We demonstrate the capability of linear and non-linear optical microspectroscopy techniques such as fluorescence lifetime imaging (FLIM), Raman spectroscopy (RS), second-harmonic generation (SHG), and two-photon fluorescence (TPF), to monitor structural, biochemical and biomechanical alterations in collagenous tissues upon both collagen digestion and cross-linking using genipin as cross-linker. Thanks to a unique combination of optical and force microscopy techniques in a correlative manner, we obtained detailed information about the biochemical, structural, and biomechanical properties of collagenous tissues upon both digestion and cross-linking treatment.
We demonstrate the capability of a time-resolved autofluorescence lifetime imaging setup for discriminating, perilesional and tumor tissues in freshly excised liver samples. In particular, freshly excised liver biopsies were collected from the surgery room and imaged within 30 minutes using 445 nm as excitation wavelength and one spectral window for detection. Differences in mean fluorescence lifetime were observed among the examined tissue types, potentially allowing their discrimination and classification. Interestingly, the obtained autofluorescence lifetime values were significantly different when comparing primary tumors of liver with colorectal tumor metastasis to the liver, underlying the classification capability of this experimental setup. The presented approach offers real-time acquisition and processing, optical flexibility, as well as the possibility to acquire autofluorescence data under bright background conditions. Hence, it meets all the requirements for label-free diagnostics and surgical guidance in various clinical and histopathological applications.
Significance: Glioblastoma (GBM) is the most common and aggressive malignant brain tumor in adults. With a worldwide incidence rate of 2 to 3 per 100,000 people, it accounts for more than 60% of all brain cancers; currently, its 5-year survival rate is <5 % . GBM treatment relies mainly on surgical resection. In this framework, multimodal optical spectroscopy could provide a fast and label-free tool for improving tumor detection and guiding the removal of diseased tissues.
Aim: Discriminating healthy brain from GBM tissues in an animal model through the combination of Raman and reflectance spectroscopies.
Approach: EGFP-GL261 cells were injected into the brains of eight laboratory mice for inducing murine GBM in these animals. A multimodal optical fiber probe combining fluorescence, Raman, and reflectance spectroscopy was used to localize in vivo healthy and tumor brain areas and to collect their spectral information.
Results: Tumor areas were localized through the detection of EGFP fluorescence emission. Then, Raman and reflectance spectra were collected from healthy and tumor tissues, and later analyzed through principal component analysis and linear discriminant analysis in order to develop a classification algorithm. Raman and reflectance spectra resulted in 92% and 93% classification accuracy, respectively. Combining together these techniques allowed improving the discrimination between healthy and tumor tissues up to 97%.
Conclusions: These preliminary results demonstrate the potential of multimodal fiber-probe spectroscopy for in vivo label-free detection and delineation of brain tumors, and thus represent an additional, encouraging step toward clinical translation and deployment of fiber-probe spectroscopy.
Urothelial carcinoma (UC) is the most common type of bladder cancer, and its treatment depends from both tumour invasiveness (stage) and aggressiveness (grade). The gold standard for detecting UC is white-light cystoscopy, followed by tissue biopsy and histopathological examination; however, such process is invasive, time-consuming, operatordependent and prone to sampling errors. In this framework, optical spectroscopy techniques could be a promising solution for fast and label-free diagnosis of bladder tissues and for early detection of UC. Thus, we combined autofluorescence, diffuse reflectance and Raman spectroscopy in a compact and transportable setup based on an optical fibrebundle probe. This experimental setup was used for studying fresh biopsies of urothelial tumour (140 samples) and healthy bladder (50 samples) collected from 90 patients undergoing Transurethral Resection of Bladder Tumours (TURBT). The aim of this study was to develop an automated classification of the examined tissues based on the intrinsic spectral information provided by all three techniques. We found that healthy and diseased tissues showed significant spectral differences for each technique, resulting in high accuracy (up to 90%) from a Linear Discriminant Analysis (LDA) routine. In particular, fluorescence spectroscopy – excited either with blue or UV light – provided very good results in detecting UC. However, tumour grading and staging proved to be more challenging tasks, for which no single spectroscopic technique could provide sufficient sensitivity and specificity. Therefore, we found that a multimodal approach can improve significantly the diagnosis of UC stages and grades.
Surgery is the usual treatment for removing malformations and tumours in brain; however, the lack of contrast between diseased tissues and normal brain is a major problem. Magnetic Resonance Imaging (MRI) can be used to detect them, but brain shifts may severely reduce the accuracy of surgical removal procedures. In this framework, optical spectroscopy – being a fast and label-free method for analysing tissue composition – has the potential for improving detection and diagnosis of diseased areas. In this study, we used a quadrifurcated optical fibre-probe system combining multiple spectroscopic techniques for analysing ex vivo human brain freshly excised biopsies taken from both tumour and dysplastic tissues. All spectral recordings were done immediately after surgical resection, requiring less than 2 minutes for each sample. The recorded data were analysed using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for obtaining an automated classification of the examined samples based on the intrinsic spectral information provided by all three techniques. Significant differences were observed between dysplastic and tumour spectra, resulting in high sensitivity (83%) and specificity (73%). In particular, diffuse reflectance and UVexcited fluorescence spectroscopies provided the highest accuracies in discriminating different tissue types (78% and 75%, respectively) in good agreement with the corresponding histopathological examination; moreover, their combination with Raman spectroscopy resulted in a further improve of the classification capability up to 85%. The presented method demonstrates the huge potential of multimodal spectroscopy for the examination of brain tissues and opens the way for possible applications in surgical environment.
KEYWORDS: Tissues, Raman spectroscopy, Spectroscopy, In vivo imaging, Diffuse reflectance spectroscopy, Fluorescence spectroscopy, Brain, Principal component analysis, Surgery
Glioblastoma (GBM) is the most common and aggressive malignant brain tumour in adults, and the survival rate of patients affected by this disease is strongly dependent on the successful resection of the tumour. In this framework, multimodal optical spectroscopy could provide a fast and label-free tool for improving tumour detection and guiding the surgical removal of diseased tissues. In this study, we used an optical fibre-probe system combining multiple spectroscopic techniques for in vivo examination of normal and GBM tissues in mouse brain. Spectroscopic measurements based on fluorescence, Raman, and diffuse reflectance spectroscopy were performed on anesthetized animals through two optical windows implanted on the head of each mouse. Then, the recorded data were analysed using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for obtaining an automated classification of the examined tissues based on the intrinsic spectral information provided by Raman and reflectance spectroscopy. These techniques provided 77% and 97% classification accuracy, respectively, by taking advantage of the intrinsic molecular content of the examined tissues. In particular, the high sensitivity and specificity achieved by means of reflectance spectroscopy indicate that such technique is the most suited for in vivo detection of GBM. The presented results demonstrate the potential of our method for improving the diagnosis of suspicious brain areas during surgery through a very fast spectroscopic inspection, thus helping the surgeon in removing all tumour tissues and reducing the probability of GBM recurrence.
Urothelial carcinoma (UC) is the most common type of bladder cancer, and its treatment depends from both tumour invasiveness (stage) and aggressiveness (grade). The gold standard for detecting UC is white-light cystoscopy, followed by tissue biopsy and histopathological examination; however, such process is invasive, time-consuming, operatordependent and prone to sampling errors. In this framework, optical spectroscopy techniques can provide a fast, label-free and non-invasive tool for improving diagnosis. Thus, we combined auto-fluorescence, diffuse reflectance and Raman spectroscopy in a compact and transportable setup based on an optical fibre-bundle probe. This experimental setup was used for studying fresh biopsies of urothelial tumour (129 samples) and healthy bladder (40 samples) collected from 78 patients undergoing Transurethral Resection of Bladder Tumours (TURBT). The recorded data were analysed using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for obtaining an automated classification of the examined samples based on the intrinsic spectral information provided by all three techniques. We found that healthy and diseased tissues showed significant spectral differences for each technique, resulting in high accuracy (up to 90%) from PCA-LDA routines. While fluorescence spectroscopy seems sensitive enough for detecting UC, we found that a multimodal approach is crucial for obtaining high discriminating capability (<80%) in grading and staging tumour biopsies. In conclusion, the presented strategy generates results similar to gold standard histology, but in a fast and labelfree way, offering the potential for endoscopic in vivo applications.
The most common type of bladder cancer is urothelial carcinoma (UC), whose treatment depends from both tumour extension (stage) and aggressiveness (grade). The gold standard for detecting UC is white-light cystoscopy, followed by tissue biopsy and pathological examination for determining tumour stage and grade. However, such process is invasive, time-consuming and prone to sampling errors. In this framework, optical spectroscopy techniques provide fast, label-free and non-invasive alternatives to standard histopathology. Thus, we combined auto-fluorescence, diffuse reflectance and Raman spectroscopy in a compact and transportable setup based on an optical fibre-probe. The latter was coupled to three laser diodes (emitting at 378 nm, 445 nm and 785 nm) and to a halogen lamp for exciting and collecting autofluorescence, Raman and reflectance spectra, respectively. This experimental setup was used for studying fresh biopsies of urothelial tumour (103 samples) and healthy bladder (34 samples) collected from 63 patients undergoing Transurethral Resection of Bladder Tumours (TURBT). All spectral recordings were done within 30 minutes from surgical resection, and optical inspection required less than 2 minutes for each sample. The recorded data were analysed using Principal Component Analysis (PCA) for obtaining an automated classification of the examined samples based on the intrinsic spectral information provided by all three techniques. We found that multimodal spectroscopy provides high-sensitivity, high-specificity discriminating capability for UC detection, grading and staging. The presented strategy generates results similar to gold standard histology, but in a fast and label-free way, offering the potential for endoscopic in vivo applications.
Glioblastoma (GBM) is the most common and aggressive malignant brain tumour in adults. Patient survival rates are strongly dependent on the successfully resection of the tumour. In this framework, multimodal optical spectroscopy could provide a fast and label-free tool for improving tumour detection and guiding the removal of diseased tissue. In this study, we used an optical fibre-probe system combining multiple spectroscopic techniques for in vivo examination of normal and GBM tissues in mouse brain. Specifically, the probe – based on a fibre-bundle with optical fibres of various size and properties – allowed performing spectroscopic measurements based on fluorescence, Raman, and diffuse reflectance spectroscopy though two optical windows implanted on the head of each animal. Two visible laser diodes were used for fluorescence spectroscopy, a laser diode emitting in the NIR was used for Raman spectroscopy, and a fibre-coupled halogen lamp for diffuse reflectance. All spectral recordings were done when the animals were anesthetized; optical inspection required less than 4 minutes for each animal. The recorded data were analysed using Principal Component Analysis (PCA) for obtaining an automated classification of the examined tissues based on the intrinsic spectral information provided by Raman and reflectance spectroscopy. The presented method demonstrated high sensitivity and specificity in discriminating GBM from normal brain. Furthermore, we found that the multimodal approach is crucial for improving diagnostic capabilities beyond what can be achieved from individual techniques.
Optical spectroscopy is a fast, label-free and non-invasive method for analysing tissue composition and, thus, has the potential for improving standard diagnostic capabilities. This is particularly relevant for brain surgery due to the lack of contrast between diseased tissues (e.g. malformations and tumours) and the surrounding brain. In this study, we used an optical fibre-probe system combining multiple spectroscopic techniques for analysing ex vivo human brain biopsies taken from both tumour and dysplastic tissues. Specifically, the probe – based on a fibre-bundle with optical fibres of various size and properties – allowed performing spectroscopic measurements based on fluorescence, Raman, and diffuse reflectance spectroscopy. Two visible laser diodes were used for fluorescence spectroscopy, a laser diode emitting in the NIR was used for Raman spectroscopy, and a fibre-coupled halogen lamp for diffuse reflectance. All spectral recordings were done within 30 minutes from surgical resection, and optical inspection required less than 2 minutes for each sample. The recorded data were analysed using Principal Component Analysis (PCA) for obtaining an automated classification of the examined samples based on the intrinsic spectral information provided by all three techniques. The presented method demonstrated high sensitivity and specificity in discriminating different tissue types in good agreement with histopathological examination. Furthermore, we found that the multimodal approach is crucial for improving diagnostic capabilities beyond what can be achieved from individual techniques.
Urothelial carcinoma (UC) is the most common type of bladder cancer. Its treatment depends from both tumour extension (stage) and aggressiveness (grade). The gold standard for detecting UC is white-light cystoscopy, followed by tissue biopsy and pathological examination for determining tumour stage and grade. However, such process is invasive, time-consuming and prone to sampling errors. In this framework, optical spectroscopy techniques provide fast, label-free and non-invasive alternatives to standard histopathology. Thus, we combined auto-fluorescence, diffuse reflectance and Raman spectroscopies in a compact and transportable setup based on an optical fibre-probe. The latter was coupled to three laser diodes (emitting at 378 nm, 445 nm and 785 nm) and to a halogen lamp for exciting and collecting autofluorescence, Raman and reflectance spectra, respectively. This experimental setup was used for studying fresh biopsies of urothelial tumour (82 samples) and healthy bladder (32 samples) collected from 49 patients undergoing Transurethral Resection of Bladder Tumours (TURBT). All spectral recordings were done within 30 minutes from surgical resection, and optical inspection required less than 2 minutes for each sample. The recorded data were analysed using Principal Component Analysis (PCA) for obtaining an automated classification of the examined samples based on the intrinsic spectral information provided by all three techniques. We found that multimodal spectroscopy provides high-sensitivity, high-specificity discriminating capability for UC detection, grading and staging. The presented strategy generates results similar to gold standard histology, but in a fast and label-free way, offering the potential for endoscopic in vivo applications.
Urothelial carcinoma (UC) is the most common type of bladder cancer. The gold standard for detecting UC is white-light cystoscopy, which is followed by tissue biopsy and pathological examination. However, such process is invasive, timeconsuming and prone to sampling errors. In this framework, optical spectroscopy techniques provide fast, label-free and non-invasive alternatives to standard histopathology. Thus, the aim of this study is to discriminate normal bladder tissues from urothelial tumours, and to identify the different stages of the disease, by means of combined auto-fluorescence, diffuse reflectance and Raman spectroscopy. In fact, these techniques were implemented in a compact and transportable setup based on two optical fibre probes: one coupled to fluorescence and reflectance excitation sources, while the other one to the 785 nm laser. Raman, fluorescence and reflected light signals were collected though the same probe used for excitation and sent to a spectrograph. We used this experimental setup for studying fresh biopsies of urothelial tumour and healthy bladder collected from 32 patients undergoing Transurethral Resection of Bladder Tumours (TURBT). Scoring methods based on ratiometric approach and Principal Component Analysis (PCA) allowed not only to discriminate healthy biopsies from tumour ones, but also to recognize three tumour stages.
We combined Second Harmonic Generation and Two-Photon Fluorescence for imaging ex
vivo tissue sections of human bladder affected by urothelial carcinoma. We studied different grades of
the tumor, and compared them to healthy bladder mucosa.
We combined Second Harmonic Generation, Two-Photon Fluorescence and Fluorescence
Lifetime Imaging Microscopy for studying human carotid ex vivo tissue sections affected by
atherosclerosis, resulting in the discrimination of different arterial regions within the plaques.
Atherosclerosis is a widespread cardiovascular disease caused by the deposition of lipids (such as cholesterol and triglycerides) on the inner arterial wall. The rupture of an atherosclerotic plaque, resulting in a thrombus, is one of the leading causes of death in the Western World. Preventive assessment of plaque vulnerability is therefore extremely important and can be performed by studying collagen organization and lipid composition in atherosclerotic arterial tissues. Routinely used diagnostic methods, such as histopathological examination, are limited to morphological analysis of the examined tissues, whereas an exhaustive characterization requires immune-histochemical examination and a morpho-functional approach. Instead, a label-free and non-invasive alternative is provided by nonlinear microscopy. In this study, we combined SHG and FLIM microscopy in order to characterize collagen organization and lipids in human carotid ex vivo tissues affected by atherosclerosis. SHG and TPF images, acquired from different regions within atherosclerotic plaques, were processed through image pattern analysis methods (FFT, GLCM). The resulting information on collagen and cholesterol distribution and anisotropy, combined with collagen and lipids fluorescence lifetime measured from FLIM images, allowed characterization of carotid samples and discrimination of different tissue regions. The presented method can be applied for automated classification of atherosclerotic lesions and plaque vulnerability. Moreover, it lays the foundation for a potential in vivo diagnostic tool to be used in clinical setting.
Detection of pre-malignant lesions in skin could help in reducing the 5 year patient mortality rates and greatly advancing the quality of life. Current gold standard for the detection of skin pathologies is a tissue biopsy and followed by a series of steps before it is examined under a light microscope by a pathologist. The disadvantage with this method is its invasiveness. Light based biomedical point spectroscopic techniques offers an adjunct technique to invasive tissue pathology. In this context, we have implemented a simple multiplexed ratiometric approach (F470/F560 and F510/F580) based on fluorescence at two excitation wavelengths 378 nm and 445 nm respectively. The emission profile at these excitation wavelengths showed a shift towards the longer wavelengths for melanoma when compared with normal and nevus. At both excitation wavelengths, we observed an increased intensity ratios for normal, followed by nevus and melanoma. This intensity ratios provide a good diagnostic capability in differentiating normal, nevus and melanocytic skin lesions. This method could be applied in vivo because of the simplicity involved in discriminating normal and pathological skin tissues.
Atherosclerosis is among the most widespread cardiovascular diseases and one of the leading cause of death in the Western World. Characterization of arterial tissue in atherosclerotic condition is extremely interesting from the diagnostic point of view, especially for what is concerning collagen content and organization because collagen plays a crucial role in plaque vulnerability. Routinely used diagnostic methods, such as histopathological examination, are limited to morphological analysis of the examined tissues, whereas an exhaustive characterization requires immunehistochemical examination and a morpho-functional approach. Non-linear microscopy techniques offer the potential for providing morpho-functional information on the examined tissues in a label-free way. In this study, we employed combined SHG and FLIM microscopy for characterizing collagen organization in both normal arterial wall and within atherosclerotic plaques. Image pattern analysis of SHG images allowed characterizing collagen organization in different tissue regions. In addition, the analysis of collagen fluorescence decay contributed to the characterization of the samples based on collagen fluorescence lifetime. Different values of collagen fiber mean size, collagen distribution, and collagen anisotropy and collagen fluorescence lifetime were found in normal arterial wall and within plaque depositions, prospectively allowing for automated classification of atherosclerotic lesions and plaque vulnerability. The presented method represents a promising diagnostic tool for evaluating atherosclerotic tissue and has the potential to find a stable place in clinical setting as well as to be applied in vivo in the near future.
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