At Laser Biomedical Applications & Instrumentation Division, RRCAT, several studies have been carried out towards development and evaluation of laser induced fluorescence (LIF) spectroscopy for the diagnosis of cancer. In the initial phase of this work [1], studies were carried out on tissues resected at surgery or biopsy from patients with cancer of different organs - uterus [2], breast [3,4] and oral cavity[5,6]. The objectives for these studies were to establish the potential of the approach, find the excitation wavelength(s), which result in significant differences in the fluorescence from normal and diseased tissue and develop algorithms, which can exploit these differences for diagnosis. These studies revealed that nitrogen laser operating at 337nm was a good choice for exciting tissue fluorescence. Algorithms developed to quantify the spectral differences in the nitrogen laser excited fluorescence from malignant, benign tumor and normal tissue sites provided good discrimination with sensitivity and specificity towards cancer of ~ 90% in general and up to 100% in favourable cases. Another important finding of these studies was that while the malignant breast tissue sites (invasive ductal carcinoma) were considerably more fluorescent than the benign tumor (fibroadenoma) and normal tissue sites (uninvolved region of the resected tissue) [3], reverse was the case with tissue from oral cavity[5]. For the latter the malignant sites (squamous cell carcinoma) were considerably less fluorescent than the normal tissue. Various measurements on tissue fluorescence (excitation-emission spectroscopy, synchronous scan and time resolved measurements [7]) were carried out to unravel the reasons for the observed difference in the fluorescence from normal and malignant sites. These suggest a significant variation in the concentration of the fluorophores in the different tissue types. In particular, the studies showed that while concentration of NADH (reduced nicotinamide adenine dinucleotide) is higher in malignant breast tissues compared to benign tumor and normal breast tissues [4] the reverse is true for tissues from oral cavity where NADH concentration is higher in normal oral tissues [6]. These results have been confirmed by enzymatic measurements of NADH concentration in malignant and normal tissues from breast and oral cavity [8]. The differences in fluorophore concentration inferred from spectroscopic studies not only account qualitatively for the observed spectral differences in the autofluorescence spectra of the normal and diseased oral and breast tissues but also explain why nitrogen laser is a good excitation source.

Since the measured fluorescence spectra is strongly modulated by absorption and scattering in the tissue a quantitative evaluation of the concentration of fluorophores from the measured fluorescence spectra requires measurement of tissue optical parameters and modeling of light transport in tissue. Work in this direction is also being carried out at RRCAT. Our measurements on breast tissue showed that the absorption and scattering coefficients are larger in malignant sites as compared to normal [9]. The larger scattering coefficient of malignant sites has an interesting consequence. Whereas for thin tissue sections (thickness < optical transport length) the depolarization of fluorescence was observed to be smaller in malignant tissues compared to normal the reverse was observed for thicker tissue section. The latter effect has been shown by us to arise due to larger scattering in malignant tissue [10]. Studies carried out at LBAID have also revealed that the signatures of blood absorption on tissue fluorescence spectra are significantly reduced in polarized fluorescence compared to that in unpolarized fluorescence spectra [11]. The reduced effect of blood absorption on polarized fluorescence also leads to a reduced site-to-site variability in polarized fluorescence intensity and line shape compared to unpolarized fluorescence. This therefore suggests that use of polarized fluorescence instead of conventional unpolarized fluorescence may be more useful for improving discrimination between malignant and normal sites.

Fig. 1. The prototype system for LIF diagnosis of cancer

The prototype system developed at RRCAT for evaluation of the LIF technique for in-vivo diagnosis of cancer is shown in Fig. 1. The system comprises of a sealed-off N2 laser (7ns, 10mJ, 10Hz), an optical fiber probe, and a gateable intensified CCD (ICCD) detector. The diagnostic probe is a bifurcated fiber bundle with a central fiber surrounded by an array of six fibers. The central fiber delivers excitation light to the tissue surface and the six collection fibers collect tissue fluorescence from the surface area directly illuminated by the excitation light. An additional fiber has been put in the diagnostic probe to monitor the energy of each nitrogen laser output pulse by monitoring luminescence of a phosphor coated on the tip of this fiber. The light coming from the distal ends of the six collection fibers and the reference fiber is imaged on the entrance slit of a spectrograph coupled to the ICCD. One such unit has been installed at the Government cancer hospital, Indore for a detailed clinical evaluation of the technique after satisfactory results were obtained in a pilot study on 25 patients with histopathologically confirmed squamous cell carcinoma of oral cavity [12]. The unit has been used to record in-vivo autofluorescence spectra from healthy volunteers and more than 50 patients enrolled at out patient department of the Hospital for screening / evaluation of neoplasm of oral cavity. In order to develop algorithms that can efficiently discriminate between the spectral features of the malignant and nonmalignant tissue sites we have used the spectral data from oral cavity of healthy volunteers to correspond to normal (nonmalignant) and that recorded from oral cavity sites of patients that were reported as having squamous cell carcinoma Grade I on the basis of the histopathology of biopsy taken from the site subsequent to acquisition of spectra as abnormal (malignant). Both linear as well as nonlinear statistical techniques have been investigated to explore their discrimination efficacy. The nonlinear diagnostic algorithm developed by us based on nonlinear Maximum Representation and Discrimination Feature (MRDF) provided significantly improved diagnostic performance as compared to the linear principal component analysis based algorithm in discriminating the cancerous tissue sites of the oral cancer patients from the healthy squamous tissue sites of normal volunteers as well as the uninvolved tissue sites of the oral cavity of the patients with cancer [13]. The MRDF based algorithm provided a sensitivity of 93% and a specificity of 96% towards cancer for the training set data and a sensitivity of 93% and a specificity of 96% towards cancer for the validation set data. On the other hand, the linear PCA based algorithm provided a sensitivity of 83% and a specificity of 66% towards cancer for the training set data and a sensitivity of 80% and a specificity of 58% towards cancer for the validation set data.

1. An overview of the work is provided in P.K. Gupta, and D.D. Bhawalkar, Current Science, 1999, 77, 925-933.
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3. P.K. Gupta, S.K. Majumder, and A. Uppal, Lasers Surg. Med., 1997, 21, 417-422.
4. S.K. Majumder, P.K. Gupta, B. Jain, and A. Uppal, Lasers Life Sci, 1999, 8, 249-264.
5. S.K. Majumder, P.K. Gupta, and A. Uppal, Lasers Life Sci, 1999, 8, 211-227.
6. S.K. Majumder, and P.K. Gupta, Lasers Life Sci., 2000, 9, 143-152.
7. B. Jain, S.K. Majumder, P.K. Gupta, Lasers Life Sci., 1998, 8, 163-173.
8. A. Uppal and P.K. Gupta, Biotechnology and Applied Biochemistry, 2003, 37, 45-50.
9. N. Ghosh, S.K. Mohanty, S.K. Majumder, and P.K. Gupta, Appl. Opt. 2001, 40, 176-184.
10. S.K. Mohanty, N. Ghosh, S.K. Majumder, and P.K. Gupta, Appl. Opt. 2001, 40, 1147-1154.
11. N. Ghosh, S.K. Majumder, and P.K. Gupta, Opt. Lett. 2002, 27, 2007-2009.
12. S.K. Majumder, S.K. Mohanty, N. Ghosh, P.K. Gupta, D.K. Jain, and F. Khan, Current Science, 2000, 79, 1089-1094.
13. S.K. Majumder N. Ghosh, and P.K. Gupta, Lasers Surg. Med., 2003, 33, 48-56.