Mid-infrared spectral classification of endometrial cancer compared to benign controls in serum or plasma samples

Mabwa, David; Gajjar, Ketankumar; Furniss, David; Schiemer, Roberta; Crane, Richard; Fallaize, Christopher J.; Martin‐Hirsch, Pierre L.; Martin, Francis; Kypraios, Theordore; Seddon, Angela B.; Phang, Sendy

doi:10.1039/d1an00833a

Cited by 13 publications

(15 citation statements)

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“…Special attention was paid to the 700-1450 cm −1 range of the ATR spectra. As other studies pointed out, spectral ranges outside of amide band regions are better suited to discriminating between ill and healthy subjects [ 28 , 47 ]. The second derivatives of ATR spectra without additional pretreatment were used to construct chemometric models.…”

Section: Resultsmentioning

confidence: 98%

“…In this study, we present multivariate models that can discriminate among advanced endometriosis, nonendometriosis, and healthy controls by applying previously determined biochemical parameters of serum samples [ 2 , 26 ] and their ATR spectra. In a commonly used approaches, two groups, i.e., patients and healthy controls, are usually taken into account [ 27 , 28 ]. However, in our research, two groups of women suffering from benign pathologic conditions, one with advanced endometriosis and one for which endometriosis was excluded, were compared with a group of healthy women without any symptoms of inflammation or medical history of endometriosis, to select biomarkers allowing for discrimination among these three groups of women.…”

Section: Introductionmentioning

confidence: 99%

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ATR-IR Spectroscopy Application to Diagnostic Screening of Advanced Endometriosis

Kokot

Mazurek

Piwowar

et al. 2022

Oxidative Medicine and Cellular Longevity

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Endometriosis is one of the most common gynecological diseases among young women of reproductive age. Thus far, it has not been possible to define a parameter that is sensitive and specific enough to be a recognized biomarker for diagnosing this disease. Nonspecific symptoms of endometriosis and delayed diagnosis are impulses for researching noninvasive methods of differentiating endometriosis from other gynecological disorders. We compared three groups of individuals in our research: women with endometriosis (E), patients suffering from other gynecological disorders (nonendometriosis, NE), and healthy women from the control group (C). Partial least squares discriminant analysis (PLS-DA) models were developed based on selected serum biochemical parameters, specific regions of the serum’s infrared attenuated total reflectance (FTIR ATR) spectra, and combined data. Incorporating the spectral data into the models significantly improved differentiation among the three groups, with an overall accuracy of 87.5%, 97.3%, and 98.5%, respectively. This study shows that infrared spectroscopy and discriminant analysis can be used to differentiate serum samples among women with advanced endometriosis, women without this disease, i.e., healthy women, and, most importantly, also women with other benign gynecological disorders.

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Section: Resultsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

ATR-IR Spectroscopy Application to Diagnostic Screening of Advanced Endometriosis

Kokot

Mazurek

Piwowar

et al. 2022

Oxidative Medicine and Cellular Longevity

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“…The k -nearest neighbor (kNN) [ 21 , 22 , 23 , 24 , 25 ] is one of the most commonly used multi-classification algorithms. When it was applied to a supervised multi-category problem, the idea was as follows: based on the spectra of calibration samples containing multiple categories, the Euclidean (or Mahalanobis) distances between the unknown sample and all calibration samples were calculated; the k nearest calibration samples were determined; finally, the unknown sample was categorized as the category with the largest number among the k nearest samples.…”

Section: Introductionmentioning

confidence: 99%

“…It is not limited by the number of categories and is especially suitable for multi-category spectral discriminant analysis. The kNN has been applied to multi-category discriminant analysis based on various spectral techniques, such as, NIR [ 21 ], mid-infrared [ 22 ], Raman [ 23 , 24 ], and laser-induced breakdown spectroscopies [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

Performance Improvement of NIR Spectral Pattern Recognition from Three Compensation Models’ Voting and Multi-Modal Fusion

Fang

et al. 2022

Molecules

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Inspired by aquaphotomics, the optical path length of measurement was regarded as a perturbation factor. Near-infrared (NIR) spectroscopy with multi-measurement modals was applied to the discriminant analysis of three categories of drinking water. Moving window-k nearest neighbor (MW-kNN) and Norris derivative filter were used for modeling and optimization. Drawing on the idea of game theory, the strategy for two-category priority compensation and three-model voting with multi-modal fusion was proposed. Moving window correlation coefficient (MWCC), inter-category and intra-category MWCC spectra, and k-shortest distances plotting with MW-kNN were proposed to evaluate weak differences between two spectral populations. For three measurement modals (1 mm, 4 mm, and 10 mm), the optimal MW-kNN models, and two-category priority compensation models were determined. The joint models for three compensation models’ voting were established. Comprehensive discrimination effects of joint models were better than their sub-models; multi-modal fusion was better than single-modal fusion. The best joint model was the dual-modal fusion of compensation models of one- and two-category priority (1 mm), one- and three-category priority (10 mm), and two- and three-category priority (1 mm), validation’s total recognition accuracy rate reached 95.5%. It fused long-wave models (1 mm, containing 1450 nm) and short-wave models (10 mm, containing 974 nm). The results showed that compensation models’ voting and multi-modal fusion can effectively improve the performance of NIR spectral pattern recognition.

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“…Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) is a frequently used spectroscopic technique that produces different absorbance intensities in several wavelengths of the electromagnetic spectrum following molecular excitation from an infrared source [ 11 ]. Its application in easily collectable biofluids (particularly blood and urine) has shown considerable potential for detecting several types of cancer [ 12 , 13 , 14 , 15 , 16 ], including endometrial cancer [ 17 , 18 , 19 ]. These biofluids are ideal for cancer detection through spectroscopy, as their acquisition is minimally or non-invasive with negligible cost [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Infrared Spectroscopy of Urine for the Non-Invasive Detection of Endometrial Cancer

Ramírez

Stringfellow

Naik

et al. 2022

Cancers

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Current triage for women with post-menopausal bleeding (PMB) to diagnose endometrial cancer rely on specialist referral for intimate tests to sequentially image, visualise and sample the endometrium. A point-of-care non-invasive triage tool with an instant readout could provide immediate reassurance for low-risk symptomatic women, whilst fast-tracking high-risk women for urgent intrauterine investigations. This study assessed the potential for infrared (IR) spectroscopy and attenuated total reflection (ATR) technology coupled with chemometric analysis of the resulting spectra for endometrial cancer detection in urine samples. Standardised urine collection and processing protocols were developed to ensure spectroscopic differences between cases and controls reflected cancer status. Urine spectroscopy distinguished endometrial cancer (n = 109) from benign gynaecological conditions (n = 110) with a sensitivity of 98% and specificity of 97%. If confirmed in subsequent low prevalence studies embedded in PMB clinics, this novel endometrial cancer detection tool could transform clinical practice by accurately selecting women with malignant pathology for urgent diagnostic work up whilst safely reassuring those without.

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Mid-infrared spectral classification of endometrial cancer compared to benign controls in serum or plasma samples

Abstract: This study demonstrates a discrimination of endometrial cancer versus (non-cancerous) benign controls based on mid-infrared (MIR) spectroscopy of dried plasma or serum liquid samples. A detailed evaluation was performed of...

Cited by 13 publications

References 50 publications

ATR-IR Spectroscopy Application to Diagnostic Screening of Advanced Endometriosis

ATR-IR Spectroscopy Application to Diagnostic Screening of Advanced Endometriosis

Performance Improvement of NIR Spectral Pattern Recognition from Three Compensation Models’ Voting and Multi-Modal Fusion

Infrared Spectroscopy of Urine for the Non-Invasive Detection of Endometrial Cancer

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