Im2mesh: A Python Library to Reconstruct 3D Meshes from Scattered Data and 2D Segmentations, Application to Patient-Specific Neuroblastoma Tumour Image Sequences

The future of personalised medicine lies in the development of increasingly sophisticated digital twins, where the patient-specific data is fed into predictive computational models that support the decisions of clinicians on the best therapies or course actions to treat the patient’s afflictions. Th...

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Vydané v:	Applied sciences Ročník 12; číslo 22; s. 11557
Hlavní autori:	Sainz-DeMena, Diego, García-Aznar, José Manuel, Pérez, María Ángeles, Borau, Carlos
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.11.2022
Predmet:	Algorithms Artificial intelligence Cancer Decision making Decision support systems Geometry Growth models Magnetic resonance imaging medical image Medical imaging mesh generation Neuroblastoma patient-specific computational modelling Precision medicine python library slice interpolation Software Tomography
ISSN:	2076-3417, 2076-3417
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Abstract	The future of personalised medicine lies in the development of increasingly sophisticated digital twins, where the patient-specific data is fed into predictive computational models that support the decisions of clinicians on the best therapies or course actions to treat the patient’s afflictions. The development of these personalised models from image data requires a segmentation of the geometry of interest, an estimation of intermediate or missing slices, a reconstruction of the surface and generation of a volumetric mesh and the mapping of the relevant data into the reconstructed three-dimensional volume. There exist a wide number of tools, including both classical and artificial intelligence methodologies, that help to overcome the difficulties in each stage, usually relying on the combination of different software in a multistep process. In this work, we develop an all-in-one approach wrapped in a Python library called im2mesh that automatizes the whole workflow, which starts reading a clinical image and ends generating a 3D finite element mesh with the interpolated patient data. In this work, we apply this workflow to an example of a patient-specific neuroblastoma tumour. The main advantages of our tool are its straightforward use and its easy integration into broader pipelines.
AbstractList	The future of personalised medicine lies in the development of increasingly sophisticated digital twins, where the patient-specific data is fed into predictive computational models that support the decisions of clinicians on the best therapies or course actions to treat the patient’s afflictions. The development of these personalised models from image data requires a segmentation of the geometry of interest, an estimation of intermediate or missing slices, a reconstruction of the surface and generation of a volumetric mesh and the mapping of the relevant data into the reconstructed three-dimensional volume. There exist a wide number of tools, including both classical and artificial intelligence methodologies, that help to overcome the difficulties in each stage, usually relying on the combination of different software in a multistep process. In this work, we develop an all-in-one approach wrapped in a Python library called im2mesh that automatizes the whole workflow, which starts reading a clinical image and ends generating a 3D finite element mesh with the interpolated patient data. In this work, we apply this workflow to an example of a patient-specific neuroblastoma tumour. The main advantages of our tool are its straightforward use and its easy integration into broader pipelines.
Author	Sainz-DeMena, Diego García-Aznar, José Manuel Borau, Carlos Pérez, María Ángeles
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Cites_doi	10.1145/2487228.2487237 10.1016/B978-0-12-823299-6.00001-8 10.1049/ipr2.12419 10.1101/2021.03.03.433731 10.1186/s41747-021-00214-4 10.1007/s00276-012-0985-0 10.1088/1361-6560/aac040 10.1007/s00330-021-08431-6 10.1007/s10278-013-9622-7 10.1038/s41592-019-0686-2 10.1109/ISBI.2019.8759500 10.1109/TBME.2008.921158 10.1111/1467-8659.00334 10.1016/j.fertnstert.2018.05.006 10.1109/ISBI.2018.8363819 10.1109/AIPR52630.2021.9762167 10.1118/1.4898202 10.1016/j.ymeth.2020.02.010 10.1101/2022.09.26.509452 10.1593/tlo.13130 10.1145/258734.258849 10.1590/0100-3984.2019.0049 10.3389/fphys.2018.01246 10.1007/978-3-540-40899-4_19 10.2172/901967 10.1145/1278780.1278807 10.1111/ene.14294 10.1016/j.mri.2012.05.001 10.1016/j.nicl.2018.08.032 10.1002/nme.2579
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References	Ronneberger (ref_17) 2015; 9 Amorim (ref_35) 2012; 30 Clark (ref_40) 2013; 26 Khalifa (ref_33) 2014; 41 Grignon (ref_3) 2012; 34 ref_14 ref_36 ref_13 Albu (ref_18) 2008; 55 ref_31 Angeli (ref_10) 2018; 20 ref_19 Ladenstein (ref_21) 2020; 4 ref_39 Santos (ref_2) 2019; 52 ref_38 ref_15 Vollmer (ref_29) 1999; 18 ref_37 Atuegwu (ref_32) 2013; 6 Kazhdan (ref_27) 2013; 32 Hadjicharalambous (ref_6) 2020; 185 Geuzaine (ref_30) 2009; 79 Scapicchio (ref_22) 2021; 5 Goetz (ref_1) 2018; 109 Virtanen (ref_34) 2020; 17 Bradski (ref_23) 2000; 25 ref_25 Jarrett (ref_11) 2018; 63 Wang (ref_16) 2020; 16 Schenk (ref_24) 2000; 1935 Sturchio (ref_4) 2020; 27 ref_28 (ref_5) 2018; 9 Fedorov (ref_20) 2012; 30 ref_26 ref_9 ref_8 Gabelloni (ref_12) 2022; 32 ref_7
References_xml	– volume: 32 start-page: 1 year: 2013 ident: ref_27 article-title: Screened poisson surface reconstruction publication-title: ACM Trans. Graph. doi: 10.1145/2487228.2487237 – volume: 30 start-page: 687 year: 2012 ident: ref_35 article-title: InVesalius—An open-sourceimaging application publication-title: World J. Urol. – ident: ref_13 doi: 10.1016/B978-0-12-823299-6.00001-8 – volume: 16 start-page: 1243 year: 2020 ident: ref_16 article-title: Medical image segmentation using deep learning: A survey publication-title: IET Image Process. doi: 10.1049/ipr2.12419 – ident: ref_9 – ident: ref_8 doi: 10.1101/2021.03.03.433731 – volume: 5 start-page: 1 year: 2021 ident: ref_22 article-title: DICOM-MIABIS integration model for biobanks: A use case of the EU PRIMAGE project publication-title: Eur. Radiol. Exp. doi: 10.1186/s41747-021-00214-4 – volume: 34 start-page: 675 year: 2012 ident: ref_3 article-title: Recent advances in medical imaging: Anatomical and clinical applications publication-title: Surg. Radiol. Anat. doi: 10.1007/s00276-012-0985-0 – volume: 63 start-page: 105015 year: 2018 ident: ref_11 article-title: Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: Theory and preliminary clinical results publication-title: Phys. Med. Biol. doi: 10.1088/1361-6560/aac040 – volume: 32 start-page: 3173 year: 2022 ident: ref_12 article-title: Bridging gaps between images and data: A systematic update on imaging biobanks publication-title: Eur. Radiol. doi: 10.1007/s00330-021-08431-6 – volume: 4 start-page: 1 year: 2020 ident: ref_21 article-title: PRIMAGE project: Predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers publication-title: Eur. Radiol. Exp. – ident: ref_39 – ident: ref_37 – volume: 26 start-page: 1045 year: 2013 ident: ref_40 article-title: The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository publication-title: J. Digit. Imaging doi: 10.1007/s10278-013-9622-7 – volume: 17 start-page: 261 year: 2020 ident: ref_34 article-title: SciPy 1.0 Contributors. SciPy 1.0 Fundamental Algorithms for Scientific Computing in Python publication-title: Nat. Methods doi: 10.1038/s41592-019-0686-2 – ident: ref_15 doi: 10.1109/ISBI.2019.8759500 – volume: 55 start-page: 2022 year: 2008 ident: ref_18 article-title: A Morphology-Based Approach for Interslice Interpolation of Anatomical Slices from Volumetric Images publication-title: IEEE Trans. Biomed. Eng. doi: 10.1109/TBME.2008.921158 – volume: 18 start-page: 131 year: 1999 ident: ref_29 article-title: Improved Laplacian Smoothing of Noisy Surface Meshes publication-title: Comput. Graph. Forum doi: 10.1111/1467-8659.00334 – volume: 109 start-page: 952 year: 2018 ident: ref_1 article-title: Personalized medicine: Motivation, challenges, and progress publication-title: Fertil. Steril. doi: 10.1016/j.fertnstert.2018.05.006 – ident: ref_25 – ident: ref_14 doi: 10.1109/ISBI.2018.8363819 – volume: 25 start-page: 120 year: 2000 ident: ref_23 article-title: The OpenCV library publication-title: Dr. Dobb’s J. – ident: ref_19 doi: 10.1109/AIPR52630.2021.9762167 – volume: 41 start-page: 124301 year: 2014 ident: ref_33 article-title: Models and methods for analyzing DCE-MRI: A review publication-title: Med. Phys. doi: 10.1118/1.4898202 – volume: 185 start-page: 82 year: 2020 ident: ref_6 article-title: From tumour perfusion to drug delivery and clinical translation of in silico cancer models publication-title: Methods doi: 10.1016/j.ymeth.2020.02.010 – ident: ref_7 doi: 10.1101/2022.09.26.509452 – volume: 6 start-page: 256 year: 2013 ident: ref_32 article-title: Parameterizing the Logistic Model of Tumor Growth by DW-MRI and DCE-MRI Data to Predict Treatment Response and Changes in Breast Cancer Cellularity during Neoadjuvant Chemotherapy publication-title: Transl. Oncol. doi: 10.1593/tlo.13130 – ident: ref_28 doi: 10.1145/258734.258849 – volume: 52 start-page: 387 year: 2019 ident: ref_2 article-title: Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: Advances in imaging towards to precision medicine publication-title: Radiol. Bras. doi: 10.1590/0100-3984.2019.0049 – ident: ref_38 – ident: ref_36 – volume: 9 start-page: 1246 year: 2018 ident: ref_5 article-title: Integration of in vitro and in silico models using Bayesian optimization with an application to stochastic modeling of mesenchymal 3D cell migration publication-title: Front. Physiol. doi: 10.3389/fphys.2018.01246 – volume: 1935 start-page: 186 year: 2000 ident: ref_24 article-title: Efficient semiautomatic segmentation of 3D objects in medical images publication-title: Lect. Notes Comput. Sci. doi: 10.1007/978-3-540-40899-4_19 – ident: ref_31 doi: 10.2172/901967 – ident: ref_26 doi: 10.1145/1278780.1278807 – volume: 27 start-page: 1461 year: 2020 ident: ref_4 article-title: How have advances in genetic technology modified movement disorder nosology? publication-title: Eur. J. Neurol. doi: 10.1111/ene.14294 – volume: 30 start-page: 1323 year: 2012 ident: ref_20 article-title: 3D Slicer as an image computing platform for the Quantitative Imaging Network publication-title: Magn. Reson. Imaging doi: 10.1016/j.mri.2012.05.001 – volume: 9 start-page: 16591 year: 2015 ident: ref_17 article-title: U-Net: Convolutional Networks for Biomedical Image Segmentation publication-title: IEEE Access – volume: 20 start-page: 664 year: 2018 ident: ref_10 article-title: Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI publication-title: NeuroImage Clin. doi: 10.1016/j.nicl.2018.08.032 – volume: 79 start-page: 1309 year: 2009 ident: ref_30 article-title: Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities publication-title: Int. J. Numer. Methods Eng. doi: 10.1002/nme.2579
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SubjectTerms	Algorithms Artificial intelligence Cancer Decision making Decision support systems Geometry Growth models Magnetic resonance imaging medical image Medical imaging mesh generation Neuroblastoma patient-specific computational modelling Precision medicine python library slice interpolation Software Tomography
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Title	Im2mesh: A Python Library to Reconstruct 3D Meshes from Scattered Data and 2D Segmentations, Application to Patient-Specific Neuroblastoma Tumour Image Sequences
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