Name: Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence (Video) | JoVE Journal
Uploaded: 2025-06-10T12:20:00.000+00:00
Duration: 8 min 5 s
Description: Discover how to detect prostate cancer in biopsies using stimulated Raman histology and artificial intelligence. This protocol improves diagnostic accuracy and supports biobanking for future research.

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5 minutes

We acknowledge the contributions of the research team at Vancouver Prostate Centre and NYU Langone Health, and the technical support provided by Invenio Imaging. This work was funded by the British Columbia Ministry of Health Innovation Hub.

This protocol involves the use of human specimens and adheres to the human care guidelines of the University of British Columbia. The research has been approved by the Institutional Review Board (IRB) under the following ethics approval numbers: SRH: H23-00459, AI: H24-00585, and Biobank: H21-03722. Written informed consent was obtained from all human subjects prior to the collection of specimens. All procedures were conducted in compliance with institutional and regulatory ethical standards to ensure the protection and confidentiality of participants.
1. Turn on the SRH Imager
<ol>
	<li>Power on the SRH imager (Figure 1A). Allow the system to warm up for 30 min to ensure the laser reaches optimal operating temperature for accurate imaging.</li>
</ol>
2. Prepare the fluid chamber
<ol>
	<li>Attach a 50 mL syringe filled with sterilized water to the syringe valve on the left-hand side of the SRH imager interface (Figure 1B). Ensure the syringe is securely fitted to maintain proper fluid circulation.</li>
</ol>
3. Log in to the system
<ol>
	<li>Once the system loads, use the touchscreen monitor to enter the Username and Password.</li>
	<li>Select the appropriate username and type the password. Tap Log in.</li>
	<li>Accept the Disclaimer to acknowledge that the study is for research purposes if used outside of the United States or European Union.</li>
</ol>
4. Create a New Study
<ol>
	<li>Select Create New Study from the display options: Create New Study, Continue Existing Study, and View Existing Study.</li>
</ol>
5. Enter Case Information
<ol>
	<li>Input relevant case information including Last Name, First Name, Medical Record Number, Date of Birth, Accession Number, Trial ID, Physician Name, Room Number, Primary Anatomical Location, and Analysis Module.</li>
	<li>Save the samples as John Doe (for example).</li>
	<li>Under Primary Anatomical Location, select Prostate (Research Use Only).</li>
	<li>For Analysis Mode, choose Prostate Cancer (Research Use Only) to use the integrated AI for prostate cancer detection.</li>
</ol>
6. Finalize Study Creation and Fill the Fluid Chamber
<ol>
	<li>Tap Create Study after entering the case information.</li>
	<li>When prompted by the system, tap Acknowledge to confirm that the data will be used for research purposes only.</li>
	<li>Fill the Fluid Chamber with sterilized water as instructed.</li>
	<li>Tap Next when prompted, then select Acquire from the options displayed.</li>
	<li>Tap Load New Specimen, and the system will display Prepare Specimen &#38; Load NIO Slide.</li>
</ol>
7. Preparation of specimen and slide
<ol>
	<li>Retrieve the prostate biopsy slide. Use tissue forceps with teeth to carefully open the attached coverslip.While holding the slide and the coverslip open, use the tissue forceps to place the prostate biopsy from the RPMI media securely in the groove of the slide. Gently close the coverslip and secure the sample.</li>
	<li>Open the slide holder on the SRH imager interface andinsert the prepared slide into the slide holder, ensuring proper alignment.Close the SRH imager lid. When the system detects the closed lid, tap Next to proceed.</li>
</ol>
8. Set imaging acquisition parameters
<ol>
	<li>Set the following imaging parameters:
	<ol>
		<li>For Specimen Name: Select Biopsy 1 A for the first biopsy.</li>
		<li>For Scan Area: Select 0.4 mm x 6.1 mm, 3 regions (Research Use Only) to scan the entire biopsy.</li>
		<li>For Scan Position: Use the on-screen image to manually adjust the scan location.</li>
	</ol>
	</li>
	<li>Tap Acquire Image to proceed.</li>
	<li>Review the sample details displayed on the screen and confirm by selecting Proceed.</li>
</ol>
9. Acquire the SRH image
<ol>
	<li>Allow the SRH imager to autofocus and acquire images generating the final SRH image.</li>
	<li>Let the imager scan the biopsy in three sections (scan 1, scan 2, and scan 3) as shown in Figure 2A.</li>
	<li>Let the imager combine the sections to form a complete SRH image (Figure 2B), producing a pseudo-H&#38;E image for evaluation.</li>
</ol>
10. Display of the SRH image
<ol>
	<li>View the SRH image of the fresh, unstained prostate biopsy. The image mimics H&#38;E staining using a pink/purple color scheme that highlights CH2 molecular vibrations (associated with lipids) and CH3 molecular vibrations (related to proteins and DNA).</li>
</ol>
11. AI interpretation of the SRH image for research use only
<ol>
	<li>Apply the AI overlay by clicking the (&#62;&#62;) icon on the screen.The AI overlay identifies cancer regions in red, non-cancer regions in green, and non-diagnostic regions in violet (Figure 3A).</li>
	<li>Review the bar graph quantifying the percentage of cancer tissue, non-cancer tissue, and non-diagnostic tissue (Figure 3B).</li>
	<li>Return to the original SRH image without the AI overlay by clicking on the (&#60;&#60;) icon.</li>
</ol>
12. Zoom and navigation of the SRH image
<ol>
	<li>Use the zoom-in and zoom-out functions on the touchscreen to explore different regions of the biopsy in detail.</li>
	<li>Use the navigation icons to move through the image for a comprehensive examination of the biopsy sample.</li>
</ol>
13. Isolation of selected tissue
<ol>
	<li>After the initial scan, carefully remove the biopsy from the slide. Use tissue forceps with teeth to lift the attached coverslip and gently release the biopsy.</li>
	<li>Place the biopsy on a moistened Telfa soaked in saline to maintain tissue integrity during the trimming process.</li>
	<li>Use a surgical blade to trim non-cancer areas identified in the AI-generated overlay of the SRH image by visually assessing the overlay to determine the optimal regions for removal. Focus on removing areas typically located at the ends of the biopsy to increase the cancer-to-tissue ratio. Ensure sufficient tissue is left for re-scanning.</li>
</ol>
14. Re-scan the biopsy
<ol>
	<li>Re-scan the biopsy following the same procedure outlined in steps 9-11.</li>
	<li>Adjust the scan area and position to confirm an increased cancer-to-tissue ratio (seen in Figure 3C-E). Review the updated SRH image and AI overlay to verify the percentages of cancer and non-cancer regions.</li>
	<li>Repeat trimming and re-scanning until the desired ratio is achieved.</li>
</ol>
15. Biobanking and cryopreservation
<ol>
	<li>Remove the biopsy from the slide using tissue forceps with teeth .Place the biopsy in a cryotube.</li>
	<li>Freeze the cryotube in liquid nitrogen to ensure rapid preservation of the sample.</li>
	<li>Transfer the cryotube in liquid nitrogen to a -80 &#176;C freezer or liquid nitrogen storage facility for long-term preservation.</li>
</ol>
16.&#160;Export image data
<ol>
	<li>Tap the Paper Airplane Icon to export image data for storage and further analysis.</li>
	<li>To select the export location, tap the Select Export Location option and choose from USB (De-Identified), USB (Complete), and iPhone (Complete). Select USB (Complete) and choose an external hard disk for data export.</li>
	<li>To select the image series to export, select Entire Study to export all SRH image series for the patient rather than a specific series.</li>
	<li>Wait for the system to display Export in Progress and tap Confirm once the export is complete.</li>
</ol>
17. Turn off the SRH microscope
<ol>
	<li>Tap Exit and follow the shut-down instructions displayed on the screen.</li>
	<li>Select Proceed Without when prompted to archive image data (if already exported).</li>
	<li>Dispose of the sample according to the appropriate laboratory protocols.</li>
	<li>Tap Next and empty the fluid chamber using the attached syringe, as instructed.</li>
	<li>Tap Next when prompted, then select Yes from the options displayed.</li>
	<li>Remove and dispose of the syringe.</li>
	<li>Tap Shut Down to power off the SRH microscope completely.</li>
</ol>

<ol><li>Siegel, R. L., Miller, K. D., Jemal, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Cancer+statistics%2C+2020%5BTitle%5D)+AND+%22CA+Cancer+J+Clin%22%5BJournal%5D)">Cancer statistics, 2020.</a> CA Cancer J Clin. 70 (1), 7-30 (2020).</li>
<li>Epstein, J. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+2014+International+Society+of+Urological+Pathology+%28ISUP%29+Consensus+Conference+on+Gleason+Grading+of+Prostatic+Carcinoma%3A+Definition+of+grading+patterns+and+proposal+for+a+new+grading+system%5BTitle%5D)+AND+%22Am+J+Surg+Pathol%22%5BJournal%5D)">The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of grading patterns and proposal for a new grading system.</a> Am J Surg Pathol. 40 (2), 244-252 (2016).</li>
<li>Freudiger, C. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Stimulated+Raman+scattering+microscopy+with+a+robust+fibre+laser+source%5BTitle%5D)+AND+%22Nat+Photonics%22%5BJournal%5D)">Stimulated Raman scattering microscopy with a robust fibre laser source.</a> Nat Photonics. 8 (2), 153-159 (2014).</li>
<li>Freudiger, C. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Label-free+biomedical+imaging+with+high+sensitivity+by+stimulated+Raman+scattering+microscopy%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">Label-free biomedical imaging with high sensitivity by stimulated Raman scattering microscopy.</a> Science. 322 (5909), 1857-1861 (2008).</li>
<li>Hu, F., Shi, L., Min, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Biological+imaging+of+chemical+bonds+by+stimulated+Raman+scattering+microscopy%5BTitle%5D)+AND+%22Nat+Methods%22%5BJournal%5D)">Biological imaging of chemical bonds by stimulated Raman scattering microscopy.</a> Nat Methods. 16 (9), 830-842 (2019).</li>
<li>Cheng, Q., Miao, Y., Wild, J., Min, W., Yang, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Emerging+applications+of+stimulated+Raman+scattering+microscopy+in+materials+science%5BTitle%5D)+AND+%22Matter%22%5BJournal%5D)">Emerging applications of stimulated Raman scattering microscopy in materials science.</a> Matter. 4 (5), 1460-1483 (2021).</li>
<li>Orringer, D. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Rapid+intraoperative+histology+of+unprocessed+surgical+specimens+via+fibre-laser-based+stimulated+Raman+scattering+microscopy%5BTitle%5D)+AND+%22Nat+Biomed+Eng%22%5BJournal%5D)">Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy.</a> Nat Biomed Eng. 1, 0027(2017).</li>
<li>Mannas, M. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Stimulated+Raman+histology%2C+a+novel+method+to+allow+for+rapid+pathologic+examination+of+unprocessed%2C+fresh+prostate+biopsies%5BTitle%5D)+AND+%22Prostate%22%5BJournal%5D)">Stimulated Raman histology, a novel method to allow for rapid pathologic examination of unprocessed, fresh prostate biopsies.</a> Prostate. 83 (11), 1060-1067 (2023).</li>
<li>Mannas, M. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Stimulated+Raman+histology+interpretation+by+artificial+intelligence+provides+near-real-time+pathologic+feedback+for+unprocessed+prostate+biopsies%5BTitle%5D)+AND+%22J+Urol%22%5BJournal%5D)">Stimulated Raman histology interpretation by artificial intelligence provides near-real-time pathologic feedback for unprocessed prostate biopsies.</a> J Urol. 211 (3), 384-391 (2024).</li>
<li>Mannas, M. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Intraoperative+margin+assessment+with+near+real+time+pathology+during+partial+gland+ablation+of+prostate+cancer%3A+A+feasibility+study%5BTitle%5D)+AND+%22Urol+Oncol%22%5BJournal%5D)">Intraoperative margin assessment with near real time pathology during partial gland ablation of prostate cancer: A feasibility study.</a> Urol Oncol. 43 (1), 64.e19-64.e25 (2024).</li>
<li>Mannas, P. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((MP61-18+stimulated+Raman+histology%2C+a+novel+method+for+intraoperative+surgical+margin+assessments+during+robotic+assisted+laparoscopic+prostatectomy%5BTitle%5D)+AND+%22J+Urol%22%5BJournal%5D)">MP61-18 stimulated Raman histology, a novel method for intraoperative surgical margin assessments during robotic assisted laparoscopic prostatectomy.</a> J Urol. 209 (Supplement 4), (2023).</li>
<li>Hollon, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Artificial-intelligence-based+molecular+classification+of+diffuse+gliomas+using+rapid%2C+label-free+optical+imaging%5BTitle%5D)+AND+%22Nat+Med%22%5BJournal%5D)">Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging.</a> Nat Med. 29 (4), 828-832 (2023).</li>
<li>Lee, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Recent+advances+in+the+use+of+stimulated+Raman+scattering+in+histopathology%5BTitle%5D)+AND+%22Analyst%22%5BJournal%5D)">Recent advances in the use of stimulated Raman scattering in histopathology.</a> Analyst. 146 (3), 789-802 (2021).</li>
<li>Sarri, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((In+vivo+organoid+growth+monitoring+by+stimulated+Raman+histology%5BTitle%5D)+AND+%22Npj+Imaging%22%5BJournal%5D)">In vivo organoid growth monitoring by stimulated Raman histology.</a> Npj Imaging. 2 (1), 18(2024).</li>
<li>Ao, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Stimulated+Raman+scattering+microscopy+enables+Gleason+scoring+of+prostate+core+needle+biopsy+by+a+convolutional+neural+network%5BTitle%5D)+AND+%22Cancer+Res%22%5BJournal%5D)">Stimulated Raman scattering microscopy enables Gleason scoring of prostate core needle biopsy by a convolutional neural network.</a> Cancer Res. 83 (4), 641-651 (2023).</li>
</ol>

C. Freudiger is an employee, shareholder, and director of Invenio Imaging and holds patents on stimulated Raman spectroscopic microscopy that are independently licensed. A. Ion-Margineanu is a shareholder of Invenio Imaging.

The SRH protocol for prostate cancer detection represents a significant advancement in medical imaging and histopathology. SRH enables near-real-time, label-free imaging of fresh, unstained tissue, allowing for rapid cancer detection of unprocessed tissues without the delays associated with traditional histopathological methods3,4,5,6,7,<sup class="...

Prostate cancer remains one of the leading malignancies affecting men globally, with early detection being pivotal for successful intervention and treatment1. Historically, the diagnosis of prostate cancer has relied heavily on histopathological evaluation of prostate biopsy samples, most commonly through Hematoxylin and Eosin (H&#38;E) staining2. While effective, traditional methods of prostate biopsy analysis typically result in a waiting period of several days to weeks, depending on the city or country, due to procedural and logistical factors. These delays arise from multiple labor-intensive steps, including formalin fixation, paraffin embedding, sectioning, and H&#38;E staining. Thus, the cumulative processing time, compounded by the high volume of biopsy samples can delay diagnosis and treatment planning.
Recent advances in imaging technologies particularly stimulated Raman scattering (SRS) microscopy, can transform diagnostic practices by providing a robust imaging method that is background-free and easily interpretable3,4. SRS utilizes two laser beams, the pump beam (&#969;p) and the Stokes beam (&#969;s), which interact with the sample. When the frequency difference (&#916;&#969; = &#969;p &#8722;&#969;s) matches a specific molecular vibrational frequency (&#937;), the signal is amplified due to stimulated Raman gain or loss. This process enhances the contrast of molecular vibrations, allowing for highly sensitive imaging of tissues3,4. SRS enables the detection of molecular vibrations associated with CH2 stretching vibrations (2,845 cm-1), correlating with lipids, and CH3 stretching vibrations (2,930 cm-1), linked to proteins and DNA4. The detection of the SRS signal typically involves a high-frequency modulation transfer scheme, allowing for precise isolation of the weak vibrational signals from background noise.
SRS microscopy has optical sectioning capabilities that enable precise three-dimensional imaging without the need for physical tissue sectioning. This is achieved by aligning and focusing the pump and Stokes laser beams at a diffraction-limited spot within the sample, where specific molecular vibrations are excited. The confocal nature of SRS, derived from its quadratic dependence on the lasers&#39; intensity, ensures that signals are confined to the focal plane, excluding out-of-focus contributions and providing highly localized chemical information5,6. This depth-resolved imaging preserves tissue integrity by eliminating mechanical slicing, reducing processing time, and maintaining the biological and molecular context of the sample.
Building on the principles of SRS, stimulated Raman histology (SRH) utilizes this molecular vibrational data to create pseudo-H&#38;E images of fresh, unstained tissue in real time, thus providing clinicians with faster and more efficient diagnostic tools7,8. This capability to generate high-quality images has made SRH an indispensable tool for research and potential clinical applications9. Recently, intraoperative margin assessment using SRH provided near-real-time pathologic feedback during partial gland ablation and radical prostatectomy, allowing for immediate treatment adjustments10,11.
The SRH imager leverages intrinsic molecular vibrations to provide insights into tissue composition. SRH can be used to effectively differentiate cancerous from benign prostate tissues by analyzing CH2 and CH3 vibrational properties7,12. The SRH imager captures these vibrations and produces pseudo-H&#38;E images that enhance nuclear contrast, serving as a rapid alternative to conventional histopathology and delivering high-quality images in 2-8 min, depending on tissue size7,8.
The effectiveness of SRH for the rapid pathologic examination of unprocessed prostate biopsies was evaluated. Pathologists were trained to interpret SRH images from prostate biopsy cores obtained ex vivo from prostatectomy specimens8. The SRH scanning method was optimized to enable the acquisition of high-resolution images within minutes, significantly reducing the time required compared to traditional histopathology. Biopsy samples containing a mix of benign and malignant histology served as a training set for the pathologists, who then performed a blinded evaluation of a separate set of biopsies imaged by SRH and processed by H&#38;E staining to serve as ground truth. The results showed that the mean pathologist accuracy for identifying prostate cancer was 95.7%, with good concordance in detecting clinically significant cancers, indicating that SRH can effectively support near-real-time diagnosis8.
In subsequent studies, artificial intelligence (AI) was integrated to further enhance diagnostic accuracy, efficiency, and ease of implementation. This AI model employs deep learning techniques to analyze vibrational and morphological features captured by SRH, enabling automated classification of prostate biopsy samples into benign, cancerous, and non-diagnostic regions, significantly streamlining the pathological assessment process9. The SRH-AI integration demonstrated impressive accuracy, achieving 96.5% in prostate cancer detection, with sensitivity and specificity rates of 96.3% and 96.6%, respectively9. By integrating AI with SRH, diagnostic performance matching that of experienced pathologists was achieved.
Through the extensive evaluation of SRH with pathologists and the development of an AI model integrated into the SRH imager, the capabilities of this technology have been significantly advanced. This protocol outlines the detailed steps for preparing prostate biopsy samples, imaging them using the SRH imager, and analyzing the data with AI-assisted tools. By following these steps, researchers and clinicians can leverage this novel technique to enhance prostate cancer detection, research, and treatment.

<table><tbody><tr><td>Benchtop Liquid Nitrogen Container</td><td>Thermo Scientific</td><td>11-670-4B</td><td></td></tr><tr><td>Cytotube</td><td>Greiner Bio-One</td><td>126279</td><td></td></tr><tr><td>Dumont #5 Fine Forceps</td><td>Fine Science Tools</td><td>11254-20</td><td></td></tr><tr><td>NIO Prostate Biopsy Slide</td><td>Invenio Imaging, Inc.</td><td>AT0013</td><td></td></tr><tr><td>RPMI Solution</td><td>Thermo Fisher Scientific</td><td>11875093</td><td></td></tr><tr><td>Saline Solution</td><td>Baxter</td><td></td><td></td></tr><tr><td>SRH Imager (NIO Laser Imaging System)</td><td>Invenio Imaging, Inc.</td><td></td><td></td></tr><tr><td>Surgical Blade</td><td>Fisher Scientific</td><td>501094395</td><td></td></tr></tbody></table>

detection and isolation of cancer in prostate biopsies using stimulated raman histology and artificial intelligence

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Prostate cancer remains one of the most prevalent malignancies affecting men worldwide, making early detection and advancements in precision medicine crucial for effective intervention and treatment. A standardized protocol is presented for utilizing stimulated Raman histology (SRH) with integrated artificial intelligence (AI) in prostate cancer detection, offering significant advancements over conventional histopathological methods. SRH provides these advancements by enhancing efficiency through near-real-time, label-free imaging of fresh, unstained tissues, thereby eliminating the delays associated with traditional biopsy analysis.
By using stimulated Raman scattering (SRS) microscopy to detect the specific vibrational frequencies of CH2 bonds associated with lipids and CH3 bonds linked to proteins and DNA, cancerous and benign tissues in prostate biopsies can be differentiated. The AI model further enhances diagnostic precision, achieving 98.6% accuracy in identifying prostate cancer. The protocol outlines essential steps for sample preparation, imaging, and data analysis, facilitating improved biobanking processes and enabling downstream applications, such as transcriptomics and xenograft studies. This approach accelerates the diagnostic workflow and shows promise for intraoperative applications, potentially aiding surgeons in identifying positive margins intraoperatively. Additionally, the ability to re-scan and adjust cancer-to-tissue ratios allows for a more tailored analysis of biopsy samples, enhancing tumor detection in unprocessed tissues. Further research and validation are necessary for the widespread adoption of SRH in clinical practice.

The application of SRH integrated with AI demonstrated the rapid detection and characterization of prostate cancer within biopsy samples in minutes. Figure 2A outlines the multi-step scanning procedure of the SRH imager, where three distinct scans (scan 1, scan 2, and scan 3) were performed across the biopsy sample. Each scan captured unique molecular vibrational signatures corresponding to lipid, protein, and DNA content, essential for generating a comprehensive SRH image. The final composi...

Here, we present a standardized protocol for detecting prostate cancer using stimulated Raman histology (SRH) on biopsy samples due to advantages over traditional histopathology, focusing on sample preparation, imaging, and artificial intelligence to improve the cancer-to-tissue ratio. Additionally, it supports biobanking for transcriptomics, organoid or xenograft models, and identification of intraoperative surgical margins.

Prostate cancer remains one of the most prevalent malignancies affecting men worldwide, making early detection and advancements in precision medicine ...

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Discover how to detect prostate cancer in biopsies using stimulated Raman histology and artificial intelligence. This protocol improves diagnostic accuracy and supports biobanking for future research.

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

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