A roadmap for the clinical implementation of optical-imaging biomarkers

Abstract

Clinical workflows for the non-invasive detection and characterization of disease states could benefit from optical-imaging biomarkers. In this Perspective, we discuss opportunities and challenges towards the clinical implementation of optical-imaging biomarkers for the early detection of cancer by analysing two case studies: the assessment of skin lesions in primary care, and the surveillance of patients with Barrett’s oesophagus in specialist care. We stress the importance of technical and biological validations and clinical-utility assessments, and the need to address implementation bottlenecks. In addition, we define a translational roadmap for the widespread clinical implementation of optical-imaging technologies.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Visible and near-infrared light–tissue interactions.
Fig. 2: Roadmap for OIBs.
Fig. 3: Current and potential future clinical implementations of optical imaging in two case studies.

References

  1. 1.

    Wax, A. et al. Angle-resolved low coherence interferometry for detection of dysplasia in Barrett’s esophagus. Gastroenterology 141, 443–447 (2011).

    PubMed  PubMed Central  Google Scholar 

  2. 2.

    Imamoto, Y. & Shichida, Y. Cone visual pigments. Biochim. Biophys. Acta 1837, 664–673 (2014).

    CAS  PubMed  Google Scholar 

  3. 3.

    O’Connor, J. B. P. et al. Imaging biomarker roadmap for cancer studies. Nat. Rev. Clin. Oncol. 14, 169–186 (2017).

    PubMed  Google Scholar 

  4. 4.

    Sharma, P. et al. White Paper AGA: Advanced Imaging in Barrett’s Esophagus. Clin. Gastroenterol. Hepatol. 13, 2209–2218.

    PubMed  Google Scholar 

  5. 5.

    Thosani, N. et al. ASGE Technology Committee systematic review and meta-analysis assessing the ASGE Preservation and Incorporation of Valuable Endoscopic Innovations thresholds for adopting real-time imaging–assisted endoscopic targeted biopsy during endoscopic surveillance. Gastrointest. Endosc. 83, 684–698.

  6. 6.

    Nikolaou, V. & Stratigos, A. J. Emerging trends in the epidemiology of melanoma. Br. J. Dermatol. 170, 11–19 (2014).

    CAS  PubMed  Google Scholar 

  7. 7.

    Suspected Cancer: Recognition and Referral: NICE Guideline (NG12) (NICE, 2015); https://www.nice.org.uk/guidance/ng12

  8. 8.

    Terushkin, V. & Halpern, A. C. Melanoma Early Detection. Hematol. Oncol. Clin. North Am. 23, 481–500 (2009).

    PubMed  Google Scholar 

  9. 9.

    Lindholm, C. et al. Invasive cutaneous malignant melanoma in Sweden, 1990–1999: A prospective, population-based study of survival and prognostic factors. Cancer 101, 2067–2078 (2004).

    PubMed  Google Scholar 

  10. 10.

    Breitbart, E. W. et al. Systematic skin cancer screening in Northern Germany. J. Am. Acad. Dermatol. 66, 201–211 (2012).

    PubMed  Google Scholar 

  11. 11.

    Katalinic, A. et al. Does skin cancer screening save lives?: an observational study comparing trends in melanoma mortality in regions with and without screening. Cancer 118, 5395–5402 (2012).

    PubMed  Google Scholar 

  12. 12.

    Bibbins-Domingo, K. et al. Screening for Skin Cancer. Jama 316, 429–435 (2016).

    PubMed  Google Scholar 

  13. 13.

    Stratigos, A. J. et al. Euromelanoma: a dermatology-led European campaign against nonmelanoma skin cancer and cutaneous melanoma. Past, present and future. Br. J. Dermatol. 167, 99–104 (2012).

    PubMed  Google Scholar 

  14. 14.

    Vestergaard, M. E. et al. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: A meta-analysis of studies performed in a clinical setting. Br. J. Dermatol. 159, 669–676 (2008).

    CAS  PubMed  Google Scholar 

  15. 15.

    Moncrieff, M. et al. Spectrophotometric intracutaneous analysis: a new technique for imaging pigmented skin lesions. Br. J. Dermatol. 146, 448–457 (2002).

    CAS  PubMed  Google Scholar 

  16. 16.

    Emery, J. D. et al. Accuracy of SIAscopy for pigmented skin lesions encountered in primary care: development and validation of a new diagnostic algorithm. BMC Dermatol. 10, 9 (2010).

    PubMed  PubMed Central  Google Scholar 

  17. 17.

    Walter, F. M. et al. Protocol for the MoleMate UK Trial: a randomised controlled trial of the MoleMate system in the management of pigmented skin lesions in primary care. BMC Fam. Pract. 11, 36 (2010).

    PubMed  PubMed Central  Google Scholar 

  18. 18.

    Walter, F. M. et al. Effect of adding a diagnostic aid to best practice to manage suspicious pigmented lesions in primary care: randomised controlled trial. Br. Med. J. 345, e4110 (2012).

    Google Scholar 

  19. 19.

    Vasefi, F. et al. Multimode optical dermoscopy (SkinSpect) analysis for skin with melanocytic nevus. Proc. of SPIE 9711, 971110 (2016).

    Google Scholar 

  20. 20.

    Vasefi., F. et al. Polarization-sensitive hyperspectral imaging in vivo: a multimode dermoscope for skin analysis. Sci. Rep. 4, 4924 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Vasefi, F. et al. Separating melanin from hemodynamics in nevi using multimode hyperspectral dermoscopy and spatial frequency domain spectroscopy. J. Biomed. Opt. 21, 114001 (2016).

    PubMed  PubMed Central  Google Scholar 

  22. 22.

    MacKinnon, N. et al. In vivo skin chromophore mapping using a multimode imaging dermoscope (SkinSpect). Proc. SPIE 8587, (1–13 (2013).

    Google Scholar 

  23. 23.

    Elbaum, M. et al. Automatic differentiation of melanoma from melanocytic nevi with multispectral digital dermoscopy: a feasibility study. J. Am. Acad. Dermatol. 44, 207–218 (2001).

    CAS  PubMed  Google Scholar 

  24. 24.

    Monheit, G. et al. The performance of MelaFind: a prospective multicenter study. Arch. Dermatol. 147, 188–194 (2011).

    PubMed  Google Scholar 

  25. 25.

    Hauschild, A. et al. To excise or not: impact of MelaFind on German dermatologists’ decisions to biopsy atypical lesions. J. Dtsch Dermatol. Ges. 12, 606–614 (2014).

    PubMed  Google Scholar 

  26. 26.

    Xiong, Y.-Q. et al. Comparison of dermoscopy and reflectance confocal microscopy for the diagnosis of malignant skin tumours: a meta-analysis. J. Cancer Res. Clin. Oncol. Springer 1627–1635 (2017).

  27. 27.

    Segura, S. et al. Development of a two-step method for the diagnosis of melanoma by reflectance confocal microscopy. J. Am. Acad. Dermatol. 61, 216–229 (2009).

    PubMed  Google Scholar 

  28. 28.

    Guitera, P. et al. Surveillance for treatment failure of lentigo maligna with dermoscopy and in vivo confocal microscopy: new descriptors. Br. J. Dermatol. 170, 1305–1312 (2014).

    CAS  PubMed  Google Scholar 

  29. 29.

    Guitera, P. et al. In vivo reflectance confocal microscopy enhances secondary evaluation of melanocytic lesions. J. Invest. Dermatol. 129, 131–138 (2009).

    CAS  PubMed  Google Scholar 

  30. 30.

    Stanganelli, I. et al. Integration of reflectance confocal microscopy in sequential dermoscopy follow-up improves melanoma detection accuracy. Br. J. Dermatol. 172, 365–371 (2015).

    CAS  PubMed  Google Scholar 

  31. 31.

    Witkowski, A. M. et al. Non-invasive diagnosis of pink basal cell carcinoma: how much can we rely on dermoscopy and reflectance confocal microscopy? Ski. Res. Technol. 22, 230–237 (2016).

    CAS  Google Scholar 

  32. 32.

    Venturini, M. et al. Reflectance confocal microscopy allows in vivo real-time noninvasive assessment of the outcome of methyl aminolaevulinate photodynamic therapy of basal cell carcinoma. Br. J. Dermatol. 168, 99–105 (2013).

    CAS  PubMed  Google Scholar 

  33. 33.

    Langley, R. G. B. et al. The diagnostic accuracy of in vivo confocal scanning laser microscopy compared to dermoscopy of benign and malignant melanocytic lesions: a prospective study. Dermatology 215, 365–372 (2007).

    PubMed  Google Scholar 

  34. 34.

    Moscarella, E. et al. The role of reflectance confocal microscopy as an aid in the diagnosis of collision tumors. Dermatology 227, 109–117 (2013).

    PubMed  Google Scholar 

  35. 35.

    Alarcon, I. et al. Impact of in vivo reflectance confocal microscopy on the number needed to treat melanoma in doubtful lesions. Br. J. Dermatol. 170, 802–808 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    VivaScope 1500 and 3000 imaging systems for detecting skin cancer lesions - guidance (DG19) (NICE, 2015).

  37. 37.

    Konig, K. & Riemann, I. High-resolution multiphoton tomography of human skin with subcellular spatial resolution and picosecond time resolution. J. Biomed. Opt. 8, 432–439 (2003).

    PubMed  Google Scholar 

  38. 38.

    Manfredini, M. et al. High-resolution imaging of basal cell carcinoma: a comparison between multiphoton microscopy with fluorescence lifetime imaging and reflectance confocal microscopy. Ski. Res. Technol. 19, 433–443 (2013).

    Google Scholar 

  39. 39.

    Seidenari, S. et al. Multiphoton laser tomography and fluorescence lifetime imaging of melanoma: morphologic features and quantitative data for sensitive and specific non-invasive diagnostics,”. PLoS ONE 8, e70682 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Ulrich, M. et al. Dynamic optical coherence tomography in dermatology. Dermatology 232, 298–311 (2016).

    PubMed  Google Scholar 

  41. 41.

    Boone, M. A. L. M. et al. High-definition optical coherence tomography imaging of melanocytic lesions: a pilot study. Arch. Dermatol. Res. 306, 11–26 (2014).

    PubMed  Google Scholar 

  42. 42.

    Gambichler, T. et al. High-definition optical coherence tomography of melanocytic skin lesions. J. Biophotonics 8, 681–686 (2015).

    PubMed  Google Scholar 

  43. 43.

    Schuh, S. et al. Comparison of different optical coherence tomography devices for diagnosis of non-melanoma skin cancer. Ski. Res. Technol. 22, 395–405 (2016).

    CAS  Google Scholar 

  44. 44.

    Nolan, R. C. et al. Optical coherence tomography for the neurologist. Semin. Neurol. 35, 564–577 (2015).

    PubMed  Google Scholar 

  45. 45.

    Tan, A. C. S. et al. An overview of the clinical applications of optical coherence tomography angiography. Eye 32, 262–268 (2017).

    PubMed  PubMed Central  Google Scholar 

  46. 46.

    Liu, Q. Role of optical spectroscopy using endogenous contrasts in clinical cancer diagnosis. World J. Clin. Oncol. 2, 50–63 (2011).

    PubMed  PubMed Central  Google Scholar 

  47. 47.

    Kendall, C. et al. Vibrational spectroscopy: a clinical tool for cancer diagnostics. Analyst 134, 1029–1045 (2009).

    CAS  PubMed  Google Scholar 

  48. 48.

    Pence, I. & Mahadevan-Jansen, A. Clinical instrumentation and applications of Raman spectroscopy. Chem. Soc. Rev. 45, 1958–1979 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Brancaleon, L. et al. In vivo fluorescence spectroscopy of nonmelanoma skin cancer. Photochem. Photobiol. 73, 178–183 (2001).

    CAS  PubMed  Google Scholar 

  50. 50.

    Garcia-Uribe, A. et al. Skin cancer detection by spectroscopic oblique-incidence reflectometry: classification and physiological origins. Appl. Opt. 43, 2643–2650 (2004).

    PubMed  Google Scholar 

  51. 51.

    Rajaram, N. et al. Pilot clinical study for quantitative spectral diagnosis of non-melanoma skin cancer. Lasers Surg. Med. 42, 716–727 (2010).

    PubMed  PubMed Central  Google Scholar 

  52. 52.

    Thompson, A. J. et al. In vivo measurements of diffuse reflectance and time-resolved autofluorescence emission spectra of basal cell carcinomas. J. Biophotonics 5, 240–254 (2012).

    PubMed  Google Scholar 

  53. 53.

    Garcia-Uribe, A. et al. In vivo diagnosis of melanoma and nonmelanoma skin cancer using oblique incidence diffuse reflectance spectrometry. Cancer Res. 72, 2738–2745 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Upile, T. et al. Elastic scattering spectroscopy in assessing skin lesions: an ‘in vivo’ study. Photodiagnosis Photodyn. Ther. 9, 132–141 (2012).

    PubMed  Google Scholar 

  55. 55.

    Lui, H. et al. Real-time raman spectroscopy for in vivo skin cancer diagnosis. Cancer Res. 72, 2491–2500 (2012).

    CAS  PubMed  Google Scholar 

  56. 56.

    Zhao, J. et al. Real-time Raman spectroscopy for non-invasive skin cancer detection - preliminary results. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2008, 3107–3109 (2008).

    PubMed  Google Scholar 

  57. 57.

    Lim, L. et al. Clinical study of noninvasive in vivo melanoma and nonmelanoma skin cancers using multimodal spectral diagnosis. J. Biomed. Opt. 19, 117003 (2014).

    PubMed  PubMed Central  Google Scholar 

  58. 58.

    Schleusener, J. et al. In vivo study for the discrimination of cancerous and normal skin using fibre probe-based Raman spectroscopy. Exp. Dermatol. 24, 767–772 (2015).

    PubMed  Google Scholar 

  59. 59.

    Zakharov, V. P. et al. Combined Raman spectroscopy and autofluoresence imaging method for in vivo skin tumor diagnosis. Proc. SPIE 9198, (919804 (2014).

    Google Scholar 

  60. 60.

    Stamnes, J. J. et al. Optical detection and monitoring of pigmented skin lesions. Biomed. Opt. Express 8, 2946–2964 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61.

    Shim, M. G. & B. C. Wilson, B. C. The effects of ex vivo handling procedures on the near-infrared Raman spectra of normal mammalian tissues. Photochem. Photobiol. 63, 662–671 (1996).

    CAS  PubMed  Google Scholar 

  62. 62.

    Kim, S., Byun, K. M. & Lee, S. Y. Influence of water content on Raman spectroscopy characterization of skin sample. Biomed. Opt. Express 8, 1130–1138 (2017).

    PubMed  PubMed Central  Google Scholar 

  63. 63.

    Hvid-Jensen, F. et al. Incidence of adenocarcinoma among patients with Barrett’s esophagus. N. Engl. J. Med. 365, 1375–1383 (2011).

    CAS  PubMed  Google Scholar 

  64. 64.

    Gatenby, P. et al. Lifetime risk of esophageal adenocarcinoma in patients with Barrett’s esophagus. World J. Gastroenterol. 20, 9611–9617 (2014).

    PubMed  PubMed Central  Google Scholar 

  65. 65.

    Duits, L. C. et al. Barrett’s oesophagus patients with low-grade dysplasia can be accurately risk-stratified after histological review by an expert pathology panel. Gut 64, 700–706 (2015).

    PubMed  Google Scholar 

  66. 66.

    Singh, S. et al. Incidence of esophageal adenocarcinoma in Barrett’s esophagus with low-grade dysplasia: a systematic review and meta-analysis. Gastrointest. Endosc. 79, 897–909 (2014).

    PubMed  Google Scholar 

  67. 67.

    Fitzgerald, R. C. et al. British Society of Gastroenterology guidelines on the diagnosis and management of Barrett’s oesophagus. Gut 63, 7–42 (2014).

    PubMed  Google Scholar 

  68. 68.

    Spechler, S. J. et al. American Gastroenterological Association technical review on the management of Barrett’s esophagus. Gastroenterology 140, 18–52 (2011).

    Google Scholar 

  69. 69.

    Wang., K. K. & Sampliner, R. E. Updated guidelines 2008 for the diagnosis, surveillance and therapy of Barrett’s esophagus. Am. J. Gastroenterol. 103, 788–797 (2008).

    PubMed  Google Scholar 

  70. 70.

    Evans, J. A. et al. The role of endoscopy in Barrett’s esophagus and other premalignant conditions of the esophagus. Gastrointest. Endosc. 76, 1087–1094 (2012).

    PubMed  Google Scholar 

  71. 71.

    Weusten, B. et al. Endoscopic management of Barrett’s esophagus: European Society of Gastrointestinal Endoscopy (ESGE) position statement. Endoscopy 49, 191–198 (2017).

    PubMed  Google Scholar 

  72. 72.

    Rubenstein, J. H. et al. Effect of a prior endoscopy on outcomes of esophageal adenocarcinoma among United States veterans. Gastrointest. Endosc. 68, 849–855 (2008).

    PubMed  PubMed Central  Google Scholar 

  73. 73.

    Cooper, G. S., Kou, T. D. & Chak, A. Receipt of previous diagnoses and endoscopy and outcome from esophageal adenocarcinoma: a population-based study with temporal trends. Am. J. Gastroenterol. 104, 1356–1362 (2009).

    PubMed  Google Scholar 

  74. 74.

    El-Serag, H. B. et al. Surveillance endoscopy is associated with improved outcomes of oesophageal adenocarcinoma detected in patients with Barrett’s oesophagus. Gut 65, 1252–1260 (2016).

    PubMed  Google Scholar 

  75. 75.

    Kastelein, F. et al. Impact of surveillance for Barrett’s oesophagus on tumour stage and survival of patients with neoplastic progression. Gut 65, 1–7 (2015).

    Google Scholar 

  76. 76.

    Verbeek, R. E. et al. Surveillance of Barrett’s Esophagus and mortality from esophageal adenocarcinoma: a population-based cohort study. Am. J. Gastroenterol. 109, 1215–1222 (2014).

    PubMed  Google Scholar 

  77. 77.

    Sturm, M. B. & Wang, T. D. Emerging optical methods for surveillance of Barrett’s oesophagus. Gut 64, 1816–1823 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. 78.

    Chedgy, F. J. Q. et al. Acetic acid chromoendoscopy: Improving neoplasia detection in Barrett’s esophagus. World J. Gastroenterol. 22, 5753–5760 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. 79.

    Sharma, P. et al. The American Society for Gastrointestinal Endoscopy PIVI (preservation and incorporation of valuable endoscopic innovations) on imaging in Barrett’s Esophagus. Gastrointest. Endosc. 76, 252–254 (2012).

    PubMed  Google Scholar 

  80. 80.

    Lim, C. H. et al. Randomized crossover study that used methylene blue or random 4-quadrant biopsy for the diagnosis of dysplasia in Barrett’s esophagus. Gastrointest. Endosc. 64, 195–199 (2006).

    PubMed  Google Scholar 

  81. 81.

    Horwhat, J. D. et al. A randomized comparison of methylene blue-directed biopsy versus conventional four-quadrant biopsy for the detection of intestinal metaplasia and dysplasia in patients with long-segment Barrett’s esophagus. Am. J. Gastroenterol. 103, 546–554 (2008).

    PubMed  Google Scholar 

  82. 82.

    Coletta, M. et al. Acetic acid chromoendoscopy for the diagnosis of early neoplasia and specialized intestinal metaplasia in Barrett’s esophagus: a meta-analysis. Gastrointest. Endosc. 83, 57–67 (2016).

    PubMed  Google Scholar 

  83. 83.

    Tholoor, S. et al. Acetic acid chromoendoscopy in Barrett’s esophagus surveillance is superior to the standardized random biopsy protocol: results from a large cohort study. Gastrointest. Endosc. 80, 417–424 (2014).

    PubMed  Google Scholar 

  84. 84.

    Olliver, J. R. et al. Chromoendoscopy with methylene blue and associated DNA damage in Barrett’s oesophagus. Lancet 362, 373–374 (2003).

    CAS  PubMed  Google Scholar 

  85. 85.

    Sturmey, R. G., Wild, C. P. & Hardie, L. J. Removal of red light minimizes methylene blue-stimulated DNA damage in oesophageal cells: implications for chromoendoscopy. Mutagenesis 24, 253–258 (2009).

    CAS  PubMed  Google Scholar 

  86. 86.

    Kovacic, P. & Somanathan, R. Toxicity of imine-iminium dyes and pigments: electron transfer, radicals, oxidative stress and other physiological effects. J. Appl. Toxicol. 34, 825–834 (2014).

    CAS  PubMed  Google Scholar 

  87. 87.

    James, M. L. & Gambhir, S. S. A molecular imaging primer: modalities, imaging agents, and applications. Physiol. Rev. 92, 897–965 (2012).

    CAS  PubMed  Google Scholar 

  88. 88.

    Lee, J. H. & Wang, T. D. Molecular endoscopy for targeted imaging in the digestive tract. Lancet Gastroenterol. Hepatol. 1, 147–155 (2016).

    PubMed  Google Scholar 

  89. 89.

    Sturm, M. B. et al. Targeted imaging of esophageal neoplasia with a fluorescently labeled peptide: first-in-human results. Sci. Transl. Med. 5, 184ra61 (2013).

    PubMed  Google Scholar 

  90. 90.

    Joshi, B. P. et al. Multimodal endoscope can quantify wide-field fluorescence detection of Barrett’s neoplasia. Endoscopy 48, 1–13 (2015).

    CAS  Google Scholar 

  91. 91.

    Bird-Lieberman, E. L. et al. Molecular imaging using fluorescent lectins permits rapid endoscopic identification of dysplasia in Barrett’s esophagus. Nat. Med. 18, 315–321 (2012).

    CAS  PubMed  Google Scholar 

  92. 92.

    Nagengast, W. B. et al. Near-infrared fluorescence molecular endoscopy detects dysplastic oesophageal lesions using topical and systemic tracer of vascular endothelial growth factor A. Gut 68, 7–10 (2017).

    PubMed  Google Scholar 

  93. 93.

    Kaneko, K. et al. Effect of novel bright image enhanced endoscopy using blue laser imaging (BLI). Endosc. Int. Open 2, E212–E219 (2014).

    PubMed  PubMed Central  Google Scholar 

  94. 94.

    Yoshida, N. et al. Ability of a novel blue laser imaging system for the diagnosis of colorectal polyps. Dig. Endosc. 26, 250–258 (2014).

    PubMed  Google Scholar 

  95. 95.

    Miyake, Y. et al. Development of new electronic endoscopes using the spectral images of an internal organ. In Proc. IS&T/SID’s Thirteen Color Imaging Conf. 261–269 (Society for Imaging Science and Technology, 2005).

  96. 96.

    Kodashima, S. & Fujishiro, M. Novel image-enhanced endoscopy with i-scan technology. World J. Gastroenterol. 16, 1043–1049 (2010).

    PubMed  PubMed Central  Google Scholar 

  97. 97.

    Li, C. Q. et al. Magnified and enhanced computed virtual chromoendoscopy in gastric neoplasia: a feasibility study. World J. Gastroenterol. 19, 4221–4227 (2013).

    PubMed  PubMed Central  Google Scholar 

  98. 98.

    Osawa, H. et al. Diagnosis of depressed-type early gastric cancer using small-caliber endoscopy with flexible spectral imaging color enhancement. Dig. Endosc. 24, 231–236 (2012).

    PubMed  Google Scholar 

  99. 99.

    Osawa, H. et al. Diagnosis of endoscopic Barrett’s esophagus by transnasal flexible spectral imaging color enhancement. J. Gastroenterol. 44, 1125–1132 (2009).

    PubMed  Google Scholar 

  100. 100.

    Aminalai, A. et al. Live image processing does not increase adenoma detection rate during colonoscopy: a randomized comparison between FICE and conventional imaging (Berlin Colonoscopy Project 5, BECOP-5). Am. J. Gastroenterol. 105, 2383–2388 (2010).

    PubMed  Google Scholar 

  101. 101.

    Chung, S. J. et al. Efficacy of computed virtual chromoendoscopy on colorectal cancer screening: a prospective, randomized, back-to-back trial of Fuji Intelligent Color Enhancement versus conventional colonoscopy to compare adenoma miss rates. Gastrointest. Endosc. 72, 136–142 (2010).

    PubMed  Google Scholar 

  102. 102.

    Basford, P. J. et al. High-definition endoscopy with i-Scan for evaluation of small colon polyps: the HiSCOPE study. Gastrointest. Endosc. 79, 111–118 (2014).

    PubMed  Google Scholar 

  103. 103.

    Hong, S. N. et al. Prospective, randomized, back-to-back trial evaluating the usefulness of i-SCAN in screening colonoscopy. Gastrointest. Endosc. 75, 1011–1021 (2012).

    PubMed  Google Scholar 

  104. 104.

    Lee, C. K., Lee, S. H. & Hwangbo, Y. Narrow-band imaging versus I-Scan for the real-time histological prediction of diminutive colonic polyps: A prospective comparative study by using the simple unified endoscopic classification. Gastrointest. Endosc. 74, 603–609 (2011).

    PubMed  Google Scholar 

  105. 105.

    Yoshida, Y. et al. A randomized crossover open trial of the adenoma miss rate for narrow band imaging (NBI) versus flexible spectral imaging color enhancement (FICE). Int. J. Colorectal Dis. 28, 1511–1516 (2013).

    PubMed  Google Scholar 

  106. 106.

    Chung, S. J. et al. Comparison of detection and miss rates of narrow band imaging, flexible spectral imaging chromoendoscopy and white light at screening colonoscopy: a randomised controlled back-to-back study. Gut 63, 785–791 (2014).

    PubMed  Google Scholar 

  107. 107.

    Masci, E. et al. Interobserver agreement among endoscopists on evaluation of polypoid colorectal lesions visualized with the Pentax i-Scan technique. Dig. Liver Dis. 45, 207–210 (2013).

    PubMed  Google Scholar 

  108. 108.

    Pigò, F. et al. I-Scan high-definition white light endoscopy and colorectal polyps: prediction of histology, interobserver and intraobserver agreement. Int. J. Colorectal Dis. 28, 399–406 (2013).

    PubMed  Google Scholar 

  109. 109.

    Sharma, P. et al. Development and validation of a classification system to identify high-grade dysplasia and esophageal adenocarcinoma in Barrett’s Esophagus using narrow band imaging. Gastroenterology 150, 591–598 (2016).

    PubMed  Google Scholar 

  110. 110.

    Haringsma, J. & Tytgat, G. N. J. Fluorescence and autofluorescence. Clin. Gastroenterol. 13, 1–10 (1999).

    CAS  Google Scholar 

  111. 111.

    Kara, M. A. et al. Endoscopic video autofluorescence imaging may improve the detection of early neoplasia in patients with Barrett’s esophagus. Gastrointest. Endosc. 61, 679–685 (2005).

    PubMed  Google Scholar 

  112. 112.

    Curvers, W. L. et al. Endoscopic trimodal imaging versus standard video endoscopy for detection of early Barrett’s neoplasia: a multicenter, randomized, crossover study in general practice. Gastrointest. Endosc. 73, 195–203 (2011).

    PubMed  Google Scholar 

  113. 113.

    Boerwinkel, D. F. et al. Endoscopic TriModal imaging and biomarkers for neoplasia conjoined: a feasibility study in Barrett’s esophagus. Dis. Esophagus 27, 435–443 (2014).

    CAS  PubMed  Google Scholar 

  114. 114.

    Curvers, W. L. et al. Endoscopic tri-modal imaging is more effective than standard endoscopy in identifying early-stage neoplasia in Barrett’s esophagus. Gastroenterology 139, 1106–1114 (2010).

    PubMed  Google Scholar 

  115. 115.

    Wallace, M. et al. Miami classification for probe-based confocal laser endomicroscopy. Endoscopy 43, 882–891 (2011).

    CAS  PubMed  Google Scholar 

  116. 116.

    Kiesslich, R. et al. In vivo histology of Barrett’s esophagus and associated neoplasia by confocal laser endomicroscopy. Clin. Gastroenterol. Hepatol. 4, 979–987 (2006).

    PubMed  Google Scholar 

  117. 117.

    Vakoc, B. J. et al. Comprehensive esophageal microscopy by using optical frequency-domain imaging. Gastrointest. Endosc. 65, 898–905 (2007).

    PubMed  PubMed Central  Google Scholar 

  118. 118.

    Gora, M. J. et al. Tethered capsule endomicroscopy enables less invasive imaging of gastrointestinal tract microstructure. Nat. Med. 19, 238–240 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  119. 119.

    Yun, S. H. et al. Comprehensive volumetric optical microscopy in vivo. Nat. Med. 12, 1429–1433 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  120. 120.

    Wolfsen, H. C. et al. Safety and feasibility of volumetric laser endomicroscopy in patients with Barrett’s esophagus. Gastrointest. Endosc. 82, 631–640 (2015).

    PubMed  Google Scholar 

  121. 121.

    Swager, A. F. et al. Detection of buried Barrett’s glands after radiofrequency ablation with volumetric laser endomicroscopy. Gastrointest. Endosc. 83, 80–88 (2016).

    PubMed  Google Scholar 

  122. 122.

    Swager, A. et al. Volumetric laser endomicroscopy in Barrett’s esophagus: a feasibility study on histological correlation. Dis. Esophagus 29, 505–512 (2015).

    PubMed  Google Scholar 

  123. 123.

    Trindade, A. J. et al. Volumetric laser endomicroscopy can target neoplasia not detected by conventional endoscopic measures in long segment Barrett’s esophagus. Endosc. Int. 4, 318–322 (2016).

    Google Scholar 

  124. 124.

    Leggett, C. L. et al. Comparative diagnostic performance of volumetric laser endomicroscopy and confocal laser endomicroscopy in the detection of dysplasia associated with Barrett’s esophagus. Gastrointest. Endosc. 83, 880–888 (2015).

    PubMed  PubMed Central  Google Scholar 

  125. 125.

    Poneros, J. M. et al. Diagnosis of specialized intestinal metaplasia by optical coherence tomography. Gastroenterology 120, 7–12 (2001).

    CAS  PubMed  Google Scholar 

  126. 126.

    Evans, J. A. et al. Optical coherence tomography to identify intramucosal carcinoma and high-grade dysplasia in Barrett’s esophagus. Clin. Gastroenterol. Hepatol. 4, 38–43 (2006).

    PubMed  PubMed Central  Google Scholar 

  127. 127.

    Evans, J. A. et al. Identifying intestinal metaplasia at the squamocolumnar junction by using optical coherence tomography. Gastrointest. Endosc. 65, 50–56 (2007).

    PubMed  Google Scholar 

  128. 128.

    Sauk, J. et al. Interobserver agreement for the detection of barrett’s esophagus with optical frequency domain imaging. Dig. Dis. Sci. 58, 2261–2265 (2013).

    PubMed  PubMed Central  Google Scholar 

  129. 129.

    Suter, M. J. et al. Esophageal-guided biopsy with volumetric laser endomicroscopy and laser cautery marking: a pilot clinical study. Gastrointest. Endosc. 79, 886–896 (2014).

    PubMed  PubMed Central  Google Scholar 

  130. 130.

    Gora, M. J. et al. Imaging the upper gastrointestinal tract in unsedated patients using tethered capsule endomicroscopy. Gastroenterology 145, 723–725 (2013).

    PubMed  Google Scholar 

  131. 131.

    Ughi, G. J. et al. Automated segmentation and characterization of esophageal wall in vivo by tethered capsule optical coherence tomography endomicroscopy. Biomed. Opt. Express 7, 660–665 (2016).

    Google Scholar 

  132. 132.

    Gora, M. et al. Tethered capsule endomicroscopy : from bench to bedside at a primary care practice tethered capsule endomicroscopy : from bench to bedside at a primary care practice. J. Biomed. Opt. 21, 104001 (2016).

    PubMed  PubMed Central  Google Scholar 

  133. 133.

    Ntziachristos, V. ESOTRAC https://www.esotrac2020.eu/ (2018).

  134. 134.

    Bergholt, M. S. et al. Fiberoptic confocal raman spectroscopy for real-time in vivo diagnosis of dysplasia in Barrett’s esophagus. Gastroenterology 146, 27–32 (2014).

    PubMed  Google Scholar 

  135. 135.

    Almond, L. M. et al. Endoscopic Raman spectroscopy enables objective diagnosis of dysplasia in Barrett’s esophagus. Gastrointest. Endosc. 79, 37–45 (2014).

    PubMed  Google Scholar 

  136. 136.

    Van Norman, G. A. Drugs and devices: comparison of European and U. S. approval processes. JACC Basic Transl. Sci. 1, 399–412 (2016).

    PubMed  PubMed Central  Google Scholar 

  137. 137.

    Regulation (EU) 2017/745 of the European Parliament and of the Council of 5 April 2017. Official J. European Union L117, 1–175, https://eur-lex.europa.eu/legal-content/ENG/TXT/PDF/?uri=CELEX:32017R0745 (2017).

  138. 138.

    Beswick, D. M., Kaushik, A. & Beinart, D. Biomedical device innovation methodology: applications in biophotonics. J. Biomed. Opt. 23, 1–7 (2017).

    PubMed  Google Scholar 

  139. 139.

    Laudicella, M. et al. Cost of care for cancer patients in England: evidence from population-based patient-level data. Br. J. Cancer 114, 1286–1292 (2016).

    PubMed  PubMed Central  Google Scholar 

  140. 140.

    Trivedi, P. J. & Braden, B. Indications, stains and techniques in chromoendoscopy. QJM 106, 117–131 (2013).

    CAS  PubMed  Google Scholar 

  141. 141.

    Sevick-Muraca, E. M. et al. Advancing the translation of optical imaging agents for clinical imaging. Biomed. Opt. Express 4, 160–170 (2013).

    PubMed  Google Scholar 

  142. 142.

    Tummers, W. S. et al. Regulatory aspects of optical methods and exogenous targets for cancer detection. Cancer Res. 77, 2197–2206 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  143. 143.

    US FDA. Overview of Device Regulation. US Department of Health and Human Services https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/Overview/default.htm (2017).

  144. 144.

    European Commission. Medical devices. European Union https://ec.europa.eu/growth/sectors/medical-devices_en (2017).

  145. 145.

    Marcu, L. et al. Biophotonics: the big picture. J. Biomed. Opt. 23, 1–7 (2017).

    PubMed  Google Scholar 

  146. 146.

    Boerwinkel, D. F. et al. Third-generation autofluorescence endoscopy for the detection of early neoplasia in Barrett’s esophagus: a pilot study. Dis. Esophagus 27, 276–284 (2014).

    CAS  PubMed  Google Scholar 

  147. 147.

    Alvarez Herrero, L. et al. Zooming in on Barrett oesophagus using narrow-band imaging: an international observer agreement study. Eur. J. Gastroenterol. Hepatol. 21, 1068–1075 (2009).

    PubMed  Google Scholar 

  148. 148.

    Curvers, W. L. et al. Mucosal morphology in Barrett’s esophagus: interobserver agreement and role of narrow band imaging. Endoscopy 40, 799–805 (2008).

    CAS  PubMed  Google Scholar 

  149. 149.

    Silva, F. B. et al. Endoscopic assessment and grading of Barrett’s esophagus using magnification endoscopy and narrow-band imaging: accuracy and interobserver agreement of different classification systems. Gastrointest. Endosc. 73, 7–14 (2011).

    PubMed  Google Scholar 

  150. 150.

    Kara, M. A. et al. Detection and classification of the mucosal and vascular patterns (mucosal morphology) in Barrett’s esophagus by using narrow band imaging. Gastrointest. Endosc. 64, 155–166 (2006).

    PubMed  Google Scholar 

  151. 151.

    Singh, R. et al. Narrow-band imaging with magnification in Barrett’s esophagus: validation of a simplified grading system of mucosal morphology patterns against histology. Endoscopy 40, 457–463 (2008).

    CAS  PubMed  Google Scholar 

  152. 152.

    Sharma, P. et al. The utility of a novel narrow band imaging endoscopy system in patients with Barrett’s esophagus. Gastrointest. Endosc. 64, 167–175 (2006).

    PubMed  Google Scholar 

  153. 153.

    de Bruijne, M. Machine learning approaches in medical image analysis: From detection to diagnosis. Med. Image Anal. 33, 94–97 (2016).

    PubMed  Google Scholar 

  154. 154.

    Suzuki, K. Overview of deep learning in medical imaging. Radiol. Phys. Technol. 10, 1–17 (2017).

    Google Scholar 

  155. 155.

    Garcia-Allende, P. B. et al. Towards clinically translatable NIR fluorescence molecular guidance for colonoscopy. Biomed. Opt. Express 5, 78–92 (2013).

    PubMed  PubMed Central  Google Scholar 

  156. 156.

    Pelargos, P. E. et al. Utilizing virtual and augmented reality for educational and clinical enhancements in neurosurgery. J. Clin. Neurosci. 35, 1–4 (2016).

    PubMed  Google Scholar 

  157. 157.

    Nicolau, S. et al. Augmented reality in laparoscopic surgical oncology. Surg. Oncol. 20, 189–201 (2011).

    PubMed  Google Scholar 

  158. 158.

    Kandiah, K. et al. OC-054 Development and validation of a classification system to identify Barrett’s neoplasia using acetic acid chromoendoscopy: the predict classification. Gut 65(31), 1–31 (2016).

    Google Scholar 

  159. 159.

    Longcroft-Wheaton, G. et al. Duration of acetowhitening as a novel objective tool for diagnosing high risk neoplasia in Barrett’s esophagus: a prospective cohort trial. Endoscopy 45, 426–432 (2013).

    CAS  PubMed  Google Scholar 

  160. 160.

    Wilson, B. C., Jermyn, M. & Leblond, F. Challenges and opportunities in clinical translation of biomedical optical spectroscopy and imaging. J. Biomed. Opt. 23, 1–13 (2018).

    PubMed  Google Scholar 

  161. 161.

    ICNIRP. ICNIRP guidelines on limits of exposure to incoherent visible and infrared radiation. Health Phys. 71, 804–819 (2013).

    Google Scholar 

  162. 162.

    Brookner, C. K. et al. Safety analysis: relative risks of ultraviolet exposure from fluorescence spectroscopy and colposcopy are comparable. Photochem. Photobiol. 65, 1020–1025 (1997).

    CAS  PubMed  Google Scholar 

  163. 163.

    EU. Directive 2006/25/EC of the European Parliament and of the Council of 5th of April 2006. Official J. European Union L114, 38–60 (2006); https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:114:0038:0059:en:PDF

  164. 164.

    Performance Measurements of Positron Emission Tomographs (PETs) (NEMA, 2013); https://www.nema.org/Standards/Pages/Performance-Measurements-of-Positron-Emission-Tomographs.aspx

  165. 165.

    Boellaard, R. et al. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur. J. Nucl. Med. Mol. Imaging 42, 328–354 (2014).

    PubMed  PubMed Central  Google Scholar 

  166. 166.

    Zhu, B. et al. Determining the performance of fluorescence molecular imaging devices using traceable working standards with SI units of radiance. IEEE Trans. Med. Imaging 0062, 1 (2015).

    Google Scholar 

  167. 167.

    Downs-Kelly, E. et al. Poor interobserver agreement in the distinction of high-grade dysplasia and adenocarcinoma in pretreatment Barrett’s esophagus biopsies. Am. J. Gastroenterol. 103, 2333–2340 (2008).

    PubMed  Google Scholar 

  168. 168.

    O’Connor, J. P. B. et al. Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome. Clin. Cancer Res. 21, 249–257 (2015).

    PubMed  Google Scholar 

  169. 169.

    Usher-Smith, J. A., Sharp, S. J. & Griffin, S. J. The spectrum effect in tests for risk prediction, screening, and diagnosis. BMJ 353, i3139 (2016).

    PubMed  PubMed Central  Google Scholar 

  170. 170.

    Calin, M. A. et al. Hyperspectral imaging in the medical field: present and future. Appl. Spectrosc. Rev. 49, 435–447 (2014).

    Google Scholar 

  171. 171.

    Grosenick, D. et al. Review of optical breast imaging and spectroscopy. J. Biomed. Opt. 21, 091311 (2016).

    PubMed  Google Scholar 

  172. 172.

    Fuks, D. et al. Intraoperative confocal laser endomicroscopy for real-time in vivo tissue characterization during surgical procedures. Surg. Endosc. https://doi.org/10.1007/s00464-018-6442-3 (2018).

    PubMed  Google Scholar 

  173. 173.

    Kassianos, A. P. et al. Smartphone applications for melanoma detection by community, patient and generalist clinician users: a review. Br. J. Dermatol. 172, 1507–1518 (2015).

    CAS  PubMed  Google Scholar 

  174. 174.

    Farahani, N. et al. International telepathology: promises and pitfalls. Pathobiology 83, 121–126 (2016).

    PubMed  Google Scholar 

  175. 175.

    Tensen, E. et al. Two decades of teledermatology: current status and integration in national healthcare systems. Curr. Dermatol. Rep. 5, 96–104 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  176. 176.

    Cohen, J. D. et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science 359, 926–930 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  177. 177.

    Chi, C. et al. Intraoperative imaging-guided cancer surgery: from current fluorescence molecular imaging methods to future multi-modality imaging technology. Theranostics 4, 1072–1084 (2014).

    PubMed  PubMed Central  Google Scholar 

  178. 178.

    De Boer, E. et al. Optical innovations in surgery. Br. J. Surg. 102, 56–72 (2015).

    Google Scholar 

  179. 179.

    Heinzmann, K. et al. Multiplexed imaging for diagnosis and therapy. Nat. Biomed. Eng. 1, 697–713 (2017).

    PubMed  Google Scholar 

  180. 180.

    Bhat, Y. M. et al. High-definition and high-magnification endoscopes. Gastrointest. Endosc. 80, 919–927 (2014).

    Google Scholar 

  181. 181.

    Medical Systems (Olympus Technologies, 2017); https://www.olympus-europa.com/medical/en/medical_systems/technologies/narrow_band_imaging__nbi_1/technologies_nbi.jsp

  182. 182.

    FICE Dual Mode (Fujifilm Europe, 2017); https://www.fujifilm.eu/eu/products/medical-systems/endoscopy/technology/fice-dual-mode.

  183. 183.

    i-Scan Imaging (Pentax Medical, 2017); https://www.pentaxmedical.com/pentax/en/95/1/i-scan-imaging

  184. 184.

    About SIMSYS-MoleMate (MedX Health, 2017); http://medxhealth.com/Our-Products/SIAscopytrade;/overview.aspx.

  185. 185.

    MelaFind http://www.melafind.com (accessed 26 April 2017).

  186. 186.

    Manfredi, M. A. et al. Electronic chromoendoscopy. Gastrointest. Endosc. 81, 249–261 (2015).

    PubMed  Google Scholar 

  187. 187.

    Rameshshanker, R. & Wilson, A. Electronic imaging in colonoscopy: clinical applications and future prospects. Curr. Treat. Options Gastroenterol. 14, 140–151 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  188. 188.

    Lu, G. & Fei, B. Medical hyperspectral imaging: a review. J. Biomed. Opt. 19, 10901 (2014).

    PubMed  Google Scholar 

  189. 189.

    Jang, J. The past, present, and future of image-enhanced endoscopy. Clin. Endosc. 48, 466–475 (2015).

    PubMed  PubMed Central  Google Scholar 

  190. 190.

    DERMA Medical Systems https://www.dermamedicalsystems.com/index.php?menu_id=117 (accessed 2 May 2017).

  191. 191.

    Alali, S. & Vitkin, A. Polarized light imaging in biomedicine: emerging Mueller matrix methodologies for bulk tissue assessment. J. Biomed. Opt. 20, 61104 (2015).

    PubMed  Google Scholar 

  192. 192.

    Cellvizio: Our Flagship Product (Mauna Kea Technologies, 2017); http://www.maunakeatech.com/en/hospital-administrators/cellvizio-solution

  193. 193.

    OptiScan ViewnVivo. http://viewnvivo.com/ (accessed 26 April 2017).

  194. 194.

    Clinical Applications: Noninvasive cellular imaging of the skin (Caliber ID, 2017); http://www.caliberid.com/clinical.html

  195. 195.

    Wong Kee Song, L. M. et al. Autofluorescence imaging. Gastrointest. Endosc. 73, 647–650 (2011).

    Google Scholar 

  196. 196.

    DermaInspect (Jenlab, 2017); http://www.jenlab.de/DermaInspect.29.0.html

  197. 197.

    Hanson, K. M. & Bardeen, C. J. Application of nonlinear optical microscopy for imaging skin. Photochem. Photobiol. 85, 33–44 (2009).

    CAS  PubMed  Google Scholar 

  198. 198.

    Fu, L. & Gu, M. Fibre-optic nonlinear optical microscopy and endoscopy. J. Microsc. 226, 195–206 (2007).

    CAS  PubMed  Google Scholar 

  199. 199.

    Thomas, G. et al. Advances and challenges in label-free nonlinear optical imaging using two-photon excitation fluorescence and second harmonic generation for cancer research. J. Photochem. Photobiol. B Biol. 141, 128–138 (2014).

    CAS  Google Scholar 

  200. 200.

    NvisionVLE Imaging System (NinePoint Medical Inc, 2017); http://www.ninepointmedical.com/nvisionvle-imaging-system/

  201. 201.

    Vivosight (Michelson Diagnostics, 2017); https://vivosight.com/about-us/product/

  202. 202.

    A. J. Trindade, A. J., Smith, M. S. & Pleskow, D. K. The new kid on the block for advanced imaging in Barrett’s esophagus: a review of volumetric laser endomicroscopy. Therap. Adv. Gastroenterol. 9, 408–416 (2016).

    Google Scholar 

  203. 203.

    Kallaway, C. et al. Advances in the clinical application of Raman spectroscopy for cancer diagnostics. Photodiagnosis Photodyn. Ther. 10, 207–219 (2013).

    CAS  PubMed  Google Scholar 

  204. 204.

    Wang, W. et al. Real-time in vivo cancer diagnosis using raman spectroscopy. J. Biophotonics 8, 527–545 (2015).

    CAS  PubMed  Google Scholar 

  205. 205.

    Tu, Q. & Chang, C. Diagnostic applications of Raman spectroscopy. Nanomed. Nanotechnol. Biol. Med. 8, 545–558 (2012).

    CAS  Google Scholar 

  206. 206.

    SpectraScience and PENTAX Medical Announce Expanded Distribution of WavSTAT4 Optical Biopsy System in Europe. PENTAX Medical (24 April 2013).

  207. 207.

    Benes, Z. & Antos, Z. Optical biopsy system distinguishing between hyperplastic and adenomatous polyps in the colon during colonoscopy. Anticancer Res. 29, 4737–4739 (2009).

    PubMed  Google Scholar 

  208. 208.

    Boerwinkel, D. F. et al. Fluorescence spectroscopy incorporated in an Optical Biopsy System for the detection of early neoplasia in Barrett’s esophagus. Dis. Esophagus 28, 345–351 (2014).

    PubMed  Google Scholar 

  209. 209.

    Yu, G. Near-infrared diffuse correlation spectroscopy in cancer diagnosis and therapy monitoring. J. Biomed. Opt. 17, 010901 (2012).

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to thank F. Walter of the University of Cambridge for helpful comments on our manuscript. D.J.W., C.R.M.F. and S.E.B. are financially supported by CRUK (C14303/A17197, C47594/A16267, C47594/A21102, C55962/A24669) and EPSRC (C197/A16465, EP/N014588/1).

Author information

Affiliations

Authors

Contributions

D.J.W., J.P.B.O. and S.E.B. conceived the manuscript. D.J.W. researched and wrote the manuscript together with C.R.M.F. B.W.P. reviewed and edited the manuscript. All authors discussed and agreed with the final version of the manuscript.

Corresponding author

Correspondence to Sarah E. Bohndiek.

Ethics declarations

Competing interests

S.E.B. receives research support from iThera Medical GmbH and PreXion Inc., and chairs the International Photoacoustic Standardisation Consortium (IPASC).

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Waterhouse, D.J., Fitzpatrick, C.R.M., Pogue, B.W. et al. A roadmap for the clinical implementation of optical-imaging biomarkers. Nat Biomed Eng 3, 339–353 (2019). https://doi.org/10.1038/s41551-019-0392-5

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing