The potential role of Fourier transform infrared spectroscopy and imaging in cancer diagnosis incorporating complex mathematical methods

Infrared Spectroscopy: A New Frontier in Hematological Disease Diagnosis

Hematological diseases, due to their complex nature and diverse manifestations, pose significant diagnostic challenges in healthcare. The pressing need for early and accurate diagnosis has driven the exploration of novel diagnostic techniques. Infrared (IR) spectroscopy, renowned for its noninvasive, rapid, and cost-effective characteristics, has emerged as a promising adjunct in hematological diagnostics. This review delves into the transformative role of IR spectroscopy and highlights its applications in detecting and diagnosing various blood-related ailments. We discuss groundbreaking research findings and real-world applications while providing a balanced view of the potential and limitations of the technique. By integrating advanced technology with clinical needs, we offer insights into how IR spectroscopy may herald a new era of hematological disease diagnosis.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Infrared spectroscopic imaging study of BV-2 microglia altering tumor cell biological activity and cellular fraction

Tumor brain metastasis is a severe threat to patients' neurological function, in which microglia may be involved in the process of tumor cell metastasis among nerve cells. Our study focused on the interaction between microglia and breast and lung cancer cells. Changes in the proliferation and migration ability of cocultured tumor cells were examined; synchrotron radiation-based fourier transform infrared microspectroscopy (SR-FTIR) was used to detect changes in the structures and contents of biomolecules within the tumor cells. The experimental results showed that the proliferation and migration ability of tumor cells increased after coculture, and the structures and contents of biological macromolecules in tumor cells changed. The absorption peak positions of the amide Ⅱ and amide Ⅰ bands observed for the four kinds of tumor cells changed, and the absorption intensities were significantly enhanced, indicating changes in the secondary structures and contents of proteins in tumor cells, which may be the root cause of the change in tumor cell characteristics. Therefore, the metabolites of microglia may be involved in the progression of tumor cells in the nervous system. In this study, we focused on the interaction between microglia and tumor cells by using SR-FTIR and provided a new understanding of the mechanism of brain metastasis.

Research of Recognition Method of Discrete Wavelet Feature Extraction and PNN Classification of Rats FT-IR Pancreatic Cancer Data

Sprague-Dawley (SD) rats' normal and abnormal pancreatic tissues are determined directly by attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy method. In order to diagnose earlier stage of SD rats pancreatic cancer rate with FT-IR, a novel method of extraction of FT-IR feature using discrete wavelet transformation (DWT) analysis and classification with the probability neural network (PNN) was developed. The differences between normal pancreatic and abnormal samples were identified by PNN based on the indices of 4 feature variants. When error goal was 0.01, the total correct rates of pancreatic early carcinoma and advanced carcinoma were 98% and 100%, respectively. It was practical to apply PNN on the basis of ATR-FT-IR to identify abnormal tissues. The research result shows the feasibility of establishing the models with FT-IR-DWT-PNN method to identify normal pancreatic tissues, early carcinoma tissues, and advanced carcinoma tissues.

Spectral signatures of colonic malignancies in the mid-infrared region: from basic research to clinical applicability

The process of carcinogenesis in the colon progresses through several overlapping stages, making the evaluation process challenging, as well as subjective. Owing to the complexity of colonic tissues and the search for a technique that is rapid and foolproof for precise grading and evaluation of biopsies, many spectroscopic techniques have been evaluated in the past few decades for their efficiency and clinical compatibility. Fourier-transform infrared spectroscopy, being quantitative and objective, has the capacity for automation and relevance to cancer diagnosis. This article highlights investigations on the application of Fourier-transform infrared spectroscopy (particularly microscopy) in colon cancer diagnosis and parallel developments in data analysis techniques for the characterization of spectral signatures of malignant tissues in the colon.

In-vivo optical detection of cancer using chlorin e6--polyvinylpyrrolidone induced fluorescence imaging and spectroscopy

Background

Photosensitizer based fluorescence imaging and spectroscopy is fast becoming a promising approach for cancer detection. The purpose of this study was to examine the use of the photosensitizer chlorin e6 (Ce6) formulated in polyvinylpyrrolidone (PVP) as a potential exogenous fluorophore for fluorescence imaging and spectroscopic detection of human cancer tissue xenografted in preclinical models as well as in a patient.

Methods

Fluorescence imaging was performed on MGH human bladder tumor xenografted on both the chick chorioallantoic membrane (CAM) and the murine model using a fluorescence endoscopy imaging system. In addition, fiber optic based fluorescence spectroscopy was performed on tumors and various normal organs in the same mice to validate the macroscopic images. In one patient, fluorescence imaging was performed on angiosarcoma lesions and normal skin in conjunction with fluorescence spectroscopy to validate Ce6-PVP induced fluorescence visual assessment of the lesions.

Results

Margins of tumor xenografts in the CAM model were clearly outlined under fluorescence imaging. Ce6-PVP-induced fluorescence imaging yielded a specificity of 83% on the CAM model. In mice, fluorescence intensity of Ce6-PVP was higher in bladder tumor compared to adjacent muscle and normal bladder. Clinical results confirmed that fluorescence imaging clearly captured the fluorescence of Ce6-PVP in angiosarcoma lesions and good correlation was found between fluorescence imaging and spectral measurement in the patient.

Conclusion

Combination of Ce6-PVP induced fluorescence imaging and spectroscopy could allow for optical detection and discrimination between cancer and the surrounding normal tissues. Ce6-PVP seems to be a promising fluorophore for fluorescence diagnosis of cancer.

Infrared micro-spectral imaging: distinction of tissue types in axillary lymph node histology

Background

Histopathologic evaluation of surgical specimens is a well established technique for disease identification, and has remained relatively unchanged since its clinical introduction. Although it is essential for clinical investigation, histopathologic identification of tissues remains a time consuming and subjective technique, with unsatisfactory levels of inter- and intra-observer discrepancy. A novel approach for histological recognition is to use Fourier Transform Infrared (FT-IR) micro-spectroscopy. This non-destructive optical technique can provide a rapid measurement of sample biochemistry and identify variations that occur between healthy and diseased tissues. The advantage of this method is that it is objective and provides reproducible diagnosis, independent of fatigue, experience and inter-observer variability.

Methods

We report a method for analysing excised lymph nodes that is based on spectral pathology. In spectral pathology, an unstained (fixed or snap frozen) tissue section is interrogated by a beam of infrared light that samples pixels of 25 μm × 25 μm in size. This beam is rastered over the sample, and up to 100,000 complete infrared spectra are acquired for a given tissue sample. These spectra are subsequently analysed by a diagnostic computer algorithm that is trained by correlating spectral and histopathological features.

Results

We illustrate the ability of infrared micro-spectral imaging, coupled with completely unsupervised methods of multivariate statistical analysis, to accurately reproduce the histological architecture of axillary lymph nodes. By correlating spectral and histopathological features, a diagnostic algorithm was trained that allowed both accurate and rapid classification of benign and malignant tissues composed within different lymph nodes. This approach was successfully applied to both deparaffinised and frozen tissues and indicates that both intra-operative and more conventional surgical specimens can be diagnosed by this technique.

Conclusion

This paper provides strong evidence that automated diagnosis by means of infrared micro-spectral imaging is possible. Recent investigations within the author's laboratory upon lymph nodes have also revealed that cancers from different primary tumours provide distinctly different spectral signatures. Thus poorly differentiated and hard-to-determine cases of metastatic invasion, such as micrometastases, may additionally be identified by this technique. Finally, we differentiate benign and malignant tissues composed within axillary lymph nodes by completely automated methods of spectral analysis.

Fourier transform infrared spectroscopy in cancer detection

The rapid developments in the field of infrared spectroscopy in the past decade have demonstrated a potential for disease diagnosis using noninvasive technologies. Several earlier studies have highlighted the advantage of using infrared spectroscopy both in the near- and mid-infrared regions for diagnostic purposes at clinical levels. The areas of focus have been the distinction of premalignant and malignant cells and tissues from their normal state using specific parameters obtained from Fourier transform infrared spectra, making it a rapid and reagent-free method. While it still requires pilot studies and designed clinical trials to ensure the applicability of such systems for cancer diagnosis, substantial progress has been made in incorporating advances in computational methods into the system to increase the sensitivity of the entire setup, making it an objective and sensitive technique suitable for automation to suit the demands of the medical community. The development of fiber-optics systems for infrared spectroscopy have further opened up new and modern avenues in medical diagnosis at various levels of cells, tissues and organs under laboratory and clinical conditions.

Identification of primary tumors of brain metastases by SIMCA classification of IR spectroscopic images

Brain metastases are secondary intracranial lesions which occur more frequently than primary brain tumors. The four most abundant types of brain metastasis originate from primary tumors of lung cancer, colorectal cancer, breast cancer and renal cell carcinoma. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy based methods constitute a new approach to determine the origin of brain metastases. IR spectroscopic images of 4 by 4 mm2 tissue areas were recorded in transmission mode by a FTIR imaging spectrometer coupled to a focal plane array detector. Unsupervised cluster analysis revealed variances within each cryosection. Selected clusters of five IR images with known diagnoses trained a supervised classification model based on the algorithm soft independent modeling of class analogies (SIMCA). This model was applied to distinguish normal brain tissue from brain metastases and to identify the primary tumor of brain metastases in 15 independent IR images. All specimens were assigned to the correct tissue class. This proof-of-concept study demonstrates that IR spectroscopy can complement established methods such as histopathology or immunohistochemistry for diagnosis.