Breaking Barriers: AI's Influence on Pathology and Oncology in Resource-Scarce Medical Systems.

Alon Vigdorovits, Maria Magdalena Köteles, Gheorghe-Emilian Olteanu, Ovidiu Pop
Author Information
  1. Alon Vigdorovits: Department of Pathology, County Clinical Emergency Hospital, Faculty of Medicine and Pharmacy, University of Oradea, 1 December Sq. No. 10, 410087 Oradea, Romania. ORCID
  2. Maria Magdalena Köteles: Bihor County Clinical Emergency Hospital, Gheorghe Doja, Street No. 65, 410169 Oradea, Romania. ORCID
  3. Gheorghe-Emilian Olteanu: Center for Research and Innovation in Personalized Medicine of Respiratory Diseases, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania. ORCID
  4. Ovidiu Pop: Department of Pathology, County Clinical Emergency Hospital, Faculty of Medicine and Pharmacy, University of Oradea, 1 December Sq. No. 10, 410087 Oradea, Romania. ORCID

Abstract

The application of artificial intelligence to improve the access of cancer patients to high-quality medical care is one of the goals of modern medicine. Pathology constitutes the foundation of modern oncologic treatment, and its role has expanded far beyond diagnosis into predicting treatment response and overall survival. However, the funding of pathology is often an afterthought in resource-scarce medical systems. The increased digitalization of pathology has paved the way towards the potential use of artificial intelligence tools for improving pathologist efficiency and extracting more information from tissues. In this review, we provide an overview of the main research directions intersecting with artificial intelligence and pathology in relation to oncology, such as tumor classification, the prediction of molecular alterations, and biomarker quantification. We then discuss examples of tools that have matured into clinical products and gained regulatory approval for clinical use. Finally, we highlight the main hurdles that stand in the way of the digitalization of pathology and the application of artificial intelligence in pathology while also discussing possible solutions.

Keywords

References

  1. Nat Med. 2018 Oct;24(10):1559-1567 [PMID: 30224757]
  2. ESMO Open. 2022 Apr;7(2):100400 [PMID: 35247870]
  3. PLoS One. 2023 Sep 7;18(9):e0290613 [PMID: 37676884]
  4. Front Public Health. 2022 Apr 25;10:839835 [PMID: 35548083]
  5. NPJ Precis Oncol. 2020 Jun 8;4:14 [PMID: 32550270]
  6. Am J Pathol. 2021 Oct;191(10):1717-1723 [PMID: 33838127]
  7. Histopathology. 2017 Jan;70(1):134-145 [PMID: 27960232]
  8. Med Image Anal. 2023 Jul;87:102824 [PMID: 37126973]
  9. Mod Pathol. 2020 Nov;33(11):2169-2185 [PMID: 32467650]
  10. Histopathology. 2022 Mar;80(4):635-647 [PMID: 34786761]
  11. Sci Rep. 2022 Dec 19;12(1):21948 [PMID: 36536017]
  12. J Pathol Inform. 2017 Dec 19;8:51 [PMID: 29416914]
  13. J Pathol Inform. 2021 Nov 03;12:43 [PMID: 34881098]
  14. Diagnostics (Basel). 2022 Feb 18;12(2): [PMID: 35204617]
  15. Sci Rep. 2021 Aug 5;11(1):15907 [PMID: 34354151]
  16. Mod Pathol. 2023 Jan;36(1):100009 [PMID: 36788064]
  17. Lung Cancer. 2022 Apr;166:143-149 [PMID: 35279453]
  18. Cancers (Basel). 2022 Feb 25;14(5): [PMID: 35267505]
  19. Cancers (Basel). 2019 Nov 25;11(12): [PMID: 31769420]
  20. NPJ Precis Oncol. 2021 Sep 23;5(1):87 [PMID: 34556802]
  21. NPJ Breast Cancer. 2021 May 26;7(1):61 [PMID: 34039982]
  22. Am Soc Clin Oncol Educ Book. 2022 Apr;42:1-10 [PMID: 35687826]
  23. AMA J Ethics. 2016 Aug 01;18(8):817-25 [PMID: 27550566]
  24. Arch Pathol Lab Med. 2019 Dec;143(12):1545-1555 [PMID: 31173528]
  25. Sci Rep. 2021 Jun 29;11(1):13505 [PMID: 34188098]
  26. J Glob Oncol. 2019 Mar;5:1-8 [PMID: 30908147]
  27. Mod Pathol. 2021 May;34(5):862-874 [PMID: 33299111]
  28. J Clin Med. 2020 Nov 18;9(11): [PMID: 33217963]
  29. J Pathol Inform. 2020 Jul 24;11:19 [PMID: 33033656]
  30. Mod Pathol. 2023 Mar;36(3):100033 [PMID: 36931740]
  31. Proc Mach Learn Res. 2019 Dec;116:10-24 [PMID: 33912842]
  32. EBioMedicine. 2023 Feb;88:104427 [PMID: 36603288]
  33. Sci Rep. 2022 Jul 27;12(1):12804 [PMID: 35896791]
  34. J Telemed Telecare. 2011;17(5):222-5 [PMID: 21565844]
  35. Br J Cancer. 2021 Feb;124(4):686-696 [PMID: 33204028]
  36. J Pathol. 2019 Nov;249(3):286-294 [PMID: 31355445]
  37. Diagn Pathol. 2022 Jan 30;17(1):20 [PMID: 35094693]
  38. Mod Pathol. 2023 Nov;36(11):100304 [PMID: 37580018]
  39. Mod Pathol. 2023 Mar;36(3):100054 [PMID: 36788100]
  40. Front Med (Lausanne). 2021 Nov 17;8:765385 [PMID: 34869473]
  41. Virchows Arch. 2023 Mar;482(3):595-604 [PMID: 36809483]
  42. Nature. 2021 Jun;594(7861):106-110 [PMID: 33953404]
  43. Sci Rep. 2022 Feb 24;12(1):3166 [PMID: 35210450]
  44. Sci Rep. 2021 Apr 14;11(1):8110 [PMID: 33854137]
  45. BMC Med. 2021 Mar 29;19(1):80 [PMID: 33775248]
  46. Sci Rep. 2017 Dec 4;7(1):16878 [PMID: 29203879]
  47. J Intern Med. 2020 Jul;288(1):62-81 [PMID: 32128929]
  48. Lancet Digit Health. 2020 Aug;2(8):e407-e416 [PMID: 33328045]
  49. Arch Pathol Lab Med. 2023 Oct 1;147(10):1178-1185 [PMID: 36538386]
  50. Lancet Oncol. 2022 Sep;23(9):1221-1232 [PMID: 35964620]
  51. Mod Pathol. 2021 Mar;34(3):660-671 [PMID: 32759979]
  52. Nat Med. 2023 Sep;29(9):2307-2316 [PMID: 37592105]
  53. Sci Rep. 2021 Aug 19;11(1):16849 [PMID: 34413349]
  54. J Invest Dermatol. 2022 Jun;142(6):1650-1658.e6 [PMID: 34757067]
  55. J Glob Oncol. 2015 Sep 23;1(1):3-6 [PMID: 28804765]
  56. NPJ Precis Oncol. 2023 Aug 15;7(1):77 [PMID: 37582946]
  57. Virchows Arch. 2020 Apr;476(4):491-497 [PMID: 32124002]
  58. Arch Pathol Lab Med. 2020 Feb;144(2):221-228 [PMID: 31295015]
  59. Lancet Oncol. 2020 Feb;21(2):233-241 [PMID: 31926805]
  60. J Pathol Inform. 2014 Aug 28;5(1):33 [PMID: 25250191]
  61. Arch Pathol Lab Med. 2021 Nov 1;145(11):1438-1447 [PMID: 33571353]
  62. Pathol Oncol Res. 2021 Mar 26;27:609717 [PMID: 34257575]
  63. Front Oncol. 2021 Jun 08;11:630953 [PMID: 34168975]
  64. Clin Lab Med. 2018 Mar;38(1):141-150 [PMID: 29412878]
  65. Nat Commun. 2023 Nov 6;14(1):6695 [PMID: 37932267]
  66. NPJ Breast Cancer. 2022 Dec 6;8(1):129 [PMID: 36473870]
  67. J Pathol Inform. 2022 Jun 30;13:100122 [PMID: 36268080]
  68. Histopathology. 2018 Jan;72(2):227-238 [PMID: 28771788]
  69. J Am Med Inform Assoc. 2021 Aug 13;28(9):1874-1884 [PMID: 34260720]
  70. Front Med (Lausanne). 2022 Jun 03;9:906950 [PMID: 35721068]
  71. Lancet Digit Health. 2023 Feb;5(2):e71-e82 [PMID: 36496303]
  72. Nat Med. 2019 Jan;25(1):44-56 [PMID: 30617339]
  73. J Digit Imaging. 2017 Oct;30(5):555-560 [PMID: 28116576]
  74. Diagnostics (Basel). 2021 Oct 16;11(10): [PMID: 34679614]
  75. Arch Pathol Lab Med. 2011 Feb;135(2):215-9 [PMID: 21284441]
  76. Sci Rep. 2020 Jan 30;10(1):1504 [PMID: 32001752]
  77. Mod Pathol. 2023 May;36(5):100154 [PMID: 36925069]
  78. BMC Med Res Methodol. 2018 Feb 26;18(1):24 [PMID: 29482517]
  79. Cancers (Basel). 2020 Mar 05;12(3): [PMID: 32150991]
  80. Cancer Cell. 2023 Sep 11;41(9):1650-1661.e4 [PMID: 37652006]
  81. Front Genet. 2021 Jul 20;12:661109 [PMID: 34354733]
  82. J Pathol Inform. 2021 Mar 22;12:13 [PMID: 34012717]
  83. Biochim Biophys Acta Rev Cancer. 2021 Jan;1875(1):188452 [PMID: 33065195]
  84. J Am Acad Dermatol. 2011 May;64(5):986-7 [PMID: 21496704]
  85. Lab Invest. 2022 Mar;102(Suppl 1):419-565 [PMID: 35302070]

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