Development of patient-specific 3D models from histopathological samples for applications in radiation therapy

DeCunha, Joseph M.; Poole, Christopher; Vallières, Martin; Torres, José; Camilleri-Broët, Sophie; Rayes, Roni F.; Spicer, Jonathan; Enger, Shirin A.

doi:10.1016/j.ejmp.2020.12.009

Cited by 4 publications

(4 citation statements)

References 22 publications

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“…The aim of this study was to examine the accuracy of approximate methods for the fast calculation of patient-specific microdosimetric distributions. Variation in cell spacing and nucleus 0.246  0.004 0.245  0.005 0.247  0.003 Ir 192 0.50  0.01 0.49  0.01 0.495  0.009 0.502  0.008 Yb 169 0.89  0.01 0.803  0.03 0.839  0.009 0.85  0.02 I 125 1.001  0.004 0.797  0.001 0.901  0.002 0.89  0.01 y d ¯m keV m ⎡ ⎣ ⎤ ⎦ Co 60 0.74  0.02 0.66  0.02 0.71  0.04 0.72  0.02 Ir 192 1.22  0.05 1.10  0.03 1.17  0.03 1.19  0.03 Yb 169 1.68  0.03 1.470  0.008 1.60  0.02 1.60  0.04 I 125 2.173  0.009 1.866  0.004 2.062  0.005 2.06  0.03 radius of only a few mm was observed across multiple lung adenocarcinoma histopathological samples in a previous study (DeCunha et al 2021). This small variation suggests that conclusions drawn from the single sample investigated should be applicable to other lung adenocarcinoma samples.…”

Section: Discussionmentioning

confidence: 71%

“…( ) calculation Patient-specific microdosimetric distributions are microdosimetric functions determined in cell and nucleus volumes whose sizes are obtained from histopathological samples (Poole et al 2015, DeCunha et al 2021. We have found that calculation of such distributions require computational resources on the order of 10 000 core hours using the methods described in this work for Co 60 and thus are not currently viable for use in a clinical environment.…”

Section: Fixed Radius Models For F Ymentioning

confidence: 99%

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Patient-specific microdosimetry: a proof of concept

DeCunha¹,

Villegas²,

Vallières³

et al. 2021

Phys. Med. Biol.

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Microscopic energy deposition distributions from ionizing radiation vary depending on biological target size and are used to predict the biological effects of an irradiation. Ionizing radiation is thought to kill cells or inhibit the cell cycle mainly by damaging DNA in the cell nucleus. The size of cells and nuclei depends on tissue type, cell cycle, and malignancy, all of which vary between patients. The aim of this study was to develop methods to perform patient-specific microdosimetry, that being, determining microdosimetric quantities in volumes that correspond to the sizes of cells and nuclei observed in a patient’s tissue. A histopathological sample extracted from a stage I lung adenocarcinoma patient was analyzed. A pouring simulation was used to generate a three-dimensional tissue model from cell and nucleus size information determined from the histopathological sample. Microdosimetric distributions including and were determined for and in a patient-specific model containing a distribution of cell and nucleus sizes. Fixed radius models and a summation method were compared to the full patient-specific model to evaluate their suitability for fast determination of patient-specific microdosimetric parameters. In the summation method, f(y) from many fixed radii models are summed. Fixed radius models do not provide a close approximation of the full patient-specific model or for the lower energy sources investigated, and The higher energy sources investigated, and are less sensitive to target size variation than and The summation method yields the most accurate approximation of the full model for all radioisotopes investigated. The use of a summation method allows for the computation of patient-specific microdosimetric distributions with the computing power of a personal computer. With appropriate biological inputs the microdosimetric distributions computed using these methods can yield a patient-specific relative biological effectiveness as part of a multiscale treatment planning approach.

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Section: Discussionmentioning

confidence: 71%

Section: Fixed Radius Models For F Ymentioning

confidence: 99%

Patient-specific microdosimetry: a proof of concept

DeCunha¹,

Villegas²,

Vallières³

et al. 2021

Phys. Med. Biol.

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“…For both voxel sizessimulated, we calculated microdosimetricspectra in 39 different spherical target sizessuch that predictionsof energydeposition probabilitiesin targetswhose sizes correspondto biologicaltargetsof interest can be made. One such implementation has been described in past work by DeCunha et al (2021aDeCunha et al ( , 2021b, which demonstratedthe feasibility of performingpatient-specific or tissue-specific microdosimetry (DeCunha et al 2021b(DeCunha et al , 2021a. By weighting a series of microdosimetric spectra in various target sizes accordingto a patient's known cell and nucleus-sizedistributions, a patient-specific microdosimetric distribution can be calculated.…”

Section: Target Size Weighting Of Microdosimetric Spectramentioning

confidence: 99%

GPU-accelerated calculation of proton microdosimetric spectra as a function of target size, proton energy, and bounding volume size

2023

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Objective: Shortcomings of dose-averaged linear energy transfer (LET_D), the quantity which is most commonly used to quantify proton relative biological effectiveness (RBE), have long been recognized. Microdosimetric spectra may overcome the limitations of LET_D but are extremely computationally demanding to calculate. A systematic library of lineal energy spectra for monoenergetic protons could enable rapid determination of microdosimetric spectra in a clinical environment. The objective of this work was to calculate and validate such a library of lineal energy spectra. Approach: SuperTrack, a GPU-accelerated CUDA/C++ based application, was developed to superimpose tracks calculated using Geant4 onto targets of interest and to compute microdosimetric spectra. Lineal energy spectra of protons with energies from 0.1 to 100 MeV were determined in spherical targets of diameters from 1 nm to 10 μm and in bounding voxels with side lengths of 5 μm and 3 mm.Main Results: Compared to an analogous Geant4-based application, SuperTrack is up to 3500 times more computationally efficient if each track is resampled 1000 times. Dose spectra of lineal energy and dose-mean lineal energy calculated with SuperTrack were consistent with values published in the literature and with comparison to a Geant4 simulation. Using SuperTrack, we developed the largest known library of proton microdosimetric spectra as a function of primary proton energy, target size, and bounding volume size. Significance: SuperTrack greatly increases the computational efficiency of the calculation of microdosimetric spectra. The elevated lineal energy observed in a 3 mm side length bounding volume suggests that lineal energy spectra determined experimentally or computed in small bounding volumes may not be representative of the lineal energy spectra in voxels of a dose calculation grid. The library of lineal energy spectra calculated in this work could be integrated with a treatment planning system for rapid determination of lineal energy spectra in patient geometries. 

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“…Different methods [20][21][22][23][24][25][26] have been proposed to model cell population. Barberet et al [27] implemented a method based on high resolution confocal imaging and ion beam analysis in order to obtain realistic cell nucleus geometry; however this method requires a fully dedicated image reconstruction process that is most of the time not easily accessible to users.…”

Section: Introductionmentioning

confidence: 99%

CPOP: An open source C++ cell POPulation modeler for radiation biology applications

Maigne¹,

Delsol²,

Fois³

et al. 2021

Physica Medica

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Multicellular tumor spheroids are realistic in-vitro systems used in radiation biology research to study the effect of anticancer drugs or to evaluate the resistance of cancer cells under specific conditions. When combining the modeling of spheroids together with the simulation of radiation using Monte Carlo methods, one could estimate cell and DNA damage to be compared with experimental data. We developed a Cell Population (CPOP) modeler combined to Geant4 simulations in order to tackle how energy depositions are allocated to cells, especially when enhancing radiation outcomes using high-Z nanoparticles. CPOP manages to model large threedimensional cell populations with independent deformable cells described with their nucleus, cytoplasm and membranes together with force law systems to manage cell-cell interactions. Methods: CPOP is an opensource platform written in C++. It is divided into two main libraries: a "Modeler" library, for cell geometry modeling using meshes, and a Multi Agent System (MAS) library, simulating all agent (cell) interactions among the population. CPOP is fully interfaced with the Geant4 Monte Carlo toolkit and is able to directly launch Geant4 simulations after compilation. We modeled a full and realistic 3D cell population from SK-MEL28 melanoma cell population cultured experimentally. The spheroid diameter of 550 ± 40 µm corresponds to a population of approximately 1000 cells having a diameter of 17.2 ± 2.5 µm and a nucleus diameter of 11.2 ± 2.0 µm. We decided to reproduce cell irradiations performed with a X-RAD 320 Biological Irradiator (Precision XRay Inc., North Branford, CT). Results: We simulated the energy spectrum of secondary particles generated in the vicinity of the spheroid and plotted the different energy spectra recovered internally to the spheroid. We evaluated also the impact of AGuIX (Gadolinium) nanoparticles modeled into the spheroid with their corresponding secondary energy spectra. Conclusions: We succeeded into modeling cell populations and combined them with Geant4 simulations. The next step will be to integrate DNA geometrical models into cell nuclei and to use the Geant4-DNA physics and radiolysis modeling capabilities in order to evaluate early strand breaks induced on DNA.

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Development of patient-specific 3D models from histopathological samples for applications in radiation therapy

Cited by 4 publications

References 22 publications

Patient-specific microdosimetry: a proof of concept

Patient-specific microdosimetry: a proof of concept

GPU-accelerated calculation of proton microdosimetric spectra as a function of target size, proton energy, and bounding volume size

CPOP: An open source C++ cell POPulation modeler for radiation biology applications

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