Summary

将反射式共聚焦显微镜与光学相干断层扫描相结合,通过图像采集进行皮肤癌的无创诊断

Published: August 18, 2022
doi:

Summary

在这里,我们描述了使用反射共聚焦显微镜(RCM)和RCM和光学相干断层扫描(OCT)组合的新型无创成像设备获取高质量图像的协议。我们还让临床医生熟悉他们的临床应用,以便他们可以将这些技术整合到常规的临床工作流程中,以改善患者护理。

Abstract

皮肤癌是全球最常见的癌症之一。诊断依赖于肉眼检查和皮肤镜检查,然后进行活检以确认组织病理学。虽然皮肤镜检查的敏感性很高,但较低的特异性导致 70%-80% 的活检在组织病理学上被诊断为良性病变(皮肤镜检查呈假阳性)。

反射共聚焦显微镜(RCM)和光学相干断层扫描(OCT)成像可以无创地指导皮肤癌的诊断。RCM 可视化 面层 中的细胞形态。与皮肤镜检查相比,它使黑色素瘤和色素性角质形成细胞性皮肤癌的诊断特异性提高了一倍,使良性病变的活检数量减少了一半。RCM在美国获得了计费代码,现在正在整合到诊所中。

然而,成像深度浅 (~200 μm)、非色素性皮肤病变对比度差以及面 成像等局限性导致检测非色素基底细胞癌 (BCC) 的特异性相对较低,即与基底细胞层相邻的浅表基底细胞癌和更深的浸润性基底细胞癌。相比之下,OCT缺乏细胞分辨率,但在垂直平面上对组织进行成像,深度为~1毫米,这允许检测基底细胞癌的浅表和深层亚型。因此,这两种技术本质上是互补的。

“多模态”组合RCM-OCT设备同时以 面部 和垂直模式对皮肤病变进行成像。它有助于基底细胞癌的诊断和管理(浅表基底细胞癌的非手术治疗与深层病变的手术治疗)。与单独使用 RCM 相比,检测小的、无色素的基底细胞癌的特异性显著提高。RCM和RCM-OCT设备正在为皮肤癌的诊断和管理带来重大的范式转变;然而,它们的使用目前仅限于学术三级护理中心和一些私人诊所。本文使临床医生熟悉这些设备及其应用,解决常规临床工作流程中的转化障碍。

Introduction

传统上,皮肤癌的诊断依赖于对病变的目视检查,然后使用称为皮肤镜的放大镜仔细观察可疑病变。皮肤镜提供地下信息,与用于诊断皮肤癌的目视检查相比,该信息提高了灵敏度和特异性12。然而,皮肤镜检查缺乏细胞细节,通常需要活检以确认组织病理学。皮肤镜检查 3 的特异性低且可变(67%-97%),导致假阳性和活检,结果显示病理学上的良性病变。活检不仅是一种导致出血和疼痛的侵入性手术4 ,而且由于疤痕而在美容敏感区域(例如面部)也是非常不希望的。

为了通过克服现有的局限性来改善患者护理,正在探索许多非侵入性体内成像设备567891011,12,13,14,1516,1718.RCM和OCT设备是用于诊断皮肤病变,尤其是皮肤癌的两种主要的光学非侵入性设备。RCM已在美国获得当前程序术语(CPT)计费代码,并越来越多地用于学术三级护理中心和一些私人诊所7819。RCM 以近组织学(细胞)分辨率对病变进行成像。然而,图像位于面部平面(一次一层皮肤的可视化)中,成像深度限制在~200μm,足以仅到达浅表(状)真皮。RCM成像依赖于皮肤中各种结构的反射对比度。黑色素具有最高的对比度,使色素病变明亮且易于诊断。因此,与色素性病变(包括黑色素瘤)的皮肤镜检查相比,RCM 联合皮肤镜检查显著改善了诊断(敏感性为 90%,特异性为 82%)20。然而,由于粉红色病变中缺乏黑色素对比,尤其是对于基底细胞癌,RCM的特异性较低(37.5%-75.5%)21。传统的OCT设备是另一种常用的无创设备,可对皮肤内深度达1毫米的病变进行成像,并在垂直平面上可视化(类似于组织病理学)9。然而,OCT缺乏细胞分辨率。OCT 主要用于诊断角质形成细胞病变,尤其是基底细胞癌,但特异性仍然较低9

因此,为了克服这些器件的现有局限性,已经构建了多模态RCM-OCT器件22。该设备将RCM和OCT集成到单个手持式成像探头中,可以同时采集病变的共配准面部RCM图像和垂直OCT图像。OCT提供病变的结构细节,并且可以在皮肤内更深(深度可达~1毫米)成像。与手持式RCM设备(~0.75 mm x 0.75 mm)相比,它还具有~2 mm22的更大视场(FOV)。RCM图像用于提供OCT上识别的病变的细胞细节。该原型尚未商业化,正在诊所232425中用作研究设备。

尽管它们在改善皮肤癌的诊断和管理方面取得了成功(如文献所支持的那样),但这些设备尚未在临床中广泛使用。这主要是由于缺乏能够读取这些图像的专家,但也是由于缺乏训练有素的技术人员,他们可以在床边有效地(在临床时间范围内)获得诊断质量的图像8。在本手稿中,目标是促进这些设备在诊所的意识和最终采用。为了实现这一目标,我们让皮肤科医生、皮肤病理学家和莫氏外科医生熟悉使用 RCM 和 RCM-OCT 设备获取的正常皮肤癌和皮肤癌的图像。我们还将详细介绍每种设备在皮肤癌诊断中的效用。最重要的是,本手稿的重点是为使用这些设备采集图像提供分步指导,这将确保临床使用的高质量图像。

Protocol

下面描述的所有协议都遵循机构人类研究伦理委员会的指导方针。 1. RCM设备及成像协议 注意:有两种市售的 体内 RCM设备:宽探针RCM(WP-RCM)和手持式RCM(HH-RCM)。WP-RCM集成了数字皮肤镜。这两种设备可单独使用或作为组合单元提供。以下是使用最新一代(第 4 代)WP-RCM 和 HH-RCM 设备的图像采集协议及其临床适应症。 病变选择…

Representative Results

反射式共聚焦显微镜 (RCM)RCM上的图像解释:RCM图像的解释方式模仿组织病理学载玻片的评估。首先评估马赛克以获得整体建筑细节并确定关注区域,类似于在扫描放大率(2x)上评估组织学部分。然后放大马赛克以评估细胞细节,类似于在高放大倍率(20x)下评估幻灯片。 图 8 显示了图像分析的这种模式。 图像?…

Discussion

在本文中,我们描述了使用 体内 RCM和RCM-OCT设备进行图像采集的协议。目前,有两种商用RCM设备:宽探头或臂装RCM(WP-RCM)设备和手持式RCM(HH-RCM)设备。了解何时在临床环境中使用这些设备至关重要。癌症类型和位置是决定设备选择的主要因素。

WP-RCM设备非常适合平坦和轻微起伏的身体表面的病变,例如躯干和四肢,因为它需要与皮肤接触。由于探头很宽,因此不?…

Divulgations

The authors have nothing to disclose.

Acknowledgements

特别感谢Kwami Ketosugbo和Emily Cowen作为成像志愿者。这项研究由美国国家癌症研究所/国立卫生研究院(P30-CA008748)向纪念斯隆凯特琳癌症中心提供的资助资助。

Materials

Crystal Plus 500FG mineral oil STE Oil Company, Inc. A food grade, high viscous mineral oil used with our various devices during in vivo imaging.
RCM-OCT Physical Science Inc. A “multi-modal” combined RCM-OCT device simultaneously images skin lesions in both horizonal and vertical modes.
Vivascope 1500 Caliber I.D. A wide-probe RCM (WP-RCM) device that attaches to the skin to campture in vivo devices.
Vivascope 3000 Caliber I.D. A hand-held RCM (HH-RCM) device that is moved across the skin to capture in vivo images.

References

  1. Argenziano, G., et al. Accuracy in melanoma detection: A 10-year multicenter survey. Journal of the American Academy of Dermatology. 67 (1), 54-59 (2012).
  2. Vestergaard, M. E., Macaskill, P., Holt, P. E., Menzies, S. W. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: A meta-analysis of studies performed in a clinical setting. British Journal of Dermatology. 159 (3), 669-676 (2008).
  3. Reiter, O., et al. The diagnostic accuracy of dermoscopy for basal cell carcinoma: A systematic review and meta-analysis. Journal of the American Academy of Dermatology. 80 (5), 1380-1388 (2019).
  4. Abhishek, K., Khunger, N. Complications of skin biopsy. Journal of Cutaneous and Aesthetic Surgery. 8 (4), 239-241 (2015).
  5. Navarrete-Dechent, C., Fischer, C., Tkaczyk, E., Jain, M., Rao, B. K. Chapter 5: Principles of non-invasive diagnostic techniques in dermatology. Moschella and Hurley’s Dermatology. 1, (2019).
  6. Wassef, C., Rao, B. K. Uses of non-invasive imaging in the diagnosis of skin cancer: An overview of the currently available modalities. International Journal of Dermatology. 52 (12), 1481-1489 (2013).
  7. Rajadhyaksha, M., Marghoob, A., Rossi, A., Halpern, A. C., Nehal, K. S. Reflectance confocal microscopy of skin in vivo: From bench to bedside. Lasers in Surgery and Medicine. 49 (1), 7-19 (2017).
  8. Jain, M., Pulijal, S. V., Rajadhyaksha, M., Halpern, A. C., Gonzalez, S. Evaluation of bedside diagnostic accuracy, learning curve, and challenges for a novice reflectance confocal microscopy reader for skin cancer detection in vivo. JAMA Dermatology. 154 (8), 962-965 (2018).
  9. Sattler, E., Kästle, R., Welzel, J. Optical coherence tomography in dermatology. Journal of Biomedical Optics. 18 (6), 061224 (2013).
  10. Wang, Y. -. J., Huang, Y. -. K., Wang, J. -. Y., Wu, Y. -. H. In vivo characterization of large cell acanthoma by cellular resolution optical coherent tomography. Photodiagnosis and Photodynamic Therapy. 26, 199-202 (2019).
  11. Balu, M., et al. Distinguishing between benign and malignant melanocytic nevi by in vivo multiphoton microscopy. Recherche en cancérologie. 74 (10), 2688-2697 (2014).
  12. Balu, M., et al. In vivo multiphoton microscopy of basal cell carcinoma. JAMA Dermatology. 151 (10), 1068-1074 (2015).
  13. Lentsch, G., et al. Non-invasive optical biopsy by multiphoton microscopy identifies the live morphology of common melanocytic nevi. Pigment Cell and Melanoma Research. 33 (6), 869-877 (2020).
  14. Dimitrow, E., et al. Sensitivity and specificity of multiphoton laser tomography for in vivo and ex vivo diagnosis of malignant melanoma. Journal of Investigative Dermatology. 129 (7), 1752-1758 (2009).
  15. Ruini, C., et al. Line-field optical coherence tomography: In vivo diagnosis of basal cell carcinoma subtypes compared with histopathology. Clinical and Experimental Dermatology. 46 (8), 1471-1481 (2021).
  16. Suppa, M., et al. Line-field confocal optical coherence tomography of basal cell carcinoma: A descriptive study. Journal of the European Academy of Dermatology and Venereology. 35 (5), 1099-1110 (2021).
  17. Wang, Y. J., Wang, J. Y., Wu, Y. H. Application of cellular resolution full-field optical coherence tomography in vivo for the diagnosis of skin tumours and inflammatory skin diseases: A pilot study. Dermatology. 238 (1), 121-131 (2022).
  18. Jain, M., et al. Rapid evaluation of fresh ex vivo kidney tissue with full-field optical coherence tomography. Journal of Pathology Informatics. 6, 53 (2015).
  19. Mehta, P. P., et al. Patterns of use of reflectance confocal microscopy at a tertiary referral dermatology clinic. Journal of the American Academy of Dermatology. , (2021).
  20. Dinnes, J., et al. Reflectance confocal microscopy for diagnosing cutaneous melanoma in adults. Cochrane Database of Systematic Reviews. 12 (12), (2018).
  21. Dinnes, J., et al. Reflectance confocal microscopy for diagnosing keratinocyte skin cancers in adults. Cochrane Database of Systematic Reviews. 12 (12), (2018).
  22. Iftimia, N., et al. Handheld optical coherence tomography-reflectance confocal microscopy probe for detection of basal cell carcinoma and delineation of margins. Journal of Biomedical Optics. 22 (7), 76006 (2017).
  23. Monnier, J., et al. Combined reflectance confocal microscopy and optical coherence tomography to improve the diagnosis of equivocal lesions for basal cell carcinoma. Journal of the American Academy of Dermatology. 86 (4), 934-936 (2021).
  24. Navarrete-Dechent, C., et al. Management of complex head-and-neck basal cell carcinomas using a combined reflectance confocal microscopy/optical coherence tomography: a descriptive study. Archives of Dermatological Research. 313 (3), 193-200 (2021).
  25. Sahu, A., et al. Evaluation of a combined reflectance confocal microscopy-optical coherence tomography device for detection and depth assessment of basal cell carcinoma. JAMA Dermatology. 154 (10), 1175-1183 (2018).
  26. Rubinstein, G., Garfinkel, J., Jain, M. Live, remote control of an in vivo reflectance confocal microscope for diagnosis of basal cell carcinoma at the bedside of a patient 2500 miles away: A novel tele-reflectance confocal microscope approach. Journal of the American Academy of Dermatology. 81 (2), 41-42 (2019).
  27. Scope, A., et al. In vivo reflectance confocal microscopy imaging of melanocytic skin lesions: Consensus terminology glossary and illustrative images. Journal of the American Academy of Dermatology. 57 (4), 644-658 (2007).
  28. Calzavara-Pinton, P., Longo, C., Venturini, M., Sala, R., Pellacani, G. Reflectance confocal microscopy for in vivo skin imaging. Photochemistry and Photobiology. 84 (6), 1421-1430 (2008).
  29. Rajadhyaksha, M., Grossman, M., Esterowitz, D., Webb, R. H., Anderson, R. R. In vivo confocal scanning laser microscopy of human skin: Melanin provides strong contrast. Journal of Investigative Dermatology. 104 (6), 946-952 (1995).
  30. Gonzalez, S., Gonzalez, E., White, W. M., Rajadhyaksha, M., Anderson, R. R. Allergic contact dermatitis: Correlation of in vivo confocal imaging to routine histology. Journal of the American Academy of Dermatology. 40 (5), 708-713 (1999).
  31. Sahu, A., et al. Combined PARP1-targeted nuclear contrast and reflectance contrast enhances confocal microscopic detection of basal cell carcinoma. Journal of Nuclear Medicine. 63 (6), 912-918 (2021).
  32. González, S., Sackstein, R., Anderson, R. R., Rajadhyaksha, M. Real-time evidence of in vivo leukocyte trafficking in human skin by reflectance confocal microscopy. Journal of Investigative Dermatology. 117 (2), 384-386 (2001).
  33. Navarrete-Dechent, C., et al. Reflectance confocal microscopy terminology glossary for nonmelanocytic skin lesions: A systematic review. Journal of the American Academy of Dermatology. 80 (5), 1414-1427 (2019).
  34. Navarrete-Dechent, C., et al. Reflectance confocal microscopy terminology glossary for melanocytic skin lesions: A systematic review. Journal of the American Academy of Dermatology. 84 (1), 102-119 (2021).
  35. Sattler, E., Kastle, R., Welzel, J. Optical coherence tomography in dermatology. Journal of Biomedical Optics. 18 (6), 061224 (2013).
  36. Park, E. S. Skin-layer analysis using optical coherence tomography. Medical Lasers. 3 (1), 1-4 (2014).
  37. Marra, D. E., Torres, A., Schanbacher, C. F., Gonzalez, S. Detection of residual basal cell carcinoma by in vivo confocal microscopy. Dermatologic Surgery. 31 (5), 538-541 (2005).
  38. Alarcon, I., et al. In vivo reflectance confocal microscopy to monitor the response of lentigo maligna to imiquimod. Journal of the American Academy of Dermatology. 71 (1), 49-55 (2014).
  39. Guitera, P., et al. Surveillance for treatment failure of lentigo maligna with dermoscopy and in vivo confocal microscopy: new descriptors. British Journal of Dermatology. 170 (6), 1305-1312 (2014).
  40. Menge, T. D., Hibler, B. P., Cordova, M. A., Nehal, K. S., Rossi, A. M. Concordance of handheld reflectance confocal microscopy (RCM) with histopathology in the diagnosis of lentigo maligna (LM): A prospective study. Journal of the American Academy of Dermatology. 74 (6), 1114-1120 (2016).
  41. Chen, C. S., Elias, M., Busam, K., Rajadhyaksha, M., Marghoob, A. A. Multimodal in vivo optical imaging, including confocal microscopy, facilitates presurgical margin mapping for clinically complex lentigo maligna melanoma. British Journal of Dermatology. 153 (5), 1031-1036 (2005).
  42. Yelamos, O., et al. Handheld reflectance confocal microscopy for the detection of recurrent extramammary Paget disease. JAMA Dermatology. 153 (7), 689-693 (2017).
  43. Ardigo, M., Longo, C., Gonzalez, S. Multicentre study on inflammatory skin diseases from The International Confocal Working Group: Specific confocal microscopy features and an algorithmic method of diagnosis. British Journal of Dermatology. 175 (2), 364-374 (2016).
  44. Moscarella, E., Argenziano, G., Lallas, A., Pellacani, G., Longo, C. Confocal microscopy: A new era in understanding the pathophysiologic background of inflammatory skin diseases. Experimental Dermatology. 23 (5), 320-321 (2014).
  45. Bertrand, C., Corcuff, P. In vivo spatio-temporal visualization of the human skin by real-time confocal microscopy. Scanning. 16 (3), 150-154 (1994).
  46. Saknite, I., et al. Features of cutaneous acute graft-versus-host disease by reflectance confocal microscopy. British Journal of Dermatology. 181 (4), 829-831 (2019).
  47. Aleissa, S., et al. Presurgical evaluation of basal cell carcinoma using combined reflectance confocal microscopy-optical coherence tomography: A prospective study. Journal of the American Academy of Dermatology. 82 (4), 962-968 (2020).
  48. Bang, A. S., et al. Noninvasive, in vivo, characterization of cutaneous metastases using a novel multimodal RCM-OCT imaging device: A case-series. Journal of the European Academy of Dermatology and Venereology. , (2022).
  49. Dickensheets, D. L., Kreitinger, S., Peterson, G., Heger, M., Rajadhyaksha, M. Wide-field imaging combined with confocal microscopy using a miniature f/5 camera integrated within a high NA objective lens. Optics Letters. 42 (7), 1241-1244 (2017).
  50. Kose, K., et al. Automated video-mosaicking approach for confocal microscopic imaging in vivo: an approach to address challenges in imaging living tissue and extend field of view. Scientific Reports. 7 (1), 10759 (2017).
  51. Zhao, J., et al. Deep learning-based denoising in high-speed portable reflectance confocal microscopy. Lasers in Surgery and Medicine. 53 (6), 880-891 (2021).
  52. Curiel-Lewandrowski, C., Stratton, D. B., Gong, C., Kang, D. Preliminary imaging of skin lesions with near-infrared, portable, confocal microscopy. Journal of the American Academy of Dermatology. 85 (6), 1624-1625 (2021).
  53. Freeman, E. E., et al. Feasibility and implementation of portable confocal microscopy for point-of-care diagnosis of cutaneous lesions in a low-resource setting. Journal of the American Academy of Dermatology. 84 (2), 499-502 (2021).
  54. Peterson, G., et al. Feasibility of a video-mosaicking approach to extend the field-of-view for reflectance confocal microscopy in the oral cavity in vivo. Lasers in Surgery and Medicine. 51 (5), 439-451 (2019).
  55. Kurugol, S., et al. Automated delineation of dermal-epidermal junction in reflectance confocal microscopy image stacks of human skin. Journal of Investigative Dermatology. 135 (3), 710-717 (2015).
  56. Kose, K., et al. Utilizing machine learning for image quality assessment for reflectance confocal microscopy. Journal of Investigative Dermatology. 140 (6), 1214-1222 (2020).
  57. Campanella, G., et al. Deep learning for basal cell carcinoma detection for reflectance confocal microscopy. Journal of Investigative Dermatology. 142 (1), 97-103 (2022).
  58. Wodzinski, M., Skalski, A., Witkowski, A., Pellacani, G., Ludzik, J. Convolutional neural network approach to classify skin lesions using reflectance confocal microscopy. 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBC 2019. , (2019).
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Harris, U., Rajadhyaksha, M., Jain, M. Combining Reflectance Confocal Microscopy with Optical Coherence Tomography for Noninvasive Diagnosis of Skin Cancers via Image Acquisition. J. Vis. Exp. (186), e63789, doi:10.3791/63789 (2022).

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