Towards a Portable Platform Integrated With Multispectral Noncontact Probes for Delineating Normal and Breast Cancer Tissue Based on Near-Infrared Spectroscopy

Plasma-based near-infrared spectroscopy for early diagnosis of lung cancer

Lung cancer (LC) continues to be a leading death cause in China, primarily due to late diagnosis. This study aimed to evaluate the effectiveness of using plasma-based near-infrared spectroscopy (NIRS) for LC early diagnosis. A total of 171 plasma samples were collected, including 73 healthy controls (HC), 73 LC, and 25 benign lung tumors (B). NIRS was utilized to measure the spectra of samples. Pre-processing methods, including centering and scaling, standard normal variate, multiplicative scatter correction, Savitzky-Golay smoothing, Savitzky-Golay first derivative, and baseline correction were applied. Subsequently, 4 machine learning (ML) algorithms, including partial least squares (PLS), support vector machines (SVM), gradient boosting machine, and random forest, were utilized to develop diagnostic models using train set data. Then, the predictive performance of each model was evaluated using test set samples. The study was conducted in 5 comparisons as follows: LC and HC, LC and B, B and HC, the diseased group (D) and HC, as well as LC, B and HC. Among the 5 comparisons, SVM consistently generated the best performance with a certain pre-processing method, achieving overall accuracy of 1.0 (kappa: 1.0) in the comparisons of LC and HC, B and HC, as well as D and HC. Pre-processing was identified as a crucial step in developing ML models. Interestingly, PLS demonstrated remarkable stability and relatively high predictive performance across the 5 comparisons, even though it did not achieve the top results like SVM. However, none of these algorithms were able to effectively distinguish B from LC. These findings indicate that the combination of plasma-based NIRS with ML algorithms is a rapid, non-invasive, effective, and economical method for LC early diagnosis.

Label-free assessment of the transformation zone using multispectral diffuse optical imaging toward early detection of cervical cancer

The assessment of the transformation zone is a critical step toward diagnosis of cervical cancer. This work involves the development of a portable, label-free transvaginal multispectral diffuse optical imaging (MDOI) imaging probe to estimate the transformation zone. The images were acquired from N = 5 (N = 1 normal, N = 2 premalignant, and N = 2 malignant) patients. Key parameters such as spectral contrast ratio (ρ) at 545 and 450 nm were higher in premalignant (0.29, 0.25 for 450 nm and 0.30, 0.17 for 545 nm) as compared to the normal patients (0.13 and 0.14 for 450 and 545 nm, respectively). The threshold for the spectral intensity ratio R610/R450 and R610/R545 can also be used as a marker to correlate with the new and original squamous columnar junction (SCJ), respectively. The pilot study highlights the use of new markers such as spectral contrast ratio (ρ) and spectral intensity ratio (R610/R450 and R610/R545) images.

Infrared Spectroscopy in Gynecological Oncology: A Comprehensive Review of Diagnostic Potentials and Challenges

The early detection of gynecological cancers, which is critical for improving patient survival rates, is challenging because of the vague early symptoms and the diagnostic limitations of current approaches. This comprehensive review delves into the game-changing potential of infrared (IR) spectroscopy, a noninvasive technology used to transform the landscape of cancer diagnosis in gynecology. By collecting the distinctive vibrational frequencies of chemical bonds inside tissue samples, Fourier-transform infrared (FTIR) spectroscopy provides a 'molecular fingerprint' that outperforms existing diagnostic approaches. We highlight significant advances in this field, particularly the identification of discrete biomarker bands in the mid- and near-IR spectra. Proteins, lipids, carbohydrates, and nucleic acids exhibited different absorption patterns. These spectral signatures not only serve to distinguish between malignant and benign diseases, but also provide additional information regarding the cellular changes associated with cancer. To underscore the practical consequences of these findings, we examined studies in which IR spectroscopy demonstrated exceptional diagnostic accuracy. This review supports the use of IR spectroscopy in normal clinical practice, emphasizing its capacity to detect and comprehend the intricate molecular underpinnings of gynecological cancers.

Near-infrared spectroscopy for structural bone assessment

Aims

Disorders of bone integrity carry a high global disease burden, frequently requiring intervention, but there is a paucity of methods capable of noninvasive real-time assessment. Here we show that miniaturized handheld near-infrared spectroscopy (NIRS) scans, operated via a smartphone, can assess structural human bone properties in under three seconds.

Methods

A hand-held NIR spectrometer was used to scan bone samples from 20 patients and predict: bone volume fraction (BV/TV); and trabecular (Tb) and cortical (Ct) thickness (Th), porosity (Po), and spacing (Sp).

Results

NIRS scans on both the inner (trabecular) surface or outer (cortical) surface accurately identified variations in bone collagen, water, mineral, and fat content, which then accurately predicted bone volume fraction (BV/TV, inner R² = 0.91, outer R² = 0.83), thickness (Tb.Th, inner R² = 0.9, outer R² = 0.79), and cortical thickness (Ct.Th, inner and outer both R² = 0.90). NIRS scans also had 100% classification accuracy in grading the quartile of bone thickness and quality.

Conclusion

We believe this is a fundamental step forward in creating an instrument capable of intraoperative real-time use.

Cite this article: Bone Jt Open 2023;4(4):250–261.

Toward the development of portable light emitting diode-based polarization spectroscopy tools for breast cancer diagnosis

A robust, affordable and portable light emitting diode-based diagnostic tools (POLS-NIRDx) using a polarization-sensitive (linear as well as circular polarization) technique were designed and developed to quantify the degree of linear polarization (DOLP), degree of circular polarization (DOCP). The study was performed on malignant (invasive ductal carcinoma) and adjacent normal ex-vivo biopsy tissues excised from N = 10 patients at the operating wavelengths of 850 and 940 nm. The average DOLP and DOCP values were lower for malignant than adjacent normal while operating at 850 and 940 nm. The highest accuracy was observed for DOLP (100%) and DOCP (80%) while operating at 850 nm, which reduced (80% for DOLP and 65% for DOCP) at 940 nm. This pilot study can be utilized as a differentiating factor to delineate malignant tissues from adjacent normal tissues.

Thermo-optic measurements and their inter-dependencies for delineating cancerous breast biopsy tissue from adjacent normal

The histopathological diagnosis of cancer is the current gold standard to differentiate normal from cancerous tissues. We propose a portable platform prototype to characterize the tissue's thermal and optical properties, and their inter-dependencies to potentially aid the pathologist in making an informed decision. The measurements were performed on 10 samples from five subjects, where the cancerous and adjacent normal were extracted from the same patient. It was observed that thermal conductivity (k) and reduced-scattering-coefficient (μ'_s ) for both the cancerous and normal tissues reduced with the rise in tissue temperature. Comparing cancerous and adjacent normal tissue, the difference in k and μ'_s (at 940 nm) were statistically significant (p = 7.94e-3), while combining k and μ'_s achieved the highest statistical significance (6.74e-4). These preliminary results promise and support testing on a large number of samples for rapidly differentiating cancerous from adjacent normal tissues.

Hybrid Spectral-IRDx: Near-IR and Ultrasound Attenuation System for Differentiating Breast Cancer From Adjacent Normal Tissue

OBJECTIVE

While performing surgical excision for breast cancer (lumpectomy), it is important to ensure a clear margin of normal tissue around the cancer to achieve complete resection. The current standard is histopathology; however, it is time-consuming and labour-intensive requiring skilled personnel.

METHOD

We describe a Hybrid Spectral-IRDx - a combination of the previously reported Spectral-IRDx tool with multimodal ultrasound and NIR spectroscopy techniques. We show how this portable, cost-effective, minimal-contact tool could provide rapid diagnosis of cancer using formalin-fixed (FF) and deparaffinized (DP) breast biopsy tissues.

RESULTS

Using this new tool, measurements were performed on cancerous/fibroadenoma and its adjacent normal tissues from the same patients (N = 14). The acoustic attenuation coefficient (α) and reduced scattering coefficient (µ'_s) (at 850, 940, and 1060 nm) for the cancerous/fibroadenoma tissues were reported to be higher compared to adjacent normal tissues, a basis of delineation. Comparing FF cancerous and adjacent normal tissue, the difference in µ'_s at 850 nm and 940 nm were statistically significant (p = 3.17e-2 and 7.94e-3 respectively). The difference in α between the cancerous and adjacent normal tissues for DP and FF tissues were also statistically significant (p = 2.85e-2 and 7.94e-3 respectively). Combining multimodal parameters α and µ'_s (at 940 nm) show highest statistical significance (p = 6.72e-4) between FF cancerous/fibroadenoma and adjacent normal tissues.

CONCLUSION

We show that Hybrid Spectral-IRDx can accurately delineate between cancerous and adjacent normal breast biopsy tissue.

SIGNIFICANCE

The results obtained establish the proof-of-principle and large-scale testing of this multimodal breast cancer diagnostic platform for core biopsy diagnosis.

Laser Transmission Spectroscopy Based on Tunable-Gain Dual-Channel Dual-Phase LIA for Biological Nanoparticles Characterization

Size and absolute concentration of suspensions of nanoparticles are important information for the study and development of new materials and products in different industrial applications spanning from biotechnology and pharmaceutics to food preparation and conservation. Laser Transmission Spectroscopy (LTS) is the only methodology able to measure nanoparticle size and concentration by performing a single measurement. In this paper we report on a new variable gain calibration procedure for LTS-based instruments allowing to decrease of an order of magnitude the experimental indetermination of the particle size respect to the conventional LTS based on the double ratio technique. The variable gain calibration procedure makes use of a specifically designed tunable-gain, dual-channel, dual-phase Lock-In Amplifier (LIA) whose input voltage signals are those ones generated by two Si photodiodes that measure the laser beam intensities passing through the sample containing the nanoparticles and a reference optical path. The LTS variable gain calibration procedure has been validated by firstly using a suspension of NIST standard polystyrene nanoparticles even 36 hours after the calibration procedure was accomplished. The paper reports in detail the LIA implementation describing the design methodologies and the electronic circuits. As a case example of the characterization of biological nanostructures, we demonstrate that a single LTS measurement allowed to determine size density distribution of a population of extracellular vesicles extracted from orange juice (25 nm in size) with the presence of their aggregates having a size of 340 nm and a concentration smaller than 3 orders of magnitude.