Raman spectroscopy differentiates squamous cell carcinoma (SCC) from normal skin following treatment with a high‐powered CO<sub>2</sub> laser

Fox, Sara; Shanblatt, Ashley A.; Beckman, Hugh; Strasswimmer, John; Terentis, Andrew C.

doi:10.1002/lsm.22288

Cited by 23 publications

(29 citation statements)

References 53 publications

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“…Two studies [ 19 , 23 ] examined SCC samples ex vivo. The pooled sensitivity and specificity of Raman spectroscopy for discriminating SCC samples and normal tissues in vivo were 0.96 (95% CI 0.81–1.00) and 1.00 (95% CI 0.92–1.00), respectively.…”

Section: Resultsmentioning

confidence: 99%

“…The most important reason might be that in vivo detection could provide less information about the lesions towing to the limited time to collect Raman images. [ 19 ] Ex vivo Raman images by scanning across the surface of the lesions could provide the spatial distribution of different tissue structures. However, it usually takes a long period of time.…”

Section: Discussionmentioning

confidence: 99%

“…It would not be feasible for in vivo use, as it is hard for the patients to keep highly immobilized to obtain high spatial-resolution images. [ 18 , 19 ] There is a dearth of studies focused on in vivo detection, whereas many reports have demonstrated various ex vivo detection. [ 18 ] Thus, continued patient recruitment and future development of in vivo RS will be necessary to elucidate this matter.…”

Section: Discussionmentioning

confidence: 99%

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Accuracy of Raman spectroscopy for differentiating skin cancer from normal tissue

et al. 2018

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Background:Raman spectroscopy could be applied to distinguish tumor from normal tissues. This meta-analysis assessed the accuracy of Raman spectroscopy in differentiating skin cancer from normal tissue.Methods:PubMed, Embase, Cochrane Library, and CNKI were searched to identify suitable studies before Februray 4th, 2018. We estimated the pooled sensitivity, specificity, positive, and negative likelihood ratios, diagnostic odds ratio, and constructed summary receiver-operating characteristics curves to identify the accuracy of Raman spectroscopy in differentiating skin cancer from normal tissue.Results:A total of 12 studies with 2461 spectra were included. For basal cell skin cancer (BCC) ex vivo detection, the pooled sensitivity and specificity were 0.99 (95% confidence interval [CI] 0.97–0.99) and 0.96 (95% CI 0.95–0.97), respectively. The area under the curve (AUC) was 0.9837. For BCC in vivo detection, the pooled sensitivity and specificity were 0.69 (95% CI 0.61–0.76) and 0.85 (95% CI 0.82–0.87), respectively. The AUC was 0.9213. For melanoma (MM) ex vivo detection, the pooled sensitivity and specificity were 1.00 (95% CI 0.91–1.00) and 0.98 (95% CI 0.95–1.00), respectively. The AUC was 0.9914. For MM in vivo detection, the sensitivity (0.93) and the specificity (0.96) balanced relatively well. For squamous cell skin cancer (SCC) ex vivo detection, the pooled sensitivity and specificity were 0.96 (95% CI 0.81–1.00) and 1.00 (95% CI 0.92–1.00), respectively. For SCC in vivo detection, the sensitivity was 0.81 (95% CI 0.70–0.90) and the specificity was 0.89 (95% CI 0.86–0.91).Conclusion:This meta-analysis suggested that Raman spectroscopy could be an effective and accurate tool for differentiating BCC, MM, SCC from normal tissue, which would assist us in the diagnosis and treatment of skin cancer.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Accuracy of Raman spectroscopy for differentiating skin cancer from normal tissue

et al. 2018

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“…31 Protein tyrosine sulfation largely serves to strengthen and thereby control the interaction between secreted proteins and pathogens during the innate immune response. 32,33 If so, that explains why tyrosine exhibited an accumulation pattern in the gray matter area, but its pixel intensity is lower than protein composition as depicted by a comparable scale value. On the other side, if the band assigned to C-C stretching in tyrosine, the spectral activity of the phenol side groups is highly sensitive to the orientation of its tyrosine residue.…”

Section: Raman Spectral Imaging Of Mouse Spinal Cord Tissuementioning

confidence: 99%

Interpreting the biochemical specificity of mouse spinal cord by confocal raman microspectral imaging

Gong

Liang

Yin

et al. 2017

J. Innov. Opt. Health Sci.

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Interpreting the biochemical specificity of spinal cord tissue is the essential requirement for understanding the biochemical mechanisms during spinal-cord-related pathological course. In this work, a longitudinal study was implemented to reveal a precise linkage between the spectral features and the molecular composition in ex vivo mouse spinal cord tissue by microspectral Raman imaging. It was testified that lipid-rich white matter could be distinguished from gray matter not only by the lipid Raman peaks at 1064, 1300, 1445 and 1660[Formula: see text]cm[Formula: see text], but also by protein (1250 and 1328[Formula: see text]cm[Formula: see text] and saccharides (913 and 1137[Formula: see text]cm[Formula: see text] distributions. [Formula: see text]-means cluster analysis was further applied to visualize the morphological basis of spinal cord tissue by chemical components and their distribution patterns. Two-dimensional chemical images were then generated to visualize the contrast between two different tissue types by integrating the intensities of the featured Raman bands. All the obtained results illustrated the biochemical characteristics of spinal cord tissue, as well as some specific substance variances between different tissue types, which formed a solid basis for the molecular investigation of spinal cord pathological alterations.

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“…At present, the application of RS is used extensively to identify cancer by analyzing excised tissue, blood plasma, saliva, urine, and seminal fluid (5)(6)(7)(8)(9). Tissue samples obtained timely and even continually during treatment of previously diagnosed patients, are the ideal material for confirming a precise diagnosis (10).…”

Section: Introductionmentioning

confidence: 99%

Label-free discrimination of different stage nasopharyngeal carcinoma tissue based on Raman spectroscopy

Qiu

Huang

et al. 2016

Oncology Letters

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Abstract. The present study aimed to evaluate a label-free tissue test for the detection of nasopharyngeal carcinoma (NPC) at early and advanced stages using Raman spectroscopy (RS). RS measurements were performed to acquire high quality Raman spectra on two groups of tissue samples: One group consists of 30 NPC patients at the early stages (I-II), and the other group is 46 NPC patients at the advanced stages (III-IV). Tentative assignment of Raman bands showed specific biomolecular changes associated with cancer development. Furthermore, effective diagnostic algorithms based on principal components analysis (PCA) and linear discriminant analysis (LDA) were applied for distinguishing Raman spectra of nasopharyngeal tissues from different stages, yielding a diagnostic sensitivity of 70% and a specificity of 78%. This exploratory work suggests that RS in conjunction with the PCA-LDA algorithms provides good diagnostic ability for the early and the advanced staged NPC tissues, and RS has enormous potential for the non-invasive detection of early and advanced stage NPC. IntroductionNasopharyngeal carcinoma (NPC) is a malignant neoplasm and retains a high incidence in Southeast Asia and Southern China (1). An accurate tumor-node-metastasis (TNM) staging system is important for estimating the prognosis of malignant carcinoma, constructing treatment plans, and for predicting the 5-year overall survival rate (OS) of NPC (2). The 5-year OS rates of stage I, II, III, and IV NPC are 94, 87, 77 and 65%, respectively (3). It can be difficult to make an early diagnosis of this lesion due to the anatomical position of NPC. At present, the protocols used for NPC staging include flexible fiberoptic nasopharyngoscopy pathological biopsy, blood EB-DNA test, computed tomography (CT) of the chest, magnetic resonance imaging (MRI) of the nasopharynx and neck, bone emission computed tomography (ECT) and position emission tomography. These diagnostic processes are invasive, inconvenient, and time-consuming. Therefore, an improved diagnostic method for NPC is required, that can overcome the above disadvantages.Raman spectroscopy (RS) makes use of the inelastic scattering of light, and provides a spectrographic signature of the structure and conformation of specific molecular species, such as proteins, nucleic acids and lipids (4). At present, the application of RS is used extensively to identify cancer by analyzing excised tissue, blood plasma, saliva, urine, and seminal fluid (5-9). Tissue samples obtained timely and even continually during treatment of previously diagnosed patients, are the ideal material for confirming a precise diagnosis (10). Hitherto, RS has been widely utilized to verify diagnoses using excised samples of cancer tissues, such as esophageal cancer, lung cancer, and gastric cancer (11-13). Furthermore, Raman spectroscopy endoscopic analysis of tissues in vivo has demonstrated the potential for detecting cancers such as laryngeal cancer, esophageal cancer, lung cancer, colorectal cancer and bladder cancer (14-18). T...

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Raman spectroscopy differentiates squamous cell carcinoma (SCC) from normal skin following treatment with a high‐powered CO₂ laser

Cited by 23 publications

References 53 publications

Accuracy of Raman spectroscopy for differentiating skin cancer from normal tissue

Accuracy of Raman spectroscopy for differentiating skin cancer from normal tissue

Interpreting the biochemical specificity of mouse spinal cord by confocal raman microspectral imaging

Label-free discrimination of different stage nasopharyngeal carcinoma tissue based on Raman spectroscopy

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Raman spectroscopy differentiates squamous cell carcinoma (SCC) from normal skin following treatment with a high‐powered CO2 laser

Cited by 23 publications

References 53 publications

Accuracy of Raman spectroscopy for differentiating skin cancer from normal tissue

Accuracy of Raman spectroscopy for differentiating skin cancer from normal tissue

Interpreting the biochemical specificity of mouse spinal cord by confocal raman microspectral imaging

Label-free discrimination of different stage nasopharyngeal carcinoma tissue based on Raman spectroscopy

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Raman spectroscopy differentiates squamous cell carcinoma (SCC) from normal skin following treatment with a high‐powered CO₂ laser