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Revision as of 16:57, 10 February 2020
Home < Main Page < SlicerCommunity < 2020Go to 2022 :: 2021 :: 2020 :: 2019 :: 2018 :: 2017 :: 2016 :: 2015 :: 2014-2011 :: 2010-2000
The community that relies on 3D Slicer is large and active: (numbers below updated on December 1st, 2023)
- 1,467,466+ downloads in the last 11 years (269,677 in 2023, 206,541 in 2022)
- over 17.900+ literature search results on Google Scholar
- 2,147+ papers on PubMed citing the Slicer platform paper
- Fedorov A., Beichel R., Kalpathy-Cramer J., Finet J., Fillion-Robin J-C., Pujol S., Bauer C., Jennings D., Fennessy F.M., Sonka M., Buatti J., Aylward S.R., Miller J.V., Pieper S., Kikinis R. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magnetic Resonance Imaging. 2012 Nov;30(9):1323-41. PMID: 22770690. PMCID: PMC3466397.
- 39 events in open source hackathon series continuously running since 2005 with 3260 total participants
- Slicer Forum with +8,138 subscribers has approximately 275 posts every week
The following is a sample of the research performed using 3D Slicer outside of the group that develops it. in 2020
We monitor PubMed and related databases to update these lists, but if you know of other research related to the Slicer community that should be included here please email: marianna (at) bwh.harvard.edu.
Contents
- 1 2020
- 1.1 Temporomandibular Joint Damage in K/BxN Arthritic Mice
- 1.2 Synchrotron Radiation-Based Reconstruction of the Human Spiral Ganglion: Implications for Cochlear Implantation
- 1.3 Visualization of Mucosal Field in HPV Positive and Negative Oropharyngeal Squamous Cell Carcinomas: Combined Genomic and Radiology Based 3D Model
- 1.4 Using of a Dismountable 3D-model of the Collecting System with Color Segmentation to Improve the Learning Curve of Residents
- 1.5 Manual and Semiautomatic Segmentation of Bone Sarcomas on MRI Have High Similarity
- 1.6 Measurement Error and Reliability of Three Available 3D Superimposition Methods in Growing Patients
- 1.7 Prostate Multiparametric Magnetic Resonance Imaging Features Following Partial Gland Cryoablation
- 1.8 3D Printing Method For Next-Day Acetabular Fracture Surgery Using A Surface Filtering Pipeline: Feasibility And 1-Year Clinical Results
- 1.9 Convolutional Neural Network-based MR Image Analysis for Alzheimer's Disease Classification
2020
Temporomandibular Joint Damage in K/BxN Arthritic Mice
Publication: Int J Oral Sci. 2020 Feb 6;12(1):5. PMID: 32024813 | PDF Authors: Kuchler-Bopp S, Mariotte A, Strub M, Po C, De Cauwer A, Schulz G, Van Bellinghen X, Fioretti F, Clauss F, Georgel P, Benkirane-Jessel N, Bornert F. Institution: INSERM (French National Institute of Health and Medical Research), UMR 1260, Regenerative NanoMedicine (RNM), FMTS, Strasbourg, France. Abstract: Rheumatoid arthritis (RA) is an autoimmune disease affecting 1% of the world population and is characterized by chronic inflammation of the joints sometimes accompanied by extra-articular manifestations. K/BxN mice, originally described in 1996 as a model of polyarthritis, exhibit knee joint alterations. The aim of this study was to describe temporomandibular joint (TMJ) inflammation and damage in these mice. We used relevant imaging modalities, such as micro-magnetic resonance imaging (μMRI) and micro-computed tomography (μCT), as well as histology and immunofluorescence techniques to detect TMJ alterations in this mouse model. Histology and immunofluorescence for Col-I, Col-II, and aggrecan showed cartilage damage in the TMJ of K/BxN animals, which was also evidenced by μCT but was less pronounced than that seen in the knee joints. μMRI observations suggested an increased volume of the upper articular cavity, an indicator of an inflammatory process. Fibroblast-like synoviocytes (FLSs) isolated from the TMJ of K/BxN mice secreted inflammatory cytokines (IL-6 and IL-1β) and expressed degradative mediators such as matrix metalloproteinases (MMPs). K/BxN mice represent an attractive model for describing and investigating spontaneous damage to the TMJ, a painful disorder in humans with an etiology that is still poorly understood. The volume estimation and 3D reconstructions were obtained with 3D Slicer. |
Synchrotron Radiation-Based Reconstruction of the Human Spiral Ganglion: Implications for Cochlear Implantation
Publication: Ear Hear. 2020 Jan/Feb;41(1):173-81. PMID: 31008733 Authors: Li H, Schart-Morén N, Rohani SA, Ladak HM, Rask-Andersen H, Agrawal S. Institution: Department of Surgical Sciences, Head and Neck Surgery, Section of Otolaryngology, Uppsala University Hospital, Uppsala, Sweden. Abstract: OBJECTIVE: To three-dimensionally reconstruct Rosenthal's canal (RC) housing the human spiral ganglion (SG) using synchrotron radiation phase-contrast imaging (SR-PCI). Straight cochlear implant electrode arrays were inserted to better comprehend the electro-cochlear interface in cochlear implantation (CI). DESIGN: SR-PCI was used to reconstruct the human cochlea with and without cadaveric CI. Twenty-eight cochleae were volume rendered, of which 12 underwent cadaveric CI with a straight electrode via the round window (RW). Data were input into the 3D Slicer software program and anatomical structures were modeled using a threshold paint tool. RESULTS: The human RC and SG were reproduced three-dimensionally with artefact-free imaging of electrode arrays. The anatomy of the SG and its relationship to the sensory organ (Corti) and soft and bony structures were assessed. CONCLUSIONS: SR-PCI and computer-based three-dimensional reconstructions demonstrated the relationships among implanted electrodes, angular insertion depths, and the SG for the first time in intact, unstained, and nondecalcified specimens. This information can be used to assess stimulation strategies and future electrode designs, as well as create place-frequency maps of the SG for optimal stimulation strategies of the human auditory nerve in CI. |
Visualization of Mucosal Field in HPV Positive and Negative Oropharyngeal Squamous Cell Carcinomas: Combined Genomic and Radiology Based 3D Model
Publication: Sci Rep. 2020 Jan 8;10(1):40. PMID: 31913295 | PDF Authors: Orosz E, Gombos K, Petrevszky N, Csonka D, Haber I, Kaszas B, Toth A, Molnar K, Kalacs K, Piski Z, Gerlinger I, Burian A, Bellyei S, Szanyi I. Institution: University of Pécs, Medical School, Department of Otorhinolaryngology, Pécs, Hungary. Abstract: The aim of this study was to visualize the tumor propagation and surrounding mucosal field in radiography-based 3D model for advanced stage HNSCC and combine it with HPV genotyping and miRNA expression characterization of the visualized area. 25 patients with T1-3 clinical stage HNSCC were enrolled in mapping biopsy sampling. Biopsy samples were evaluated for HPV positivity and miR-21-5p, miR-143, miR-155, miR-221-5p expression in Digital Droplet PCR system. Significant miRNA expression differences of HPV positive tumor tissue biopsies were found for miR-21-5p, miR-143 and miR-221-5p compared to the HPV negative tumor biopsy series. Peritumoral mucosa showed patchy pattern alterations of miR-21-5p and miR-155 in HPV positive cases, while gradual change of miR-21-5p and miR-221-5p was seen in HPV negative tumors. In our study we found differences of the miRNA expression patterns among the HPV positive and negative tumorous tissues as well as the surrounding mucosal fields. The CT based 3D models of the cancer field and surrounding mucosal surface can be utilized to improve proper preoperative planning. Complex evaluation of HNSCC tissue organization field can elucidate the clinical and molecular differentiation of HPV positive and negative cases, and enhance effective organ saving therapeutic strategies. |
Using of a Dismountable 3D-model of the Collecting System with Color Segmentation to Improve the Learning Curve of Residents
Publication: Urologiia. 2020 Jan;(6):21-5. PMID: 32003162 Authors: Guliev BG, Komyakov BK, Talyshinskiy AE, Stetsik EO. Institution: Department of urology of FGBOU VO North-Western State Medical University named after I.I. Mechnikov, Saint Petersburg, Russia. Abstract: AIM: to determine the efficiency of using a non-biological dismountable 3D-model of the collecting system with color segmentation for better understanding of its anatomy by residents and to determine the optimal tactics of percutaneous nephrolithotomy (PNL). MATERIALS AND METHODS: 3D-models of the collecting system were developed based on CT data of 5 patients with staghorn stones, for whom PNL was planned. CT images were obtained in the Dicom format. RadiAnt DICOM Viewer was used for delineation and segmentation of the collecting system with 3D visualization. Using 3D Slicer v.4.8.1 software, virtual models were processed to convert DICOM files to STL format. Then, virtual color extraction of each group of calyxes was performed for convenient disassembling and intraluminal study of the anatomy of the collecting system. The final stage included the printing of each area by the method of layer-by-layer deposition using a 3D printer Picaso designer X. To assess the efficiency of the dismountable 3D-model that simulates a certain collecting system, a questionnaire was used. It allowed to evaluate the understanding of the anatomy of the collecting system by residents, as well as the ability to determine the optimal calyx for PNL by comparing the answers with the result of a survey of practicing urologists who had performed more than 50 cases. RESULTS: After studying 3D-models by residents, determination of the number of calyxes in each group was not statistically significantly different from those for practicing urologists who used CT images. The choice of the calyx for primary puncture was not different between groups. However, residents chose the calyx for additional access worse (p=0.009). CONCLUSION: The dismountable 3D-model of the collecting system is promising for training of residents and planning PNL. Studying the anatomy of a single group of calyxes as well as the entire collecting system allows to choose the optimal calyx for percutaneous puncture during PNL. |
Manual and Semiautomatic Segmentation of Bone Sarcomas on MRI Have High Similarity
Publication: Braz J Med Biol Res. 2020 Jan 31;53(2):e8962. PMID: 32022102 | PDF Authors: Dionísio FCF, Oliveira LS, Hernandes MA, Engel EE, Rangayyan RM, Azevedo-Marques PM, Nogueira-Barbosa MH. Institution: Departamento de Imagens Médicas, Hematologia e Oncologia Clínica, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brasil. Abstract: The aims of this study were to evaluate the intra- and interobserver reproducibility of manual segmentation of bone sarcomas in magnetic resonance imaging (MRI) studies and to compare manual and semiautomatic segmentation methods. This retrospective study included twelve osteosarcoma and eight Ewing sarcoma MRI studies performed prior to any therapeutic intervention. All cases were histopathologically confirmed. Three radiologists used 3D Slicer software to perform manual segmentation of bone sarcomas in a blinded and independent manner. One radiologist segmented manually and also performed semiautomatic segmentation with the GrowCut tool. Segmentation exercises were timed for comparison. The dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to evaluate similarity between the segmentation results and further statistical analyses were performed to compare DSC, HD, and volumetric results. Manual segmentation was reproducible with intraobserver DSC varying from 0.83 to 0.97 and HD from 3.37 to 28.73 mm. Interobserver DSC of manual segmentation showed variation from 0.73 to 0.97 and HD from 3.93 to 33.40 mm. Semiautomatic segmentation compared to manual segmentation resulted in DSCs of 0.71-0.96 and HDs of 5.38-31.54 mm. Semiautomatic segmentation required significantly less time compared to manual segmentation (P value ≤0.05). Among all situations compared, tumor volumetry did not show significant statistical differences (P value >0.05). We found excellent intra- and interobserver agreement for manual segmentation of osteosarcoma and Ewing sarcoma. There was high similarity between manual and semiautomatic segmentation, with a significant reduction of segmentation time using the semiautomatic method. |
Measurement Error and Reliability of Three Available 3D Superimposition Methods in Growing Patients
Publication: Head Face Med. 2020 Jan 27;16(1):1. PMID: 31987041 | PDF Authors: Ponce-Garcia C, Ruellas ACO, Cevidanes LHS, Flores-Mir C, Carey JP, Lagravere-Vich M. Institution: Division of Orthodontics, School of Dentistry, University of Alberta, Edmonton, Canada. Abstract: Cone-Beam Computed Tomography (CBCT) images can be superimposed, allowing three-dimensional (3D) evaluation of craniofacial growth/treatment effects. Limitations of 3D superimposition techniques are related to imaging quality, software/hardware performance, reference areas chosen, and landmark points/volumes identification errors. The aims of this research are to determine/compare the intra-rater reliability generated by three 3D superimposition methods using CBCT images, and compare the changes observed in treated cases by these methods. METHODS: Thirty-six growing individuals (11-14 years old) were selected from patients that received orthodontic treatment. Before and after treatment (average 24 months apart) CBCTs were analyzed using three superimposition methods. The superimposed scans with the two voxel-based methods were used to construct surface models and quantify differences using 3D SlicerCMF software, while distances in the landmark-derived method were calculated using Excel. 3D linear measurements of the models superimposed with each method were then compared. RESULTS: Repeated measurements with each method separately presented good to excellent intraclass correlation coefficient (ICC ≥ 0.825). ICC values were the lowest when comparing the landmark-based method and both voxel-based methods. Moderate to excellent agreement was observed when comparing the voxel-based methods against each other. The landmark-based method generated the highest measurement error. CONCLUSIONS: Findings indicate good to excellent intra-examiner reliability of the three 3D superimposition methods when assessed individually. However, when assessing reliability among the three methods, ICC demonstrated less powerful agreement. The measurements with two of the three methods (CMFreg/3D Slicer and Dolphin) showed similar mean differences; however, the accuracy of the results could not be determined. |
Prostate Multiparametric Magnetic Resonance Imaging Features Following Partial Gland Cryoablation
Publication: Urology. 2020 Jan 15. PMID: 31954170 Authors: Al Awamlh BAH, Margolis DJ, Gross MD, Natarajan S, Priester A, Hectors S, Ma X, Mosquera JM, Liao J, Hu JC. Institution: Division of Orthodontics, School of Dentistry, University of Alberta, Edmonton, Canada. Abstract: OBJECTIVES: To assess the qualitative and quantitative changes on prostate multiparametric magnetic resonance imaging (mpMRI) following partial gland ablation (PGA) with cryotherapy and correlate with histopathology. METHODS: We used 3D Slicer to generate prostate models and segment ipsilateral (treated) and contralateral peripheral and transition zones in ten men who underwent MRI/transrectal ultrasound fusion-guided PGA during 2017-2018. Pre and post-PGA volumes of prostate segments were compared. Post-PGA mpMRI were categorized according to PI-RADS v2 and treatment response on mpMRI was assessed in a manner similar to the radiology evaluation framework following liver lesion ablation. RESULTS: Median volume of ipsilateral peripheral and transition zones decreased from 10.9 mL and 13.0 mL to 7.2 mL and 10.8 mL (p=0.005), respectively. Median volume of contralateral peripheral and transition zones also decreased from 12.1 mL and 12.5 mL to 9.9 mL to 10.4 mL (p=0.005), respectively. Five men had clinically significant disease (Grade group ≥2) on post-PGA biopsy (three within treatment field and two outside). Of the men with clinically significant prostate cancer, mpMRI revealed PI-RADS 3 lesions in two. However, the treatment response framework did not detect residual disease. CONCLUSION: PGA results in asymmetric and significant reductions in prostate volume. Our results highlight the need for a separate assessment framework to enable standardization of the interpretation and reporting of post-PGA surveillance mpMRI. Moreover, our findings have significant implications for MRI-targeted surveillance biopsy following PGA with cryotherapy. |
3D Printing Method For Next-Day Acetabular Fracture Surgery Using A Surface Filtering Pipeline: Feasibility And 1-Year Clinical Results
Publication: Int J Comput Assist Radiol Surg. 2020 Jan 2. PMID: 31897965 Authors: Weidert S, Andress S, Linhart C, Suero EM, Greiner A, Böcker W, Kammerlander C, Becker CA. Institution: Department of General, Trauma and Reconstructive Surgery, University Hospital, LMU Munich, Campus Großhadern, Munich, Germany. Abstract: INTRODUCTION: In orthopedic surgery, 3D printing is a technology with promising medical applications. Publications show promising results in acetabular fracture surgery over the last years using 3D printing. However, only little information about the workflow and circumstances of how to properly derive the 3D printed fracture model out of a CT scan is published. MATERIALS AND METHODS: We conducted a retrospective analysis of patients with acetabular fractures in a level 1 trauma center. DICOM data were preoperatively used in a series of patients with acetabular fractures. The 3D mesh models were created using 3D Slicer with a newly introduced surface filtering method. The models were printed using PLA material with FDM printer. After reduction in the printed model, the acetabular reconstruction plate was bent preoperatively and sterilized. A clinical follow-up after 12 months in average was conducted with the patients. RESULTS: In total, 12 patients included. Mean printing time was 8:40 h. The calculated mean printing time without applying the surface filter was 25:26 h. This concludes an average printing time reduction of 65%. Mean operation time was 3:16 h, and mean blood loss was 853 ml. Model creation time was about 11 min, and mean printing time of the 3D model was 8:40 h, preoperative model reduction time was 5 min on average, and preoperative bending of the plate took about 10 min. After 12 months, patients underwent a structured follow-up. Harris Hip Score was 75.7 points, the Modified Harris Hip Score 71.6 points and the Merle d'Aubigne Score 11.1 points on average. CONCLUSIONS: We presented the first clinical practical technique to use 3D printing in acetabular fracture surgery. By introducing a new surface filtering pipeline, we reduced printing time and cost compared to the current literature and the state of the art. Low costs and easy handling of the 3D printing workflow make it usable in nearly every hospital setting for acetabular fracture surgery. Funding:
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Convolutional Neural Network-based MR Image Analysis for Alzheimer's Disease Classification
Publication: Curr Med Imaging Rev. 2020;16(1):27-35. PMID: 31989891 Authors: Choi BK, Madusanka N, Choi HK, So JH, Kim CH, Park HG, Bhattacharjee S, Prakash D. Institution: Department of Digital Anti-Aging Healthcare, u-AHRC, Inje University, Gimhae, Korea. Abstract: BACKGROUND: In this study, we used a convolutional neural network (CNN) to classify Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal control (NC) subjects based on images of the hippocampus region extracted from magnetic resonance (MR) images of the brain. METHODS: The datasets used in this study were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). To segment the hippocampal region automatically, the patient brain MR images were matched to the International Consortium for Brain Mapping template (ICBM) using 3D-Slicer software. Using prior knowledge and anatomical annotation label information, the hippocampal region was automatically extracted from the brain MR images. RESULTS: The area of the hippocampus in each image was preprocessed using local entropy minimization with a bi-cubic spline model (LEMS) by an inhomogeneity intensity correction method. To train the CNN model, we separated the dataset into three groups, namely AD/NC, AD/MCI, and MCI/NC. The prediction model achieved an accuracy of 92.3% for AD/NC, 85.6% for AD/MCI, and 78.1% for MCI/NC. CONCLUSION: The results of this study were compared to those of previous studies, and summarized and analyzed to facilitate more flexible analyses based on additional experiments. The classification accuracy obtained by the proposed method is highly accurate. These findings suggest that this approach is efficient and may be a promising strategy to obtain good AD, MCI and NC classification performance using small patch images of hippocampus instead of whole slide images. |