Tissue characterization utilizing hyperspectral imaging for liver thermal ablation

Aref, Mohamed Hisham; Aboughaleb, Ibrahim H.; El-Sharkawy, Yasser H.

doi:10.1016/j.pdpdt.2020.101899

Cited by 22 publications

(19 citation statements)

References 42 publications

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“…In addition, the spectral signature of the surface RFA of ex vivo liver samples has been identified in a previously published paper. 59 The diffuse reflectance signatures were computed from the mean of the three different regions of the complete investigated liver tissue samples, which were validated later by the pathologist after thermal ablation and slicing, as shown in Figure 4c-e. The investigated samples after RFA were sliced and stored in evacuated wrap bags with tissue storage solution for later evaluation by the pathologist to confirm the ablated and the thermally affected regions, and compare them with the output of the system image processing algorithm.…”

Section: Resultsmentioning

confidence: 99%

“…We could vary the identified region (normal, ablation, thermally affected) by changing the K-means value. 59 Generally, contour delineation is an early step for target or organ identification to achieve successful image-guided therapy, usually for some additional processing such as evaluating the characteristics of ROIs or construction of quantitative measurements to observe disease progression. 70 Then, contour delineation is applied at each wavelength and the K-means value is changed to reach the optimum value for region identifications.…”

Section: Spectral Mapping and Acquisitionmentioning

confidence: 99%

“…Aref et al used the HSI of ex vivo cow liver to evaluate the variations of the tissue optical properties with different responses to light (transmission, specular reflection, absorption and diffuse reflection) over the whole spectral range and selected the best wavelengths that can distinguish between the different regions (normal/thermally influenced/ablated), see Figure A2 in the Appendix. [58][59][60] This study aims to monitor the RFA of the investigated ex vivo liver samples to distinguish between the normal and the ablated regions, as well as the thermally affected regions by measuring the diffuse reflectance (R d ) with two different systems. Initially, a hyperspectral (HS) camera with a polychromatic light source (tungsten halogen lamp) within the spectral range 348-950 nm was employed.…”

Section: Introductionmentioning

confidence: 99%

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Prospective study for commercial and low-cost hyperspectral imaging systems to evaluate thermal tissue effect on bovine liver samples

Aref¹,

Hussein²,

Youssef

et al. 2021

J. Spectral Imaging

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Thermal ablation modalities, for example radiofrequency ablation (RFA) and microwave ablation, are intended to prompt controlled tumour removal by raising tissue temperature. However, monitoring the size of the resulting tissue damage during the thermal removal procedures is a challenging task. The objective of this study was to evaluate the observation of RFA on an ex vivo liver sample with both a commercial and a low-cost system to distinguish between the normal and the ablated regions as well as the thermally affected regions. RFA trials were conducted on five different ex vivo normal bovine samples and monitored initially by a custom hyperspectral (HS) camera to measure the diffuse reflectance (Rd) utilising a polychromatic light source (tungsten halogen lamp) within the spectral range 348–950 nm. Next, the light source was replaced with monochromatic LEDs (415, 565 and 660 nm) and a commercial charge-coupled device (CCD) camera was used instead of the HS camera. The system algorithm comprises image enhancement (normalisation and moving average filter) and image segmentation with K-means clustering, combining spectral and spatial information to assess the variable responses to polychromatic light and monochromatic LEDs to highlight the differences in the Rd properties of thermally affected/normal tissue regions. The measured spectral signatures of the various regions, besides the calculation of the standard deviations (δ) between the generated six groups, guided us to select three optimal wavelengths (420, 540 and 660 nm) to discriminate between these various regions. Next, we selected six spectral images to apply the image processing to (at 450, 500, 550, 600, 650 and 700 nm). We noticed that the optimum image is the superimposed spectral images at 550, 600, 650 and 700 nm, which are capable of discriminating between the various regions. Later, we measured Rd with the CCD camera and commercially available monochromatic LED light sources at 415, 565 and 660 nm. Compared to the HS camera results, this system was more capable of identifying the ablated and the thermally affected regions of surface RFA than the side-penetration RFA of the investigated ex vivo liver samples. However, we succeeded in developing a low-cost system that provides satisfactory information to highlight the ablated and thermally affected region to improve the outcome of surgical tumour ablation with much shorter time for image capture and processing compared to the HS system.

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Section: Resultsmentioning

confidence: 99%

Section: Spectral Mapping and Acquisitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Prospective study for commercial and low-cost hyperspectral imaging systems to evaluate thermal tissue effect on bovine liver samples

Aref¹,

Hussein²,

Youssef

et al. 2021

J. Spectral Imaging

Self Cite

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“…HSI is a potential tool in medical diagnostics with many applications in discriminating between cancer and non-cancerous tissues, sensing and detecting the abnormal lesions. We have recently exploit the HIS in developing custom optical imaging system for diagnosis and imaging of ex-vivo breast cancer [74,75], in addition to, using HIS in liver tissue characterization for liver thermal ablation [76]. However, to the best of our knowledge, this is the first study to use a Hyperspectral camera in producing distinctive spectral signatures based on total RNA extracted from sera samples.…”

Section: Discussionmentioning

confidence: 99%

Integration of transcriptomes analysis with spectral signature of total RNA for generation of affordable remote sensing of Hepatocellular carcinoma in serum clinical specimens

Aboughaleb

Matboli

Shawky

et al. 2021

Heliyon

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Hepatocellular carcinoma (HCC) is a major global health problem with about 841,000 new cases and 782,000 deaths annually, due to lacking early biomarker/s, and centralized diagnosis. Transcriptomes research despite its infancy has proved excellence in its implementation in identifying a coherent specific cancer RNAs differential expression. However, results are sometimes overlapped by other cancer types which negatively affecting specificity, plus the high cost of the equipment used. Hyperspectral imaging (HSI) is an advanced tool with unique, spectroscopic features, is an emerging tool that has widely been used in cancer detection. Herein, a pilot study has been performed for HCC diagnosis, by exploiting HIS properties and the analysis of the transcriptome for the development of non-invasive remote HCC sensing. HSI data cube images of the sera extracted total RNA have been analyzed in HCC, normal subject, liver benign tumor, and chronic HCV with cirrhotic/non-cirrhotic liver groups. Data analyses have revealed a specific spectral signature for all groups and can be easily discriminated; at the computed optimum wavelength. Moreover, we have developed a simple setup based on a commercial laser pointer for sample illumination and a Smartphone CCD camera, with HSI consistent data output. We hypothesized that RNA differential expression and its spatial organization/folding are the key players in the obtained spectral signatures. To the best of our knowledge, we are the first to use HSI for sensing cancer based on total RNA in serum, using a Smartphone CCD camera/laser pointer. The proposed biosensor is simple, rapid (2 min), and affordable with specificity and sensitivity of more than 98% and high accuracy.

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“…A study was conducted to highlight the unique properties of HSI in radiofrequency ablation 41 (RFA). Aref et al showed that HSI could be a powerful tool in distinguishing thermal ablation of 10 samples of the ex-vivo bovine liver due to the variations of the optical properties, with the trials 41 showing an ideal spectral image (720±18.92 nm).…”

Section: Article Infomentioning

confidence: 99%

Novel Approach Exploiting the Hyperspectral Imaging System for Breast Cancer Therapy and Diagnosis

2020

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Background: Breast malignant growth is the most widely recognized disease in women in both highly and less developed nations where early detection is vital for life-saving and fast recovery. Recently, Photonic technologies has played a vital role in medical applications. Their satisfactory and viable implementation in therapy and diagnosis requires reliable information on the optical properties of human tissues. This study presents an outline of recent outcomes on the magnitude of breast tissue optical properties.Methods: We established two different system setups utilizing hyperspectral (HS) camera and multiple excitation source lights with wavelength (380~1050 nm) for this investigation. The first setup (Transmission Mode) was applied for light transmission measurement of ex-vivo breast sample. Thereby, we made calculations of sample absorption. The second setup (Reflection Mode) was used for the measurement of breast sample light diffuse reflectance. The outcomes of both setups were used to select the optimum spectral image to differentiate between the normal and tumoral regions in the ex-vivo breast sample by exploring the optical properties spectroscopy in the Near and visible (NIR-VIS) spectrum. Finally, we applied the custom system on the case study technique for breast tumor detection.Results: Experimental investigations results showed that due to the various excitation wavelength light source (380~1050 nm) generates variable depths of penetration depth in the ex-vivo breast sample. Consequently, experimental results of the diffuse reflectance (?d) provide the optimum spectral image at 600 nm for the diagnostic applications. However, the statistical calculation of the normalized signal validated the outcome at wavelength 680 nm. Additionally, we noticed the optimum spectral image for therapy applications at 700 nm by measurement of breast tissue transmission (?) and attenuation absorption (?) calculation. Moreover, the statistical calculation of the normalized signal validated the outcome at wavelength 760 nm.Conclusions: The proposed novel approach successfully provided promising results of the investigated breast sample optical properties in both diagnostic and therapy applications to assist the pathologist and the surgeon. The trail outcomes of the investigated case study were impressive for selecting optimum wavelength for diagnostic and treatment (680, 760 nm), respectively.

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Tissue characterization utilizing hyperspectral imaging for liver thermal ablation

Cited by 22 publications

References 42 publications

Prospective study for commercial and low-cost hyperspectral imaging systems to evaluate thermal tissue effect on bovine liver samples

Prospective study for commercial and low-cost hyperspectral imaging systems to evaluate thermal tissue effect on bovine liver samples

Integration of transcriptomes analysis with spectral signature of total RNA for generation of affordable remote sensing of Hepatocellular carcinoma in serum clinical specimens

Novel Approach Exploiting the Hyperspectral Imaging System for Breast Cancer Therapy and Diagnosis

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