Female patients' perception of pain caused by mammography in the Western Region of Saudi Arabia

Application of serum Raman spectroscopy combined with classification model for rapid breast cancer screening

Introduction

This study aimed to evaluate the feasibility of using general Raman spectroscopy as a method to screen for breast cancer. The objective was to develop a machine learning model that utilizes Raman spectroscopy to detect serum samples from breast cancer patients, benign cases, and healthy subjects, with puncture biopsy as the gold standard for comparison. The goal was to explore the value of Raman spectroscopy in the differential diagnosis of breast cancer, benign lesions, and healthy individuals.

Methods

In this study, blood serum samples were collected from a total of 333 participants. Among them, there were 129 cases of tumors (pathologically diagnosed as breast cancer and labeled as cancer), 91 cases of benign lesions (pathologically diagnosed as benign and labeled as benign), and 113 cases of healthy controls (labeled as normal). Raman spectra of the serum samples from each group were collected. To classify the normal, benign, and cancer sample groups, principal component analysis (PCA) combined with support vector machine (SVM) was used. The SVM model was evaluated using a cross-validation method.

Results

The results of the study revealed significant differences in the mean Raman spectra of the serum samples between the normal and tumor/benign groups. Although the mean Raman spectra showed slight variations between the cancer and benign groups, the SVM model achieved a remarkable prediction accuracy of up to 98% for classifying cancer, benign, and normal groups.

Discussion

In conclusion, this exploratory study has demonstrated the tremendous potential of general Raman spectroscopy as a clinical adjunctive diagnostic and rapid screening tool for breast cancer.

Optical biosensor based on SERS with signal calibration function for quantitative detection of carcinoembryonic antigen

Monitoring the levels of cancer biomarkers is essential for cancer diagnosis and evaluation. In this study, a novel sandwich type sensing platform based on surface-enhanced Raman scattering (SERS) technology was developed for the detection of carcinoembryonic antigen (CEA), with a limit of detection (LOD) of 0.258 ng/mL. In order to achieve sensitive detection of CEA in complex samples, gold nanoparticle monolayer modified with CEA antibodies and with aptamer-functionalized probes was fabricated to target CEA. Two gold layers were integrated into the SERS platform, which greatly enhanced the signal of the probe by generating tremendous "hot spots". Meanwhile, the intensity ratio of Raman probes and the second-order peak of the silicon wafer was used to achieve dynamic calibration of the Raman probe signal. Excitingly, this sensing platform was capable of distinguishing cancer patients from healthy individuals via CEA concentrations in blood samples with the accuracy of 100%. This sandwich structure SERS sensing platform presented promising potential to be an alternative tool for clinical biomarker detection in the field of cancer diagnosis.

Compression force variability in mammography in Ghana - A baseline study

INTRODUCTION

Breast compression during mammographic examinations improves image quality and patient management. Several studies have been conducted to assess compression force variability among practitioners in order to establish compression guidelines. However, no such study has been conducted in Ghana. This study aims to investigate the compression force variability in mammography in Ghana.

METHODS

This retrospective study used data gathered from 1071 screening and diagnostic mammography patients from January, 2018-December, 2019. Data were gathered by seven radiographers at three centers. Compression force, breast thickness and practitioners' years of work experience were recorded. Compression force variability among practitioners and the correlation between compression force and breast thickness were investigated.

RESULTS

Mean compression force values recorded for craniocaudal (CC) (17.2 daN) and mediolateral oblique (MLO) (18.2 daN), were within the recommended values used by western countries. Most of the mammograms performed - 80% - were within the National Health Service Breast Screening Programme (NHSBSP) range. However, 65% were above the Norwegian Breast Cancer Screening Programme (NBCSP) range. Compression forces varied significantly (p = 0.0001) among practitioners. Compression forces increased significantly (p = 0.0001) with the years of work experience. A weak negative correlation (r = -0.144) and a weak positive correlation (r = 0.142) were established between compression force and breast thickness for CC and MLO projections respectively.

CONCLUSION

This initial study confirmed that although wide variations in compression force exist among practitioners in Ghana, most practitioners used compression forces broadly within the range set by the NHSBSP. As no national guidelines for compression force currently exist in Ghana, provision of these may help to reduce the range of variations recorded.

IMPLICATIONS FOR PRACTICE

Confirmation of variations in compression will guide future practice to minimize image quality disparities and improve quality of care.

Label-Free Surface-Enhanced Raman Spectroscopy Biosensor for On-Site Breast Cancer Detection Using Human Tears

Surface-enhanced Raman scattering (SERS) is an ultrasensitive molecular screening technique with greatly enhanced Raman scattering signals from trace amounts of analytes near plasmonic nanostructures. However, research on the development of a sensor that balances signal enhancement, reproducibility, and uniformity has not yet been proposed for practical applications. In this study, we demonstrate the potential of the practical application for detecting or predicting asymptomatic breast cancer from human tears using a portable Raman spectrometer with an identification algorithm based on multivariate statistics. This potentiality was realized through the fabrication of a plasmonic SERS substrate equipped with a well-aligned, gold-decorated, hexagonal-close-packed polystyrene (Au/HCP-PS) nanosphere monolayer that provided femtomole-scale detection, giga-scale enhancement, and <5% relative standard deviation for reliability and reproducibility, regardless of the measuring site. Our results can provide a first step toward developing a noninvasive, real-time screening technology for detecting asymptomatic tumors and preventing tumor recurrence.