1.

Introduction

Cervical cancer is the second most common malignancy in women worldwide.¹ Early detection and localization of precancer in the cervix with effective treatment is crucial to improving the survival rates of the patients at high risk. The conventional exfoliative cervicovaginal cytology [i.e., Papanicolaou (Pap) smear] tests have high diagnostic specificity of 93% [95% confidence interval (CI): 89 to 97%], but with a relatively low sensitivity of 57% (95% CI: 38 to 76%) for the diagnosis of precancerous lesions in the cervix.² The white-light colposcopy, the common gynecology follow-up for abnormal Pap smears, has a good sensitivity of $\sim 96\%$, but this is tempered by a mediocre detection specificity of $\sim 48\%$ for identifying preneoplastic changes in the cervix.^2,3 While histological identification of cervical precancer and cancer remains the gold standard diagnostic approach, it is impractical as a routine screening tool for high-risk patients who may have multiple suspicious lesions. Therefore, the development of advanced optical diagnostic techniques for improving both the diagnostic sensitivity and specificity is clinically imperative for real-time, accurate diagnosis of cervical precancer in vivo.

Among different optical spectroscopic techniques, near-infrared (NIR) Raman spectroscopy has been recognized as an excellent technique with high biomolecular specificity for in vitro and in vivo diagnosis of malignancies in various organs including in the cervix.^4–11 NIR Raman spectroscopy is a molecule-specific technique for optically probing the vibrations of biomolecules, revealing the highly specific biochemical structures and conformations of tissue and cells. However, Raman signal emanating from tissue is inherently very weak and occurs concurrently with the intense tissue autofluorescence (AF) background. The tissue NIR AF background typically represents the light re-emission from the excited endogenous fluorophores. NIR AF has shown promise in differentiating cancer from normal tissues, probably due to the neoplasia-associated changes in tissue absorption, scattering, or endogenous fluorophore content and distribution in tissue.^4,12 NIR-excited spectroscopy holds potential benefits for safe tissue diagnosis, such as noncarcinogenic and relatively insensitive to tissue water content, compared to the ultraviolet-visible-excited spectroscopy. For instance, the diagnostic capability of the composite NIR AF/Raman spectroscopy together with principal components analysis (PCA) and linear discriminant analysis (LDA) for enhancing the assessment of in vivo skin tumors was demonstrated using mice tumor models.¹² We have also documented the complementary nature of NIR AF and Raman spectroscopy techniques using a volume-type Raman endoscopic probe¹³ and found that combining NIR AF and Raman modalities improved the gastric cancer diagnosis in vivo during gastroscopic inspections.⁴ The diagnostic potential of in vitro NIR AF imaging, as well as in vivo NIR AF spectroscopy, for colonic cancer and precancer detection have also been reported very recently.^8,14,15 However, to date, no systematic studies have been conducted to investigate the diagnostic utility of confocal Raman, NIR AF and the composite NIR AF/Raman spectroscopy for cervical precancer detection. In this work, we use a ball-lens confocal Raman probe, which was developed to acquire spectroscopic information about cervical tissue in vivo. We compare the diagnostic performance of the three spectroscopic modalities (i.e., confocal Raman, NIR AF, and the composite NIR AF/Raman spectroscopy) using PCA-LDA-based diagnostic algorithms and confirm that confocal Raman spectroscopy is the most robust means for improving in vivo diagnosis of cervical precancer at colposcopy.

2.

Materials and Methods

3.

Results

Figure 1 shows the mean in vivo composite NIR AF/Raman, NIR AF, and NIR Raman spectra [Fig. 1(a), 1(c), and 1(e)] together with the corresponding difference spectra [Fig. 1(b), 1(d), and 1(f)], collected from normal ($n=993$) and precancerous ($n=247$) cervical tissues of 84 patients recruited under the guidance of white-light colposcopy. The composite NIR AF/Raman spectra [Fig. 1(a)] exhibit intense, broad but overall decreasing AF intensity curves [fifth-order polynomial fit, Fig. 1(c)] with the superimposed prominent tissue Raman bands [Fig. 1(e)]. The major Raman peaks observed in both normal and precancer cervical tissues are at the following positions with tentative biochemical assignments: $854{\mathrm{cm}}^{-1}$ {glycogen [(CCH) deformation-aromatic] and (C-C) stretching of structural proteins and collagen}, $937{\mathrm{cm}}^{-1}$ (stretching of proline, valine, and glycogen), $1001{\mathrm{cm}}^{-1}$ [($\mathrm{C}─\mathrm{C}$) ring breathing of phenylalanine], $1095{\mathrm{cm}}^{-1}$ (DNA phospholipids backbone), $1253{\mathrm{cm}}^{-1}$ (amide III), $1313{\mathrm{cm}}^{-1}$ (${\mathrm{CH}}_3{\mathrm{CH}}_2$ twisting mode of lipids/proteins), $1445{\mathrm{cm}}^{-1}$ (${\mathrm{CH}}_2$ bending mode of proteins and lipids), and $1654{\mathrm{cm}}^{-1}$ [amide I band, ($\mathrm{C}═\mathrm{O}$) stretching mode of proteins].^7,10,20–22 The comprehensive biomolecular basis of Raman spectroscopic diagnosis of cervical dysplasia has been described in detail elsewhere.^7,9,22 The AF spectra show higher intensity for dysplasia; however, the change in AF intensity associated with dysplastic progression was not significant ($p=0.924$), indicating that the confocal-based NIR AF spectroscopy is inefficient for precancer identification. Conversely, the intensity of Raman-active tissue biochemical constituents changed significantly ($p<0.05$) with precancer transformation. For instance, the dysplastic tissue showed increased Raman signals at 1001, 1095, and $1313{\mathrm{cm}}^{-1}$, but exhibited much lower signals at 854, 937, 1253, 1445, and $1654{\mathrm{cm}}^{-1}$ as compared to the normal tissue.^6,7,20–23 These striking differences in the Raman-active components between different tissue pathologies indicate the diagnostic potential of confocal Raman spectroscopy for rapid in vivo diagnosis of precancer and early cancer in the cervix.

Fig. 1

(a) The mean in vivo composite NIR AF and Raman spectra $\pm 1$ standard errors (SE) and (b) the corresponding mean difference spectrum $\pm 1$ SE from normal ($n=993$) and precancer ($n=247$) cervical tissue, (c) the mean in vivo NIR AF spectra $\pm 1$ SE and (d) the mean difference spectrum $\pm 1$ SE from normal ($n=993$) and precancer ($n=247$) cervical tissue, (e) the mean in vivo NIR Raman spectra $\pm 1$ SE and (f) the mean difference spectrum $\pm 1$ SE from normal ($n=993$) and precancer ($n=247$) cervical tissue. The mean in vivo spectra of precancer cervical tissue were shifted vertically for better visualization. The shaded area represents the respective SE. Note that the SE of precancer and normal Raman signals in Fig. 1(e) have been magnified by 20-fold for better visualization.

PCA-LDA-based multivariate diagnostic algorithms were subsequently rendered on the composite NIR AF/Raman spectra measured to extract the diagnostic information associated with underlying spectroscopy modalities (i.e., confocal Raman, NIR AF, and the composite NIR AF/Raman) for discrimination between dysplasia and normal cervical tissues. The composite NIR AF/Raman spectra were mean centered to eliminate the common variance. Hotelling $T^2$ and Q-residuals were employed to remove the spectra with unusual line shape variations due to noncontact measurements and probe handling variations.¹⁹ Figure 2 shows the diagnostically significant PC loadings [PC4, 0.0023%; PC5, 0.00095%; PC8, 0.00022%, ($p<0.05$)], representing the variations in the major tissue Raman peaks (e.g., 854, 937, 1095, 1253, 1311, 1445, and $1654{\mathrm{cm}}^{-1}$) together with PC1 (99.93%, $p=0.924$), typically exhibiting the broad tissue NIR AF features. LDA classifier was further employed on the diagnostically significant PCs, and the cross-validated classification results for each spectrum belonging to normal and precancer tissue categories were obtained (Fig. 3). The PC1 constituting the tissue AF features rendered a diagnostic accuracy of 59.6% [sensitivity of 49.8% (123/247) and specificity of 69.4% (689/993)]. A diagnostic accuracy of 84.1% [sensitivity of 81.0% (200/247) and specificity of 87.1% (865/993)] could be achieved using PC4, PC5, and PC8, primarily describing the significant tissue Raman spectral features (e.g., 854, 937, 1095, 1253, 1311, 1445, and $1654{\mathrm{cm}}^{-1}$). The PCs representing tissue AF (PC1) as well as Raman features (PC4, PC5, and PC8) were combined together to assess the diagnostic ability of the composite NIR AF/Raman spectroscopy modality, achieving a diagnostic accuracy of 82.3% [sensitivity of 76.9% (190/247) and specificity of 87.7% (871/993)]. In addition, the diagnostic performance of the three spectroscopic modalities was further evaluated by splitting the total dataset into a training set (70% of the total dataset) and a testing set (30% of the total dataset). The redeveloped PCA-LDA models using the PCs representing tissue Raman, the composite NIR AF/Raman, and NIR AF features provided predictive accuracies of 86.1% (95% CI: 83.6 to 88.7%), 85.7% (95% CI: 80.5 to 90.8%), and 59.8% (95% CI: 52.6 to 66.9%) for cervical precancer classification, respectively.

Fig. 2

Principal components (PCs) loadings calculated from the in vivo composite NIR AF/Raman spectra of cervical tissue, revealing the diagnostically significant spectral features for tissue classification. The three diagnostically significant PCs (PC4, 0.0023%; PC5, 0.00095%; PC8, 0.00022%) accounting for about 0.00347% of total variance represented the major tissue Raman peaks. PC1 (99.93%) showed the tissue AF features. The loading on PC1 has been magnified by 200-fold for better visualization.

Fig. 3

Scatter plots of the posterior probability of belonging to normal and precancer categories calculated from the three spectroscopic modalities: (a) composite NIR AF/Raman (PC1, PC4, PC5, PC8); (b) NIR AF (PC1); (c) confocal Raman spectra (PC4, PC5, PC8); (•) Precancer ($n=247$), (○) Normal ($n=993$).

ROC curves were also generated (Fig. 4) to further compare the performance of the PCA-LDA-based diagnostic algorithms developed from the three spectroscopic modalities (confocal Raman, the composite NIR AF/Raman, and NIR AF) for in vivo tissue classification. The areas under the ROC curves (AUC) were 0.88, 0.86, and 0.56 for the PCA-LDA models developed from the confocal Raman, the composite NIR AF/Raman, and NIR AF models, respectively, indicating that the diagnosis achieved using the confocal Raman diagnostic modality was superior to NIR AF spectroscopy, but marginally higher than the composite NIR AF/Raman spectroscopy.

Fig. 4

Receiver operating characteristic (ROC) curves of discrimination results for cervical precancer classification using in vivo confocal Raman, the composite NIR AF/Raman, and NIR AF spectroscopy, respectively, together with PCA-LDA and leave-one patient-out, cross-validation methods. The areas under the ROC curves are 0.88, 0.86, and 0.56 for the confocal Raman, composite NIR AF/Raman, and NIR AF spectroscopy modalities, respectively.

4.

Discussion

In the past decade, substantial research efforts have been made to develop advanced optical spectroscopy modalities for noninvasive in vivo detection of cervical precancer and cancer. In particular, Raman spectroscopy is a unique molecular vibrational technique that has found its remarkable way into routine clinical oncology applications because of its excellent capability of nondestructively probing the changes of biochemical vibrational markers associated with dysplastic transformation. The dysplastic cells initially develop in the epithelium, such that the targeted confocal illumination and collection of signals originating from the epithelial layer in the cervix is essential to improving Raman spectroscopic diagnosis of precancer. Hence, in this study, we utilize a ball-lens confocal Raman probe to selectively measure the in vivo composite NIR AF/Raman spectra, which exhibit the spectral contributions primarily from the epithelial layer of the cervix. Consequently, it can reveal the alterations in the Raman-active molecules related to metabolic changes in the cervical epithelium, while minimizing AF contributions from deeper stromal tissue layer.^9,16,24

The PCA-LDA modeling was performed on the composite NIR AF/Raman spectra measured to extract the PC loadings related to tissue NIR AF (an intense decreasing broad band curve) and Raman features (highly specific tissue biochemical fingerprints), resolving the diagnostic features associated with distinctive spectroscopy modalities. The NIR AF spectra of dysplasia tissue exhibited higher intensity than normal cervical tissue, which was in agreement with the literature.^12,25 However, the origin of NIR AF is not yet well documented. Porphyrin is assumed to be one of the major fluorophores in the NIR region²⁵. The increase of tissue NIR AF with precancer progression could be correlated to the elevated level of porphyrins in cancer or precancer tissue, which has been observed in human breast and bladder tissue,^25,26 as well as animal tumor models.^12,27 The increase of porphyrins in the tumor tissue is probably due to necrosis, microbial contamination of tumor tissue, or the ability to concentrate porphyrins by some types of cells of epithelial origin.^26,28 The hypervascularization in the precancer tissue could also contribute to the increased level of porphyrins.¹² The increase of epithelial fluorescence in dysplasia tissue could also be related to changes of other endogenous fluorophores (e.g., reduced nicotinamide adenine dinucleotide and flavin adenine dinucleotide) with the development of dysplasia in cervical tissue.^29–31 The change in NIR AF spectral line shape was captured by PC1, accounting for the largest percentage of total variance (99.93%). PC1 suggested that the increased NIR AF emission associated with precancer progression was insignificant ($p=0.924$), indicating that the change in the concentration of NIR endogenous fluorophores probed from the epithelial tissue using the confocal Raman probe was inefficient for discriminating the dysplastic lesions from the normal cervical tissue. This resulted in the very poor diagnostic accuracy of 59.6% [sensitivity of 49.8% (123/247) and specificity of 69.4% (689/993)] using the confocal NIR AF spectroscopy (PC1 associated with tissue AF changes) (Fig. 3). The PCA-LDA model developed using the PCs [PC4, 0.0023%; PC5, 0.00095%; PC8, 0.00022% ($p<0.05$)] representing the highly specific tissue Raman signatures was able to extract the diagnostic information related to the molecular changes in dysplastic cervix. These distinctive and significant variations ($p<0.05$) in the relative intensities of Raman bands accompanying dysplastic transformation can be instantly correlated to the changes of tissue biochemical compositions. For instance, the spectra showed decreased glycogen and structural proteins ($854{\mathrm{cm}}^{-1}$), primarily representing the loss of epithelial cell differentiation during neoplastic progression.^22,32 The increased nuclear content ($1095{\mathrm{cm}}^{-1}$) indicated the elevated number of epithelial cells in the dysplastic cervix.^22,32,33 The amide I ($1654{\mathrm{cm}}^{-1}$) and amide III ($1253{\mathrm{cm}}^{-1}$) bands were also noticeably decreased with dysplastic transformation.³³ Hence, the diagnostic model developed using these changes in the concentration of Raman-active biomolecules associated with dysplastic progression yielded the diagnostic accuracy of 84.1% [a sensitivity of 81.0% ($200/247$) and a specificity of 87.1% (865/993)] (Fig. 3), illustrating the diagnostic utility of confocal Raman spectroscopy for in vivo cervical precancer diagnosis at the molecular level.

We also examined if the cocontributions of the composite NIR AF and confocal Raman spectroscopy could improve the precancer detection compared to confocal Raman spectroscopy alone. The PCA-LDA model was redeveloped by combining the PCs constituting the features of both NIR AF and Raman spectroscopy modalities (PC1, PC4, PC5, and PC8). The combined NIR AF/Raman diagnostic model achieved the accuracy of 82.3% with a sensitivity of 76.9% ($190/247$) and a specificity of 87.7% ($871/993$) (Fig. 3), which was marginally reduced compared to the diagnostic ability of confocal Raman spectroscopy. This indicates that confocal Raman spectroscopy can be used as a standalone diagnostic modality for identifying the dysplastic cervix in clinical colposcopy. On the other hand, to better understand the ability of confocal Raman spectroscopy for improving cervical precancer diagnosis, we have compared the tissue NIR AF/Raman spectra acquired from a two-layer tissue model²⁴ using both the ball-lens confocal Raman probe and a volume Raman probe under the 785-nm excitation light. The result²⁴ shows that the volume Raman probe measures $\sim 74\%$ NIR AF/Raman signals emanating from deeper tissue layer. In contrast, the ball-lens confocal Raman probe detects $\sim 80\%$ of NIR AF/Raman signals originating from the superficial layer of the two-layer tissue model, confirming that confocal Raman spectroscopy technique is highly favorable for early detection of epithelial precancer in vivo. Unlike our previous gastric Raman study that used a volume Raman probe for improving gastric cancer diagnosis,⁴ the combined NIR AF and Raman spectroscopy using confocal probe in this study does not much improve the in vivo diagnosis of cervical precancer (Figs. 3 and 4). The diagnostic differences could be due to the following reasons: (1) in gastric Raman study,⁴ we applied a volume Raman probe to investigate gastric cancer tissue whereby the proliferating cancer cells invaded the underlying basement membrane and stromal layer. The reduction in stromal collagen and AF reabsorption due to excessive angiogenesis in cancer tissue can result in a decrease of NIR AF associated with gastric cancer. Thus the volume Raman probe, particularly in favor of probing the deeper tissue changes, can be used to improve the detection of AF changes of deeper layer tissue (e.g., collagen in stromal tissue, vascular information) associated with gastric cancer. (2) In the current study, we targeted at detecting cervical dysplasia which were largely confined to the epithelium (i.e., within the basement membrane) in the cervix. A confocal Raman probe is specially designed in favor of probing the biochemical changes of superficial epithelial layer (rather than the deeper tissue layer). However, the change of AF spectra of dysplastic tissue is mostly occurring in the deeper connective tissue adjacent to epithelium,^29,34 which results in an inefficiency when using confocal Raman probe for probing the AF changes of deeper cervical tissue associated with precancer transformation. One notes that the balanced accuracy $[(\text{sensitivity}+\text{specificity})/2]$ is computed in this study due to the unbalanced dataset (a large number of true negatives).³⁵ The ROC curves further confirm the best diagnostic performance of confocal Raman spectroscopy (AUC, 0.88) (Fig. 4) compared to NIR AF (AUC, 0.56) or composite NIR AF/Raman spectroscopy (AUC, 0.86) for cervical precancer identification. Overall, the results show that confocal Raman spectroscopy in conjunction with PCA-LDA modeling holds a great promise as a diagnostic tool for improving the detection of subtle biomolecular changes in dysplastic lesions leading to early cervical cancer. Currently, further clinical trials on a larger number of cervical patients with different pathological groups (e.g., low-grade/high-grade dysplasia, squamous metaplasia) are in progress at NUH for evaluating the true clinical merits of confocal Raman technique for improving the early diagnosis of cervical precancer and cancer in obstetrics and gynecology clinic.

In summary, this study demonstrates that NIR-excited confocal Raman spectroscopy can be used for improving precancer diagnosis by selectively probing dysplasia-associated molecular changes primarily from epithelial tissue. Hence, confocal Raman spectroscopy technique has the potential to become a powerful diagnostic tool in adjunct to colposcopy for cervical precancer and early cancer detection in vivo during clinical colposcopic examination.