Table 1.
List of pediatric whole-body models currently available.
Fig 1.
Structural MRI and CT scans used for segmentation.
Several sequences with different resolution and contrast were used for the segmentation of different tissues. For example, MPRAGE, a T1 weighted image, was useful for the segmentation of brain structures while T2 Flair was used for the segmentation of the arteries and veins of the brain and Radial VIBE with a gadolinium-based contrast was used for the segmentation for the vessels of the lower extremities. CT was used for the segmentation of the cortical bone of the pelvis and the core, as well as the base of the skull. Inversion Recovery was useful for the segmentation of the CSF and the Vitreous body of the eyes. HASTE was initially for segmenting the kidneys and the CSF of the spinal cord as well. T2 Fast Spin Echo offered a good outline of the anatomy of the intervertebral disc. All the different tissues were finally referred to the whole body T1 space, while T1 was used for their manual refinement.
Fig 2.
Flow chart–process of the segmentation.
The first step was to select a male patient with available whole-body sequences without major deformities as well as multiple sequences that would facilitate the segmentation process. We then pulled all the available MRI and CT scans from the database of the Boston Children’s Hospital. The meticulous process of the segmentation of the different tissues of the body was slightly differentiated for the brain and the non-brain tissues. For the segmentation of the brain structures, an automated infant-specific data processing framework was used, and the result was reviewed by two subspecialized neuroradiologists. Non-brain tissues were segmented using different sequences by two MDs, and the volumes and the weights of the segmented tissues were compared with the values from the literature. When the agreement was achieved between the operators and the tissues were aligned with the surrounded segmented tissues, the two sub-specialty certified neuroradiologists confirmed the result following a “pass or fail” process through an interactive process. The tissues that were scored with a “pass” were then finalized. Given that gradually more and more tissues were added to the segmentation project, some of which were not available when the first of the tissues were segmented and finalized, all the tissues were put together in the reference T1 sequence, and the model was again confirmed by the two neuroradiologists.
Table 2.
MRI and CT sequence parameters that were used for segmentation.
Fig 3.
Coronal view of the co-registered MRI and CT Flash neck. The contrast of skull and bone, e.g., vertebrae, ribcage, was higher in CT, while the brain, e.g., WM, GM, was enhanced in MRI.
Fig 4.
3D surfaces of the brain and its subcortical areas (created by automatic segmentation algorithm).
1) Left-Cerebral-Cortex, 2) Left-Cerebellum-Cortex, 3) Left-Thalamus, 4) Left-Caudate, 5) Left-Cerebral-White-Matter, 6) Lateral ventricle, 7) Left-Accumbens-area, 8)Left-Putamen, 9)Left-Amygdala, 10) Left-Hippocampus, 11) Pons, 12) Medulla, 13) Left-Pallidum, 14) Vermis, 15) Left-Cerebellum-White-Matter, 16) 3rd-Ventricle, 17) Left-Ventral diencephalon (DC), 18) Midbrain, 19) 4th Ventricle. See S1 Table in S1 File for the list of tissues segmented by an automatic segmentation algorithm [42].
Fig 5.
Outlining the cortical bone segmentation process from CT.
(a) coronal section of the CT centered on the hips and pelvis, (b) the results of the semi-automatic threshold-based segmentation of the cortical bone (step ii), (c) the results of smoothing with a median filter with a kernel size of 5mm (step iii), and (d) the final segmentation result after manual refinement of the cortical bone (step iv).
Fig 6.
Segmentation of brain structures (manual refinement of automatic segmentation) and vessels.
(a.) Axial, (b) sagittal, and (c) coronal views of the brain structures segmentations displayed on the MPRAGE. (d) and (e) show 3D surfaces of the brain and subcortical areas, respectively. Structures of interest: 1. Brain Grey Matter; 2. Brain White matter; 3, Caudate; 4. Lateral Ventricles; 5. Septum Pellucidum; 6. Internal capsule; 7. External Capsule; 8. Putamen; 9. Globus Pallidus; 10. Thalamus; 11. Cerebral Vein; 12. Cerebral Artery; 13b. Optic nerves; 13c. Optic nerves; 14. Hypothalamus and chiasm; 15. Mamillary bodies; 16. Epiphysis; 17. Ventral Diencephalon; 18. Midbrain; 19. Pons; 20. Medulla; 21. Vermis (Gray Matter); 22. Cerebellum White Matter; 23. Cerebellum Gray Matter; 24. Pituitary; 25. Nucleus Accumbens; 26. 4th Ventricle; 27. 3rd Ventricle; 28: Amygdala.
Fig 7.
Segmentation of the spinal cord and vertebrae.
(a) Sagittal view of the CT image used for the segmentation of the vertebrae. Arrows on the right were pointing anatomical structures included in the image and represented in the 3D reconstruction while anatomical locations were also marked on the left side. (b) Coronal view of the T2 image used to segment the intervertebral disks and the vertebral bone marrow, as shown with the 3D reconstruction on the right side. (c) Sagittal view of the IR used to delineate the spinal cord and the surrounding cerebrospinal fluid (CSF).
Fig 8.
Vessel segmentation in 3D representation.
a. Large arteries of the legs and their main branches. i. External Iliac Artery and vein, ii. Deep Femoral Artery and Vein of the thigh, iii. Femoral Artery and Vein, iv. Popliteal Artery, v. Peroneal vessels, vi. Anterior tibial vessels, vii. Great Saphenous Vein, viii. Lesser saphenous vein. b. Proximal large veins (blue) and arteries (red) of the brain and neck: 1. Superior Sagittal Sinus, 2. Internal Cerebral Vein, 3. Vein of Galen, 4. Straight Sinus, 5. Transverse Sinus, 6. Sigmoid Sinus, 7. Torcula, 8. Basal Vein of Rosenthal, 9. Internal Jugular Vein, 10.Vertebral Artery, 11. Basilar Artery, 12. Internal Carotid Artery, 13. Middle Cerebral Artery and main branches, 14. Anterior Cerebral Artery and main branches, 15. Posterior Cerebral Artery, 16. Arteries of the neck.
Fig 9.
Coronal view of the whole-body segmentation.
1. Cerebrospinal Fluid, 2. Superior Sagittal Sinus, 3. Transverse sinus, 4. Air in the Mastoid, 5. Brain Grey Matter, 6. Brain White Matte, 7. Cerebellum White Matter, 8. Cerebellum Gray Matter, 9. Vermis, 10. Thalamus, 11. Hippocampus, 12. Skull, 13. Vertebrae, 14. Intervertebral Disc, 15. Humerus Cartilage, 16. Humerus Bone, 17. Humerus Bone Marrow, 18. Radius, 19. Ulna, 20. Metacarpal bone, 21. Proximal Phalanges, 22. Femur Bone Marrow, 23. Femur Bone, 24. Tibia, 25. Trachea, 26. Esophagus, 27. Aortic trunk, 28. Lungs, 29. Heart, 30. Liver, 31. Gallbladder, 32. Pancreas, 33. Stomach, 34. Large Intestines, 35. Small Intestines, 36. Air in the Small Intestines, 37. Intra-abdominal fat, 38. Bladder, 39.Penis (Corpus cavernosum, Corpus spongiosum), 40.Testis, 41.Vessels of lower extremities, 42.Fat, 43.Connective Tissues, 44.Muscle, 45.Skin, 46.Subcutaneous Fat, 47.Secondary Ossification Center, 48. Spleen, 49. Meninges.
Fig 10.
(Top) Example of variability among segmentor A (red), B (green), and C (yellow) for a few representative structures in the body. (Bottom) Box plots of the values of DSC and Hausdorff distance for the 11 structures were included in the analysis. The variabilities were assessed by comparing each segmentation with a ground truth obtained via two CAQ subspecialized neuro-radiologists.
Fig 11.
The MARTIN pediatric model with head birdcage coil in 1.5 T.
The head of the model is positioned at the center of the high-pass birdcage coil tuned at 1.5 T.
Fig 12.
The MARTIN pediatric model with the position of the VNS.
(a) pulse generator (IPG), (b) Vagus nerve, (c) lead, (d) Electrodes, (e) insulation (bottom).
Table 3.
List of all tissue segmented.
Table 4.
Validation table (absolute value of the difference between the measured value and literature value).
Fig 13.
(a) shows the axial view of the Inversion Recovery used in segmentation, (b) shows the results of Bloch simulation, SYSSIM, using proposed voxel model, (c) shows the overlay between MRI image ((a), in grayscale) and SYSSIM ((b), in colormap scale).
Table 5.
Inter-operator variability across structures on the coronal slices.
Fig 14.
a) Maximum intensity projection of 10gSAR without an implant in 3D view and the coronal, sagittal, and axial view, b) Maximum intensity projection of 10g averaged SAR in the case of a VNS implant in 3D view, and the coronal, sagittal, and axial view (*EM simulation results were averaged to 2μT at the coil center [82]).
Table 6.
Dielectric properties of 29-month-old at 1.5T and 3T.
Table 7.
Specific absorption rate and 10g averaged rms E-field results of Nina and MARTIN at 1.5T using Tx/Rx head coil.