small-scale, hypothetical scenario as proof-of-principle, the potential, real-world utility of such complex dosimetric models for non-human biota is discussed, and a fit-for purpose approach for application of these models is proposed.
Collapse
Affiliation(s)
- Dawn A Montgomery
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, SC, USA; Center for Nuclear Environmental Engineering Sciences and Radioactive Waste Management (NEESRWM), Clemson University, Clemson, SC, USA.
| | - Nicole E Martinez
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, SC, USA; Center for Nuclear Environmental Engineering Sciences and Radioactive Waste Management (NEESRWM), Clemson University, Clemson, SC, USA
| |
Collapse
|
35
|
A New Method of Image Reconstruction for PET Using a Combined Regularization Algorithm. LECTURE NOTES IN COMPUTER SCIENCE 2020. [PMCID: PMC7340954 DOI: 10.1007/978-3-030-51935-3_19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
|
36
|
Wang H, Han Y, Chen Z, Hu R, Chatziioannou AF, Zhang B. Prediction of major torso organs in low-contrast micro-CT images of mice using a two-stage deeply supervised fully convolutional network. Phys Med Biol 2019; 64:245014. [PMID: 31747654 DOI: 10.1088/1361-6560/ab59a4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Delineation of major torso organs is a key step of mouse micro-CT image analysis. This task is challenging due to low soft tissue contrast and high image noise, therefore anatomical prior knowledge is needed for accurate prediction of organ regions. In this work, we develop a deeply supervised fully convolutional network which uses the organ anatomy prior learned from independently acquired contrast-enhanced micro-CT images to assist the segmentation of non-enhanced images. The network is designed with a two-stage workflow which firstly predicts the rough regions of multiple organs and then refines the accuracy of each organ in local regions. The network is trained and evaluated with 40 mouse micro-CT images. The volumetric prediction accuracy (Dice score) varies from 0.57 for the spleen to 0.95 for the heart. Compared to a conventional atlas registration method, our method dramatically improves the Dice of the abdominal organs by 18%-26%. Moreover, the incorporation of anatomical prior leads to more accurate results for small-sized low-contrast organs (e.g. the spleen and kidneys). We also find that the localized stage of the network has better accuracy than the global stage, indicating that localized single organ prediction is more accurate than global multiple organ prediction. With this work, the accuracy and efficiency of mouse micro-CT image analysis are greatly improved and the need for using contrast agent and high x-ray dose is potentially reduced.
Collapse
Affiliation(s)
- Hongkai Wang
- School of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, People's Republic of China
| | | | | | | | | | | |
Collapse
|
37
|
Cicone F, Gnesin S, Denoël T, Stora T, van der Meulen NP, Müller C, Vermeulen C, Benešová M, Köster U, Johnston K, Amato E, Auditore L, Coukos G, Stabin M, Schaefer N, Viertl D, Prior JO. Internal radiation dosimetry of a 152Tb-labeled antibody in tumor-bearing mice. EJNMMI Res 2019; 9:53. [PMID: 31187358 PMCID: PMC6560118 DOI: 10.1186/s13550-019-0524-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Accepted: 05/28/2019] [Indexed: 11/10/2022] Open
Abstract
Background Biodistribution studies based on organ harvesting represent the gold standard pre-clinical technique for dose extrapolations. However, sequential imaging is becoming increasingly popular as it allows the extraction of longitudinal data from single animals, and a direct correlation with deterministic radiation effects. We assessed the feasibility of mouse-specific, microPET-based dosimetry of an antibody fragment labeled with the positron emitter 152Tb [(T1/2 = 17.5 h, Eβ+mean = 1140 keV (20.3%)]. Image-based absorbed dose estimates were compared with those obtained from the extrapolation to 152Tb of a classical biodistribution experiment using the same antibody fragment labeled with 111In. 152Tb was produced by proton-induced spallation in a tantalum target, followed by mass separation and cation exchange chromatography. The endosialin-targeting scFv78-Fc fusion protein was conjugated with the chelator p-SCN-Bn-CHX-A”-DTPA, followed by labeling with either 152Tb or 111In. Micro-PET images of four immunodeficient female mice bearing RD-ES tumor xenografts were acquired 4, 24, and 48 h after the i.v. injection of 152Tb-CHX-DTPA-scFv78-Fc. After count/activity camera calibration, time-integrated activity coefficients (TIACs) were obtained for the following compartments: heart, lungs, liver, kidneys, intestines, tumor, and whole body, manually segmented on CT. For comparison, radiation dose estimates of 152Tb-CHX-DTPA-scFv78-Fc were extrapolated from mice dissected 4, 24, 48, and 96 h after the injection of 111In-CHX-DTPA-scFv78-Fc (3–5 mice per group). Imaging-derived and biodistribution-derived organ TIACs were used as input in the 25 g mouse model of OLINDA/EXM® 2.0, after appropriate mass rescaling. Tumor absorbed doses were obtained using the OLINDA2 sphere model. Finally, the relative percent difference (RD%) between absorbed doses obtained from imaging and biodistribution were calculated. Results RD% between microPET-based dosimetry and biodistribution-based dose extrapolations were + 12, − 14, and + 17 for the liver, the kidneys, and the tumors, respectively. Compared to biodistribution, the imaging method significantly overestimates the absorbed doses to the heart and the lungs (+ 89 and + 117% dose difference, respectively). Conclusions MicroPET-based dosimetry of 152Tb is feasible, and the comparison with organ harvesting resulted in acceptable dose discrepancies for body districts that can be segmented on CT. These encouraging results warrant additional validation using radiolabeled biomolecules with a different biodistribution pattern.
Collapse
Affiliation(s)
- Francesco Cicone
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, CH-1011, Lausanne, CH, Switzerland.
| | - Silvano Gnesin
- Institute of Radiation Physics, Lausanne University Hospital, Lausanne, CH, Switzerland
| | - Thibaut Denoël
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, CH-1011, Lausanne, CH, Switzerland
| | | | - Nicholas P van der Meulen
- Center for Radiopharmaceutical Sciences ETH-PSI-USZ, Paul Scherrer Institute (PSI), Villigen, CH, Switzerland.,Laboratory of Radiochemistry, Paul Scherrer Institute (PSI), Villigen, CH, Switzerland
| | - Cristina Müller
- Center for Radiopharmaceutical Sciences ETH-PSI-USZ, Paul Scherrer Institute (PSI), Villigen, CH, Switzerland
| | - Christiaan Vermeulen
- Center for Radiopharmaceutical Sciences ETH-PSI-USZ, Paul Scherrer Institute (PSI), Villigen, CH, Switzerland
| | - Martina Benešová
- Center for Radiopharmaceutical Sciences ETH-PSI-USZ, Paul Scherrer Institute (PSI), Villigen, CH, Switzerland
| | - Ulli Köster
- Institut Laue-Langevin, Grenoble, FR, France
| | | | - Ernesto Amato
- Section of Radiological Sciences, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, IT, Italy
| | - Lucrezia Auditore
- Section of Radiological Sciences, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, IT, Italy
| | - George Coukos
- Department of Oncology and Ludwig Center for Cancer Research, Lausanne, CH, Switzerland
| | | | - Niklaus Schaefer
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, CH-1011, Lausanne, CH, Switzerland
| | - David Viertl
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, CH-1011, Lausanne, CH, Switzerland
| | - John O Prior
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, CH-1011, Lausanne, CH, Switzerland
| |
Collapse
|
38
|
Gupta A, Lee MS, Kim JH, Park S, Park HS, Kim SE, Lee DS, Lee JS. Preclinical voxel-based dosimetry through GATE Monte Carlo simulation using PET/CT imaging of mice. Phys Med Biol 2019; 64:095007. [PMID: 30913544 DOI: 10.1088/1361-6560/ab134b] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Internal dosimetry is of critical importance to obtain an accurate absorbed dose-response relationship during preclinical molecular imaging and targeted radionuclide therapy (TRT). Conventionally, absorbed dose calculations have been performed using organ-level dosimetry based on the Medical Internal Radiation Dose (MIRD) schema. However, recent research has focused on developing more accurate voxel-level calculation methods. Geant4 application for emission tomography (GATE) Monte Carlo (MC) is a simulation toolkit gaining attention in voxel-based dosimetry. In this study, we used PET/CT images of real mice to estimate the absorbed doses in sensitive organs at voxel-level to evaluate the suitability of GATE MC simulation for preclinical dosimetry. Thirteen normal C57BL/6 mice (male, body weight: 27.71 ± 4.25 g) were used to acquire dynamic positron emission tomography/computed tomography (PET/CT) images after IV injection of 18F-FDG. GATE MC toolkit was applied to estimate the absorbed doses in various organs of mice at voxel-level using CT and PET images as voxelized phantom and voxelized source, respectively. In addition, mean absorbed dose at organ-level was calculated using MIRD schema for comparison purposes. The differences in the respective absorbed doses (mGy MBq-1) between GATE MC and MIRD schema for brain, heart wall, liver, lungs, stomach wall, spleen, kidneys, and bladder wall were 1.36, 12.3, -22.4, -11.2, -16.9, -2.87, -4.29, and 3.71%, respectively. Considering that the PET/CT data of real mice were used for GATE simulation, the absorbed doses estimated in this study are mouse-specific. Therefore, the GATE-based Monte Carlo is likely to allow for more accurate internal dosimetry calculations. This method can be used in TRT for personalized dosimetry because it considers patient-specific heterogeneous tissue compositions and activity distributions.
Collapse
Affiliation(s)
- Arun Gupta
- Department of Nuclear Medicine, College of Medicine, Seoul National University, Seoul, Republic of Korea
| | | | | | | | | | | | | | | |
Collapse
|
39
|
Gupta A, Shin JH, Lee MS, Park JY, Kim K, Kim JH, Suh M, Park CR, Kim YJ, Song MG, Jeong JM, Lee DS, Lee YS, Lee JS. Voxel-Based Dosimetry of Iron Oxide Nanoparticle-Conjugated 177Lu-Labeled Folic Acid Using SPECT/CT Imaging of Mice. Mol Pharm 2019; 16:1498-1506. [PMID: 30821463 DOI: 10.1021/acs.molpharmaceut.8b01125] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Several radiolabeled folic acid conjugates have been developed for targeted imaging and therapy. However, the therapeutic concept with radiolabeled folate conjugates has not yet been applied to clinical applications owing to the high renal absorbed dose. The effectiveness of targeted radionuclide therapy (TRT) depends primarily on the absorbed dose rate and on the total absorbed dose delivered to the tumor and to normal tissue. Owing to various limitations associated with organ level dosimetry, voxel-based dosimetry has become essential for the assessment of a more accurate absorbed dose during TRT. In this study, we synthesized iron oxide nanoparticle (IONP)-conjugated radiolabeled folate (177Lu-IONP-Folate) and performed voxel-based dosimetry using SPECT/CT images of normal mice through direct Geant4 application for emission tomography (GATE) Monte Carlo (MC) simulation. We also prepared 177Lu-Folate and 177Lu-IONPs for the comparison of absorbed doses with that of 177Lu-IONP-Folate. In addition, we calculated the mean absorbed dose at the organ-level using the medical internal radiation dose (MIRD) schema. The radioactivities of all three radiotracers were mainly accumulated in the liver and kidneys immediately after injection. For the kidneys, the voxel-based absorbed doses obtained with 177Lu-IONP-Folate, 177Lu-Folate, and 177Lu-IONPs were 1.01 ± 0.17, 2.46 ± 0.50, and 0.52 ± 0.08 Gy/MBq, respectively. The renal absorbed dose decreased significantly (∼half) when 177Lu-IONP-Folate was used compared with when the 177Lu-Folate only was used. The mean absorbed dose values obtained at organ-level using the MIRD schema were comparable to voxel-based absorbed doses estimated with GATE MC. The voxel-based absorbed dose values obtained in this study of individualized activity show that the renal absorbed dose could be reduced to almost half with 177Lu-IONP-Folate. Therefore, 177Lu-IONP-Folate could be clinically applicable in the TRT of folate receptor-positive cancers in a personalized manner when using the voxel-based dosimetry method.
Collapse
Affiliation(s)
- Arun Gupta
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea
| | - Jae H Shin
- Department of Chemistry, Graduate School , Kyung Hee University , Seoul 02447 , Korea
| | - Min S Lee
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea.,Interdisciplinary Program in Radiation Applied Life Science , Seoul National University , Seoul 08826 , Korea
| | - Ji Y Park
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea
| | - Kyuwan Kim
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea
| | - Joong H Kim
- Center for Ionizing Radiation , Korea Research Institute of Standards and Science , Daejeon 34113 , Korea
| | - Minseok Suh
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea
| | - Cho R Park
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea
| | - Young J Kim
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea
| | - Myung G Song
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea
| | - Jae M Jeong
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea
| | - Dong S Lee
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea.,Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology , Seoul National University , Suwon 08826 , Korea
| | - Yun-Sang Lee
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea
| | - Jae S Lee
- Department of Nuclear Medicine , Seoul National University College of Medicine , Seoul 03080 , Korea.,Interdisciplinary Program in Radiation Applied Life Science , Seoul National University , Seoul 08826 , Korea.,Department of Biomedical Sciences , Seoul National University College of Medicine , Seoul 03080 , Korea
| |
Collapse
|
40
|
Vaniqui A, van der Heyden B, Almeida IP, Schyns LEJR, van Hoof SJ, Verhaegen F. On the determination of planning target margins due to motion for mice lung tumours using a four-dimensional MOBY phantom. Br J Radiol 2019; 92:20180445. [PMID: 30004793 PMCID: PMC6541181 DOI: 10.1259/bjr.20180445] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 07/05/2018] [Accepted: 07/06/2018] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE: This work aims to analyse the effect of respiratory motion on optimal irradiation margins for murine lung tumour models. METHODS: Four-dimensional mathematical phantoms with different lung tumour locations affected by respiratory motion were created. Two extreme breathing curves were adopted and divided into time-points. Each time-point was loaded in a treatment planning system and Monte Carlo (MC) dose calculations were performed for a 360° arc plan. A time-resolved dose was derived, considering the gantry rotation and the breathing motion. Radiotherapy metrics were derived to assess the final treatment plans. An interpolation function was investigated to reduce calculation cost. RESULTS: The effect of respiratory motion on the treatment plan quality is strongly dependent on the breathing pattern and the tumour position. Tumours located closer to the diaphragm required a compromise between tumour conformity and healthy tissue damage. A recipe, which considers collimator size, was proposed to derive tumour margins and spare the organs at risk (OARs) by respecting constraints on user-defined metrics. CONCLUSION: It is recommended to add a target margin, especially on sites where movement is substantial. A simple recipe to derive tumour margins was developed. ADVANCES IN KNOWLEDGE: This work is a first step towards a standard planning target volume concept in pre-clinical radiotherapy.
Collapse
Affiliation(s)
- Ana Vaniqui
- Department of Radiation Oncology (MAASTRO), GROW—School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Brent van der Heyden
- Department of Radiation Oncology (MAASTRO), GROW—School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Isabel P Almeida
- Department of Radiation Oncology (MAASTRO), GROW—School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Lotte EJR Schyns
- Department of Radiation Oncology (MAASTRO), GROW—School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | | | - Frank Verhaegen
- Department of Radiation Oncology (MAASTRO), GROW—School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| |
Collapse
|
41
|
George Xu X. Innovations in Computer Technologies Have Impacted Radiation Dosimetry Through Anatomically Realistic Phantoms and Fast Monte Carlo Simulations. HEALTH PHYSICS 2019; 116:263-275. [PMID: 30585974 DOI: 10.1097/hp.0000000000001007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Radiological physics principles have not changed in the past 60 y when computer technologies advanced exponentially. The research field of anatomical modeling for the purpose of radiation dose calculations has experienced an explosion in activity in the past two decades. Such an exciting advancement is due to the feasibility of creating three-dimensional geometric details of the human anatomy from tomographic imaging and of performing Monte Carlo radiation transport simulations on increasingly fast and cheap personal computers. The advent of a new type of high-performance computing hardware in recent years-graphics processing units-has made it feasible to carry out time-consuming Monte Carlo calculations at near real-time speeds. This paper introduces the history of three generations of computational human phantoms (the stylized medical internal radiation dosimetry-type phantoms, the voxelized tomographic phantoms, and the boundary representation deformable phantoms) and new development of the graphics processing unit-based Monte Carlo radiation dose calculations. Examples are given for research projects performed by my students in applying computational phantoms and a new Monte Carlo code, ARCHER, to problems in radiation protection, imaging, and radiotherapy. Finally, the paper discusses challenges and future opportunities for research.
Collapse
Affiliation(s)
- X George Xu
- JEC 5049, Rensselaer Polytechnic Institute, 110 8th St., Troy, NY 12180
| |
Collapse
|
42
|
López-Coello LI, Torres-García E, Díaz-Sánchez LE, Oros-Pantoja R, Aranda-Lara L. Differences in the S value between male and female murine model for diagnostic, therapeutic and theragnostic radionuclides. Appl Radiat Isot 2019; 146:61-65. [PMID: 30753986 DOI: 10.1016/j.apradiso.2019.01.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 01/24/2019] [Indexed: 11/29/2022]
Abstract
The aim of this work was to calculate S values for 99mTc, 67Ga, 68Ga, 18F, 223Ra, 166Ho, 90Y, 161Tb 131I and 177Lu, using a mouse phantom (MOBY) standard and considering the anatomic sizes from males and females, the simulation of radiation transport was performed with GATE/Geant4 platform. This indicates that in the internal dosimetry the use of a customized geometry is relevant for each gender and a standard model is not a good choice.
Collapse
Affiliation(s)
- Límbano Iván López-Coello
- Universidad Autónoma del Estado de México, Paseo Tollocan s/n esquina Jesús Carranza, Col. Moderna de la Cruz, 50180, Toluca de Lerdo, Mexico
| | - Eugenio Torres-García
- Universidad Autónoma del Estado de México, Paseo Tollocan s/n esquina Jesús Carranza, Col. Moderna de la Cruz, 50180, Toluca de Lerdo, Mexico.
| | - Luis Enrique Díaz-Sánchez
- Universidad Autónoma del Estado de México, Paseo Tollocan s/n esquina Jesús Carranza, Col. Moderna de la Cruz, 50180, Toluca de Lerdo, Mexico
| | - Rigoberto Oros-Pantoja
- Universidad Autónoma del Estado de México, Paseo Tollocan s/n esquina Jesús Carranza, Col. Moderna de la Cruz, 50180, Toluca de Lerdo, Mexico
| | - Liliana Aranda-Lara
- Universidad Autónoma del Estado de México, Paseo Tollocan s/n esquina Jesús Carranza, Col. Moderna de la Cruz, 50180, Toluca de Lerdo, Mexico
| |
Collapse
|
43
|
Zhang Y, Salehjahromi M, Yu H. Tensor decomposition and non-local means based spectral CT image denoising. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2019; 27:397-416. [PMID: 31081796 PMCID: PMC7371001 DOI: 10.3233/xst-180413] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
BACKGROUNDAs one type of the state-of-the-art detectors, photon counting detectors are used in spectral computed tomography (CT) to classify the received photons into several energy channels and generate multichannel projections simultaneously. However, FBP reconstructed images contain severe noise due to the low photon counts in each energy channel.OBJECTIVEA spectral CT image denoising method based on tensor-decomposition and non-local means (TDNLM) is proposed.METHODSIn a CT image, it is widely accepted that there exists self-similarity over the spatial domain. In addition, because a multichannel CT image is obtained from the same object at different energies, images among different channels are highly correlated. Motivated by these two characteristics of the spectral CT images, tensor decomposition and non-local means are employed to recover fine structures in spectral CT images. Moreover, images in all energy channels are added together to form a high signal-to-noise ratio image, which is applied to encourage the signal preservation of the TDNLM. The combination of TD, NLM and the guidance of a high-quality image enhances the low-dose spectral CT, and a parameter selection strategy is designed to achieve the optimal image quality.RESULTSThe effectiveness of the developed algorithm is validated on both numerical simulations and realistic preclinical applications. The root mean square error (RMSE) and the structural similarity (SSIM) are used to quantitatively assess the image quality. The proposed method successfully restored high-quality images (average RMSE=0.0217 cm-1 and SSIM=0.987) from noisy spectral CT images (average RMSE=0.225 cm-1 and SSIM=0.633). In addition, RMSE of each decomposed material component is also remarkably reduced. Compared to the state-of-the-art iterative spectral CT reconstruction algorithms, the proposed method achieves comparable performance with dramatically reduced computational cost, resulting in a speedup of >50.CONCLUSIONSThe outstanding denoising performance, the high computational efficiency and the adaptive parameter selection strategy make the proposed method practical for spectral CT applications.
Collapse
Affiliation(s)
- Yanbo Zhang
- Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA USA
- PingAn Technology, US Research Lab, Palo Alto, CA, USA
| | - Morteza Salehjahromi
- Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA USA
| | - Hengyong Yu
- Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA USA
| |
Collapse
|
44
|
Mejia J, Mederos B, Zhao J, Ortega L, Gordillo N. Reconstruction of Positron Emission Tomography Images Using Gaussian Curvature. JOURNAL OF HEALTHCARE ENGINEERING 2018; 2018:4706165. [PMID: 30581548 PMCID: PMC6276392 DOI: 10.1155/2018/4706165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 09/25/2018] [Accepted: 10/29/2018] [Indexed: 11/17/2022]
Abstract
Positron emission tomography (PET) provides images of metabolic activity in the body, and it is used in the research, monitoring, and diagnosis of several diseases. However, the raw data produced by the scanner are severely corrupted by noise, causing a degraded quality in the reconstructed images. In this paper, we proposed a reconstruction algorithm to improve the image reconstruction process, addressing the problem from a variational geometric perspective. We proposed using the weighted Gaussian curvature (WGC) as a regularization term to better deal with noise and preserve the original geometry of the image, such as the lesion structure. In other contexts, the WGC term has been found to have excellent capabilities for preserving borders and structures of low gradient magnitude, such as ramp-like structures; at the same time, it effectively removes noise in the image. We presented several experiments aimed at evaluating contrast and lesion detectability in the reconstructed images. The results for simulated images and real data showed that our proposed algorithm effectively preserves lesions and removes noise.
Collapse
Affiliation(s)
- Jose Mejia
- Department of Electrical and Computation Engineering, Universidad Autonoma de Ciudad Juarez, Ciudad Juarez 32310, Mexico
| | - Boris Mederos
- Department of Physics and Mathematics, Universidad Autonoma de Ciudad Juarez, Ciudad Juarez 32310, Mexico
| | - Jie Zhao
- School of Medical Imaging, Xuzhou Medical University, XuZhou, China
| | - Leticia Ortega
- Department of Electrical and Computation Engineering, Universidad Autonoma de Ciudad Juarez, Ciudad Juarez 32310, Mexico
| | - Nelly Gordillo
- Department of Electrical and Computation Engineering, Universidad Autonoma de Ciudad Juarez, Ciudad Juarez 32310, Mexico
| |
Collapse
|
45
|
Wu W, Zhang Y, Wang Q, Liu F, Chen P, Yu H. Low-dose spectral CT reconstruction using image gradient ℓ 0-norm and tensor dictionary. APPLIED MATHEMATICAL MODELLING 2018; 63:538-557. [PMID: 32773921 PMCID: PMC7409840 DOI: 10.1016/j.apm.2018.07.006] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Spectral computed tomography (CT) has a great superiority in lesion detection, tissue characterization and material decomposition. To further extend its potential clinical applications, in this work, we propose an improved tensor dictionary learning method for low-dose spectral CT reconstruction with a constraint of image gradient ℓ 0-norm, which is named as ℓ 0TDL. The ℓ 0TDL method inherits the advantages of tensor dictionary learning (TDL) by employing the similarity of spectral CT images. On the other hand, by introducing the ℓ 0-norm constraint in gradient image domain, the proposed method emphasizes the spatial sparsity to overcome the weakness of TDL on preserving edge information. The split-bregman method is employed to solve the proposed method. Both numerical simulations and real mouse studies are perform to evaluate the proposed method. The results show that the proposed ℓ 0TDL method outperforms other competing methods, such as total variation (TV) minimization, TV with low rank (TV+LR), and TDL methods.
Collapse
Affiliation(s)
- Weiwen Wu
- Key Lab of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing 400044, China
- Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA
| | - Yanbo Zhang
- Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA
| | - Qian Wang
- Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA
| | - Fenglin Liu
- Key Lab of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing 400044, China
- Engineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing 400044, China
- Corresponding author at: Key Lab of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing 400044, China. (F. Liu)
| | - Peijun Chen
- Key Lab of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing 400044, China
| | - Hengyong Yu
- Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA
| |
Collapse
|
46
|
Klose AD, Paragas N. Automated quantification of bioluminescence images. Nat Commun 2018; 9:4262. [PMID: 30323260 PMCID: PMC6189049 DOI: 10.1038/s41467-018-06288-w] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Accepted: 08/24/2018] [Indexed: 02/03/2023] Open
Abstract
We developed a computer-aided analysis tool for quantitatively determining bioluminescent reporter distributions inside small animals. The core innovations are a body-fitting animal shuttle and a statistical mouse atlas, both of which are spatially aligned and scaled according to the animal’s weight, and hence provide data congruency across animals of varying size and pose. In conjunction with a multispectral bioluminescence tomography technique capitalizing on the spatial framework of the shuttle, the in vivo biodistribution of luminescent reporters can rapidly be calculated and, thus, enables operator-independent and computer-driven data analysis. We demonstrate its functionality by quantitatively monitoring a bacterial infection, where the bacterial organ burden was determined and validated with the established serial-plating method. In addition, the statistical mouse atlas was validated and compared to existing techniques providing an anatomical reference. The proposed data analysis tool promises to increase data throughput and data reproducibility and accelerate human disease modeling in mice. Analysis of bioluminescence images of bacterial distributions in living animals is mostly manual and semiquantitative. Here, the authors present an analysis platform featuring an animal mold, a probabilistic organ atlas, and a mirror gantry to perform automatic in vivo bioluminescence quantification.
Collapse
Affiliation(s)
| | - Neal Paragas
- InVivo Analytics, New York, NY, USA. .,University of Washington, Seattle, WA, USA.
| |
Collapse
|
47
|
Holbrook M, Clark DP, Badea CT. Overcoming detector limitations of x-ray photon counting for preclinical microcomputed tomography. J Med Imaging (Bellingham) 2018; 6:011004. [PMID: 30840718 DOI: 10.1117/1.jmi.6.1.011004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 07/30/2018] [Indexed: 12/21/2022] Open
Abstract
Spectral computed tomography (CT) using photon counting detectors (PCDs) can provide accurate tissue composition measurements by utilizing the energy dependence of x-ray attenuation in different materials. PCDs are especially suited for K-edge imaging, revealing the spatial distribution of select imaging probes through quantitative material decomposition. We report on a prototype spectral micro-CT system with a CZT-based PCD (DxRay, Inc.) that has 16 × 16 pixels of 0.5 × 0.5 mm 2 , a thickness of 3 mm, and four energy thresholds. Due to the PCD's limited size ( 8 × 8 mm 2 ), our system uses a translate-rotate projection acquisition strategy to cover a field of view relevant for preclinical imaging ( ∼ 4.5 cm ). Projection corrections were implemented to minimize artifacts associated with dead pixels and projection stitching. A sophisticated iterative algorithm was used to reconstruct both phantom and ex vivo mouse data. To achieve preclinically relevant spatial resolution, we trained a convolutional neural network to perform pan-sharpening between low-resolution PCD data ( 247 - μ m voxels) and high-resolution energy-integrating detector data ( 82 - μ m voxels), recovering a high-resolution estimate of the spectral contrast suitable for material decomposition. Long-term, preclinical spectral CT systems such as ours could serve in the developing field of theranostics (therapy and diagnostics) for cancer research.
Collapse
Affiliation(s)
- Matthew Holbrook
- Duke University, Center for In Vivo Microscopy, Department of Radiology, Durham, North Carolina, United States
| | - Darin P Clark
- Duke University, Center for In Vivo Microscopy, Department of Radiology, Durham, North Carolina, United States
| | - Cristian T Badea
- Duke University, Center for In Vivo Microscopy, Department of Radiology, Durham, North Carolina, United States
| |
Collapse
|
48
|
Zhang B, Yin W, Liu H, Cao X, Wang H. Bioluminescence tomography with structural information estimated via statistical mouse atlas registration. BIOMEDICAL OPTICS EXPRESS 2018; 9:3544-3558. [PMID: 30338139 PMCID: PMC6191626 DOI: 10.1364/boe.9.003544] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 06/27/2018] [Accepted: 07/02/2018] [Indexed: 05/10/2023]
Abstract
Due to an ill-posed and underestimated characteristic of bioluminescence tomography (BLT) reconstruction, a priori anatomical information obtained from computed tomography (CT) or magnetic resonance imaging (MRI), is usually incorporated to improve the reconstruction accuracy. The organs need to be segmented, which is time-consuming and challenging, especially for the low-contrast CT images. In this paper, we present a BLT reconstruction method based on a statistical mouse atlas to improve the efficiency of heterogeneous model generation and the accuracy of target localization. The low-contrast CT image of the mouse was first registered to the statistical mouse atlas model with the constraints of mouse surface and high-contrast organs (bone and lung). Then the other organs, such as the liver and kidney, were determined automatically through the statistical mouse atlas model. The estimated organs were then discretized into tetrahedral meshes for BLT reconstruction. The linearized Bregman method was used to solve the sparse inverse problem of BLT by minimizing the regularization function (L1 norm plus L2 norm with smooth factor). Both numerical simulations and in vivo experiments were conducted, and the results demonstrate that even though the localization of the estimated organs may not be exactly accurate, the proposed method is feasible to reconstruct the bioluminescent source effectively and accurately with the estimated organs. This method would greatly benefit the bioluminescent light source localization for hybrid BLT/CT systems.
Collapse
Affiliation(s)
- Bin Zhang
- School of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Wanzhou Yin
- School of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Hao Liu
- School of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Xu Cao
- Engineering Research Center of Molecular and Neuro Imaging of the Ministry of Education & School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Hongkai Wang
- School of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
| |
Collapse
|
49
|
van der Heyden B, Podesta M, Eekers DB, Vaniqui A, Almeida IP, Schyns LE, van Hoof SJ, Verhaegen F. Automatic multiatlas based organ at risk segmentation in mice. Br J Radiol 2018; 92:20180364. [PMID: 29975151 DOI: 10.1259/bjr.20180364] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE: During the treatment planning of a preclinical small animal irradiation, which has time limitations for reasons of animal wellbeing and workflow efficiency, the time consuming organ at risk (OAR) delineation is performed manually. This work aimed to develop, demonstrate, and quantitatively evaluate an automated contouring method for six OARs in a preclinical irritation treatment workflow. METHODS: Microcone beam CT images of nine healthy mice were contoured with an in-house developed multiatlas-based image segmentation (MABIS) algorithm for six OARs: kidneys, eyes, heart, and brain. The automatic contouring was compared with the manual delineation using three quantitative metrics: the Dice Similarity Coefficient (DSC), 95th percentile Hausdorff Distance, and the centre of mass displacement. RESULTS: A good agreement between manual and automatic contouring was found for OARs with sharp organ boundaries. For the brain and the heart, the median DSC was larger than 0.94, the median 95th Hausdorff Distance smaller than 0.44 mm, and the median centre of mass displacement smaller than 0.20 mm. Lower DSC values were obtained for the other OARs, but the median DSC was still larger than 0.74 for the left eye, 0.69 for the right eye, 0.89 for the left kidney and 0.80 for the right kidney. CONCLUSION: The MABIS algorithm was able to delineate six OARs with a relatively high accuracy. Segmenting OARs with sharp organ boundaries performed better than low contrast OARs. ADVANCES IN KNOWLEDGE: A MABIS algorithm is developed, evaluated, and demonstrated in a preclinical small animal irradiation research workflow.
Collapse
Affiliation(s)
- Brent van der Heyden
- 1 Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre , Maastricht , The Netherlands
| | - Mark Podesta
- 1 Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre , Maastricht , The Netherlands
| | - Daniëlle Bp Eekers
- 1 Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre , Maastricht , The Netherlands.,2 Proton Therapy Department South-East Netherlands (ZON-PTC) , Maastricht , The Netherlands
| | - Ana Vaniqui
- 1 Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre , Maastricht , The Netherlands
| | - Isabel P Almeida
- 1 Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre , Maastricht , The Netherlands
| | - Lotte Ejr Schyns
- 1 Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre , Maastricht , The Netherlands
| | | | - Frank Verhaegen
- 1 Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre , Maastricht , The Netherlands
| |
Collapse
|
50
|
Monte Carlo GEANT4-based application for in vivo RBE study using small animals at LNS-INFN preclinical hadrontherapy facility. Phys Med 2018; 54:173-178. [PMID: 30037452 DOI: 10.1016/j.ejmp.2018.07.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 07/09/2018] [Accepted: 07/11/2018] [Indexed: 01/26/2023] Open
Abstract
Preclinical studies represent an important step towards a deep understanding of the biological response to ionizing radiations. The effectiveness of proton therapy is higher than photons and, for clinical purposes, a fixed value of 1.1 is used for the relative biological effectiveness (RBE) of protons considered 1.1. Recent in vitro studies have reported that the RBE along the spread-out Bragg peak (SOBP) is not constant and, in particular, the RBE value increases on the distal part of SOBP. The present work has been carried-out in the perspective of a preclinical hadrontherapy facility at LNS-INFN and was focused on the experimental preparation of an in vivo study concerning the RBE variation along the SOBP. The main purpose of this work was to determine, using GEANT4-based Monte Carlo simulations, the best configuration for small animal treatments. The developed GEANT4 application simulates the proton-therapy beam line of LNS-INFN (CATANA facility) and allows to import the DICOM-CT images as targets. The RBE will be evaluated using a deterministic radiation damage like myelopathy as end-point. In fact, the dose at which the 50% of animals will show the myelopathy is supposed to be LET-dependent. In this work, we studied different treatment configurations in order to choose the best two that maximize the LET difference reducing as much as possible the dose released to healthy tissue. The results will be useful to plan hadrontherapy treatments for preclinical in vivo studies and, in particular, for the future in vivo RBE studies.
Collapse
|