DISCOVERIES (ISSN 2359-7232), 2016, October-December issue

CITATION: 

Submitted: December 6th, 2016; Revised: December 29th, 2016; Accepted: December 29th, 2016; Published: December 31st, 2016;

 GO BACK to 2016, October-December issue

 GO BACK to DISCOVERIES

Acquisition, Visualization and Potential Applications of 3D Data in Anatomic Pathology

Shyam Prajapati*, Emilio Madrigal, Mark T. Friedman

Mount Sinai Health System, Department of Diagnostic Pathology and Laboratory Medicine, New York, NY, USA

*Correspondence to: Shyam Prajapati, DO, Mount Sinai West, Diagnostic Pathology & Laboratory Medicine, 1000 Tenth Ave, New York, NY, 10019, USA

Abstract

Although human anatomy and histology are naturally three-dimensional (3D), commonly used diagnostic and educational tools are technologically restricted to providing two-dimensional representations (e.g. gross photography and glass slides). This limitation may be overcome by employing techniques to acquire and display 3D data, which refers to the digital information used to describe a 3D object mathematically. There are several established and experimental strategies to capture macroscopic and microscopic 3D data. In addition, recent hardware and software innovations have propelled the visualization of 3D models, including virtual and augmented reality. Accompanying these advances are novel clinical and non-clinical applications of 3D data in pathology. Medical education and research stand to benefit a great deal from utilizing 3D data as it can change our understanding of complex anatomical and histological structures. Although these technologies are yet to be adopted in routine surgical pathology, forensic pathology has embraced 3D scanning and model reconstruction. In this review, we intend to provide a general overview of the technologies and emerging applications involved with 3D data.

Access full text of the manuscript here: Full text (pdf)

References

1. McHenry K, Bajcsy P. An overview of 3d data content, file formats and viewers. National Center for Supercomputing Applications. 2008 Oct 31;1205.

2. Zhang Q, Eagleson R, Peters TM. Volume visualization: a technical overview with a focus on medical applications. Journal of digital imaging. 2011 Aug 1;24(4):640-64.

3. Sansoni G, Trebeschi M, Docchio F. State-of-the-art and applications of 3D imaging sensors in industry, cultural heritage, medicine, and criminal investigation. Sensors. 2009 Jan 20;9(1):568-601.

4. Preim B, Botha CP. Visual Computing for Medicine: Theory, Algorithms, and Applications. Newnes; 2013 Nov 7.

5. Damstra J, Fourie Z, Slater JJ, Ren Y. Accuracy of linear measurements from cone-beam computed tomography-derived surface models of different voxel sizes. American Journal of Orthodontics and Dentofacial Orthopedics. 2010 Jan 31;137(1):16-e1.

6. Furuya K, Maeda T, Nakanura S, Kikuchi T. The role of computer-aided 3-dimensional analytic tools and virtual microscopy in the investigation of radiologic-pathologic correlation. Archives of pathology & laboratory medicine. 2009 Jun;133(6):912-5.

7. Zhang, Longyu, Haiwei Dong, and Abdulmotaleb El Saddik. "From 3D sensing to printing: a survey." ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 12.2 (2016): 27.

8. Ourselin S, Roche A, Subsol G, Pennec X, Ayache N. Reconstructing a 3D structure from serial histological sections. Image and vision computing. 2001 Jan 31;19(1):25-31.

9. Song Y, Treanor D, Bulpitt AJ, Magee DR. 3D reconstruction of multiple stained histology images. Journal of pathology informatics. 2013 Jan 1;4(2):7.

10. Magee D, Song Y, Gilbert S, Roberts N, Wijayathunga N, Wilcox R, Bulpitt A, Treanor D. Histopathology in 3D: From three-dimensional reconstruction to multi-stain and multi-modal analysis. Journal of pathology informatics. 2015;6.

11. Hashimoto, Noriaki et al. "Development of a 2D Image Reconstruction and Viewing System for Histological Images from Multiple Tissue Blocks: Towards High-Resolution Whole-Organ 3D Histological Images." Pathobiology 83.2-3 (2016): 127-139.

12. Ritman EL. Current status of developments and applications of micro-CT. Annual review of biomedical engineering. 2011 Aug 15; 13:531-52.

13. Olson E, Levene MJ, Torres R. Multiphoton microscopy with clearing for three dimensional histology of kidney biopsies. Biomedical Optics Express. 2016 Aug 1;7(8):3089-96.

14. Hariri LP, Mino-Kenudson M, Mark EJ, Suter MJ. In vivo optical coherence tomography: the role of the pathologist. Archives of pathology & laboratory medicine. 2012 Dec;136(12):1492-501.

15. Coldewey, D. (2010, June 19). A guide to 3D display technology: its principles, methods, and dangers. CrunchGear. Retrieved Nov.20, 2016, from 

http://www.crunchgear.com/2010/06/19/a-guide-to-3d-display-technology-its-principles

methods-and-dangers/

16. Falah J, Khan S, Alfalah T, Alfalah SF, Chan W, Harrison DK, Charissis V. Virtual Reality medical training system for anatomy education. InScience and Information Conference (SAI), 2014 2014 Aug 27 (pp. 752-758). IEEE.

17. Madrigal E, Prajapati S, Hernandez-Prera JC. Introducing a Virtual Reality Experience in Anatomic Pathology Education. American Journal of Clinical Pathology. 2016 Oct 1;146(4):462-8.

18. Mitsouras D, Liacouras P, Imanzadeh A, Giannopoulos AA, Cai T, Kumamaru KK, George E, Wake N, Caterson EJ, Pomahac B, Ho VB. Medical 3D printing for the radiologist. RadioGraphics. 2015 Nov 12;35(7):1965-88.

19. Prajapati S, Madrigal, E. (2016, October). (Virtual) Reality Check. The Pathologist. Retrieved November 29, 2016, from https://thepathologist.com/issues/0916/virtual-reality-check/

20. Petersson H, Sinkvist D, Wang C, Smedby Ö. Web‐based interactive 3D visualization as a tool for improved anatomy learning. Anatomical sciences education. 2009 Mar 1;2(2):61-8.

21. Miller M. Use of computer‐aided holographic models improves performance in a cadaver dissection‐based course in gross anatomy. Clinical Anatomy. 2016 Oct 1;29(7):917-24.

22. Cevidanes LH, Ruellas AC, Jomier J, Nguyen T, Pieper S, Budin F, Styner M, Paniagua B. Incorporating 3-dimensional models in online articles. American Journal of Orthodontics and Dentofacial Orthopedics. 2015 May 31;147(5): S195-204.

23. Brown PM, Hamilton NM, Denison AR. A novel 3D stereoscopic anatomy tutorial. The clinical teacher. 2012 Feb 1;9(1):50-3.

24. Hackett M, Proctor M. Three-Dimensional Display Technologies for Anatomical Education: A Literature Review. Journal of Science Education and Technology. 2016 Apr:1-4.

25. Mahmoud A, Bennett M. Introducing 3-dimensional printing of a human anatomic pathology specimen: potential benefits for undergraduate and postgraduate education and anatomic pathology practice. Archives of pathology & laboratory medicine. 2015 Aug;139(8):1048-51.

26. Di Tommaso L, Tresoldi D, Destro A, Comi P, Morbiducci U, Roncalli M, Rizzo G. A 3-D study of capsular invasion in follicular thyroid tumor. A novel approach to an old dilemma. Pathologica, 2010; 102: 93-95.

27. Asioli S, Eusebi V, Gaetano L, Losi L, Bussolati G. The pre-lymphatic pathway, the rooths of the lymphatic system in breast tissue: a 3D study. Virchows Archiv. 2008 Oct 1;453(4):401-6.

28. Yelnik J, Bardinet E, Dormont D, Malandain G, Ourselin S, Tandé D, Karachi C, Ayache N, Cornu P, Agid Y. A three-dimensional, histological and deformable atlas of the human basal ganglia. I. Atlas construction based on immunohistochemical and MRI data. Neuroimage. 2007 Jan 15;34(2):618-38.

29. Lotz JM, Hoffmann F, Lotz J, Heldmann S, Trede D, Oetjen J, Becker M, Ernst G, Maas P, Alexandrov T, Guntinas-Lichius O. Integration of 3D multimodal imaging data of a head and neck cancer and advanced feature recognition. Biochimica et Biophysica Acta (BBA)-Proteins and Proteomics. 2016 Sep 1.

30. Bucur O, Irshad H, Montaser-Kouhsari L, Knoblauch NW, Oh EY, Nowak J, Beck AH. 3D morphological hallmarks of breast carcinogenesis: Diagnosis of non-invasive and invasive breast cancer with Lightsheet microscopy. Cancer Research. 2015 Aug 1;75(15 Supplement):3477.

31. Maruyama S, Shimazu Y, Kudo T, Sato K, Yamazaki M, Abé T, Babkair H, Cheng J, Aoba T, Saku T. Three‐dimensional visualization of perlecan‐rich neoplastic stroma induced concurrently with the invasion of oral squamous cell carcinoma. Journal of Oral Pathology & Medicine. 2014 Sep 1;43(8):627-36. 

32. Wentzensen N, Braumann UD, Einenkel J, Horn LC, von Knebel Doeberitz M, Löffler M, Kuska JP. Combined serial section-based 3D reconstruction of cervical carcinoma invasion using H&E/p161NK4a/ CD3 alternate staining. Cytometry A. 2007; 71:327–33.

33. Brown PJ, Toh EW, Smith KJ, Jones P, Treanor D, Magee D, Burke D, Quirke P. New insights into the lymphovascular microanatomy of the colon and the risk of metastases in pT1 colorectal cancer obtained with quantitative methods and three‐dimensional digital reconstruction. Histopathology. 2015 Aug 1;67(2):167-75.

34. Ghaznavi F, Evans A, Madabhushi A, Feldman M. Digital imaging in pathology: whole-slide imaging and beyond. Annual Review of Pathology: Mechanisms of Disease. 2013 Jan 24;8:331-59.

35. Veta M, Pluim JP, van Diest PJ, Viergever MA. Breast cancer histopathology image analysis: A review. IEEE Transactions on Biomedical Engineering. 2014 May;61(5):1400-11.

36. Huisman A, Ploeger LS, Dullens HF, Poulin N, Grizzle WE, van Diest PJ. Development of 3D chromatin texture analysis using confocal laser scanning microscopy. Analytical Cellular Pathology. 2005;27(5-6):335-45

37. Kim TY, Cho NH, Jeong GB, Bengtsson E, Choi HK. 3D texture analysis in renal cell carcinoma tissue image grading. Computational and mathematical methods in medicine. 2014 Oct 9;2014.

38. Depeursinge A, Foncubierta-Rodriguez A, Van De Ville D, Müller H. Three-dimensional solid texture analysis in biomedical imaging: Review and opportunities. Medical image analysis. 2014 Jan 31;18(1):176-96.

39. Long F, Zhou J, Peng H. Visualization and analysis of 3D microscopic images. PLoS Comput Biol. 2012 Jun 14;8(6):e1002519.

40. Farahani N, Post R, Duboy J, Ahmed I, Kolowitz BJ, Krinchai T, Monaco SE, Fine JL, Hartman DJ, Pantanowitz L. Exploring virtual reality technology and the Oculus Rift for the examination of digital pathology slides. Journal of pathology informatics. 2016;7.

41. Thali MJ, Braun M, Buck U, et al. VIRTOPSY: scientific documentation, reconstruction and animation in forensics: individual and real 3D data based geometric approach including optical body/object surface and radiological CT/MRI scanning. J Forensic Sci 2005;50:428–442.

42. Thali MJ, Jackowski C, Oesterhelweg L, Ross SG, Dirnhofer R. VIRTOPSY–the Swiss virtual autopsy approach. Legal Medicine. 2007 Mar 31;9(2):100-4.

43. Bolliger MJ, Buck U, Thali MJ, Bolliger SA. Reconstruction and 3D visualisation based on objective real 3D based documentation. Forensic science, medicine, and pathology. 2012 Sep 1;8(3):208-17.

44. Ebert LC, Ptacek W, Naether S, Fürst M, Ross S, Buck U, Weber S, Thali M. Virtobot—a multi‐functional robotic system for 3D surface scanning and automatic post mortem biopsy. The international journal of medical robotics and computer assisted surgery. 2010 Mar 1;6(1):18-27.

45. Grunewald, S. (2016, June 16). 2016 3D Scanner Buying Guide. 3Dprint.com. Retrieved November 29, 2016, from https://3dprint.com/138629/2016-3d-scanner-buying-guide/.

46. Gurusamy K, Aggarwal R, Palanivelu L, et al. Systematic review of randomized controlled trials on the effectiveness of virtual reality training for laparoscopic surgery. Br J Surg. 2008;95:1088-1097.

47. Korner M, Weber CH, Wirth S, Pfeifer KJ, Reiser MF, Treitl M. Advances in Digital Radiography: Physical Principles and System Overview 1. Radiographics. 2007 May;27(3):675-86.

48. Farahani N, Parwani AV, Pantanowitz L. Whole slide imaging in pathology: advantages, limitations, and emerging perspectives. Pathol. Lab Med. Int. 2015 Jun;7:23-33.

49. Saco A, Ramírez J, Rakislova N, Mira A, Ordi J. Validation of Whole-Slide Imaging for Histolopathogical Diagnosis: Current State. Pathobiology. 2016 Apr 26;83(2-3):89-98.