Differentiation between malignant and normal human thyroid tissue using frequency analysis of multispectral Photoacoustic images

Sinha, Saugata; Rao, Navalgund; Chinni, Bhargava; Moalem, Jacob; Giampolli, E. J.; Dogra, Vikram S.

doi:10.1109/wnyipw.2013.6890979

Cited by 7 publications

(6 citation statements)

References 9 publications

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“…The objective of the study was to verify the feasibility of differentiating among malignant prostate tissue, benign prostatic hyperplasia (BPH), and normal prostate tissue using frequency domain analysis of the 3D photoacoustic data. Although the experimental protocol and the experimental setup for acquiring photoacoustic data generated by the excised human prostate specimens were described in some of our earlier reports, [30][31][32] here those things are described in a concise way for the sake of completeness and continuity. Figure 1 shows the ex vivo photoacoustic imaging system developed in our laboratory.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Frequency Domain Analysis of a Multiwavelength Photoacoustic Signal for Differentiating Malignant From Benign and Normal Prostates

Sinha

Rao

Chinni

et al. 2016

J of Ultrasound Medicine

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Objectives The purpose of this study was to investigate the feasibility of differentiating malignant prostate from benign prostatic hyperplasia (BPH) and normal prostate tissue by performing frequency domain analysis of photoacoustic images acquired at 2 different wavelengths. Methods We performed multiwavelength photoacoustic imaging on freshly excised human prostate specimens taken from a total of 30 patients undergoing prostatectomy for biopsy-confirmed prostate cancer. Histologic slides marked by a genitourinary pathologist were used as ground truth to define regions of interest (ROIs) in the photoacoustic images. Primarily, 3 different prostate tissue categories, namely malignant, BPH, and normal, were considered, while a fourth category named nonmalignant was formed by combining the ROIs corresponding to BPH and normal tissue together. We extracted 3 spectral parameters, namely slope, midband fit, and intercept, from power spectra of the radiofrequency photoacoustic signals corresponding to the 3 primary tissue categories. Results We analyzed data from 53 ROIs selected from the photoacoustic images of 30 patients. According to the histopathologic analysis, 19 ROIs were malignant, 8 were BPH, and 26 were normal. All the 3 spectral parameters and C-scan grayscale photo - acoustic image pixel values were found to be significantly different (P < .01) between malignant and nonmalignant prostate as well as malignant and normal prostate. Conclusions Preliminary results of our ex vivo human prostate study suggest that spectral parameters obtained by performing frequency domain analysis of photoacoustic signals can be used to differentiate between malignant and nonmalignant prostate.

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Section: Methodsmentioning

confidence: 99%

Evaluation of Frequency Domain Analysis of a Multiwavelength Photoacoustic Signal for Differentiating Malignant From Benign and Normal Prostates

Sinha

Rao

Chinni

et al. 2016

J of Ultrasound Medicine

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“…Three‐dimensional (3D) photoacoustic signals generated by freshly excised thyroid specimens were acquired by an ex vivo photoacoustic imaging system at multiple wavelengths. Although detailed descriptions of the experimental protocol and photoacoustic image acquisition system are available in some of our earlier reports, a concise description of those aspects are provided here for continuity.…”

Section: Methodsmentioning

confidence: 99%

Frequency Domain Analysis of Multiwavelength Photoacoustic Signals for Differentiating Among Malignant, Benign, and Normal Thyroids in an Ex Vivo Study With Human Thyroids

Sinha

Dogra

Chinni

et al. 2017

J of Ultrasound Medicine

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Objective This study investigated the capability of spectral parameters, extracted using frequency domain analysis of photoacoustic (PA) signals, to differentiate between malignant, benign and normal thyroid tissue. Methods We acquired multiwavelength PA images of the freshly excised thyroid specimens, collected from 50 patients who underwent thyroidectomy after being diagnosed with suspected thyroid lesion. A thyroid cytopathologist marked histology slides of each tissue specimen. These marked histology slides were used as ground truth to identify the region of interests (ROI) corresponding to malignant, benign and normal thyroid tissue. Three spectral parameters, namely slope, midband fit and intercept were extracted from PA signals corresponding to different ROIs. Results Spectral parameters were extracted from a total of total of 65 ROIs. According to the ground truth, 12 out of 65 ROIs belonged to malignant thyroid, 28 out of 65 ROIs belonged to benign thyroid and 25 out of 65 ROIs belonged to normal thyroid. Besides slope, the other two spectral parameters and grayscale PA image pixel values were found to be significantly different (p < 0.05) between malignant and normal thyroid. Between benign and normal thyroid, all three spectral parameters and PA pixel values were significantly different (p < 0.05). Conclusion Preliminary results of our ex vivo human thyroid study show that the spectral parameters extracted from radio frequency PA signals as well as the pixel value of 2D PA images can be used for differentiating between malignant, benign and normal thyroid tissue.

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“…Sinha et al investigated multispectral PAI for ex vivo thyroid analysis to overcome the limited information of singlewavelength PAI. [77] They performed a frequency analysis of multispectral PA signals to differentiate malignant nodules from normal tissues. They used a 32-element linear transducer with a center frequency of 5 MHz and a tunable laser at a rate of 10 Hz.…”

Section: Ex Vivo Photoacoustic Analysismentioning

confidence: 99%

Recent Advances in Ultrasound and Photoacoustic Analysis for Thyroid Cancer Diagnosis

Park

Kim

2023

Advanced Physics Research

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Thyroid cancer is one of the most commonly diagnosed cancers worldwide, with a continuously increasing incidence rate in recent decades. Although ultrasonography, which is the current screening method in clinical workflows, has successfully triaged cancerous nodules for biopsy, overdiagnosis has also grown due to the relatively low specificity of the method. Studies are conducted to overcome this overdiagnosis issue by complementing ultrasonography with additional image-based analysis techniques. This review presents an overview of the current advances in clinical trials using advanced ultrasound (US) and photoacoustic (PA) imaging techniques for thyroid nodules in humans. A summary of initial trials by Doppler US and US elastography to improve the classification accuracy of thyroid nodules is presented. Furthermore, recent PA techniques with multispectral analyses utilizing clinically available machines are explored. By amending the existing ultrasonography, the advanced US and PA techniques can enhance the triaging accuracy by analyzing both structural and functional information of thyroid nodules in vivo.

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Differentiation between malignant and normal human thyroid tissue using frequency analysis of multispectral Photoacoustic images

Cited by 7 publications

References 9 publications

Evaluation of Frequency Domain Analysis of a Multiwavelength Photoacoustic Signal for Differentiating Malignant From Benign and Normal Prostates

Evaluation of Frequency Domain Analysis of a Multiwavelength Photoacoustic Signal for Differentiating Malignant From Benign and Normal Prostates

Frequency Domain Analysis of Multiwavelength Photoacoustic Signals for Differentiating Among Malignant, Benign, and Normal Thyroids in an Ex Vivo Study With Human Thyroids

Recent Advances in Ultrasound and Photoacoustic Analysis for Thyroid Cancer Diagnosis

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