Pathologists Use Spatial Light Interference Microscopy to Predict Risk of Prostate Cancer Recurrence Prior to Biopsy or Surgery
|
By LabMedica International staff writers Posted on 24 May 2015 |

Image: Left: Quantitative phase image of an unstained prostatectomy sample from a patient who had a biochemical recurrence of prostate cancer. Right: A zoomed-in region from the quantitative phase image showing a cancerous gland with debris in the lumen. The stroma, or supportive tissue environment, shows discontinuities in the fiber length and disorganization in the orientation of the fibers (Photo courtesy of the University of Illinois).
A novel microscopy method that combines phase contrast microscopy with holography enables prediction of the likelihood of prostate cancer recurrence prior to biopsy or surgery.
The method is called spatial light interference microscopy or SLIM. SLIM uses a commercial phase contrast microscope and white light illumination, resulting in nanometer scale sensitivity to optical path-length shifts. In essence, SLIM combines phase contrast microscopy with holography.
Investigators at the University of Illinois (Urbana, USA) have introduced a new instrument for SLIM imaging. Their real-time fast SLIM technique could image at a maximum rate of 50 frames per second and provided real-time quantitative phase images at 12.5 frames per second. They were able to achieve this fast rate by combining rapid LCPM (linear pulse-code modulation) and a fast sCMOS camera. In addition, they developed the software to perform phase reconstruction and display the quantitative phase images in real-time.
In the current study, the investigators used the SLIM technique to examine 181 tissue samples obtained from the [US] National Cancer Institute-sponsored Cooperative Prostate Tissue Resource (CPCTR), The specimens were taken from individuals who had a prostatectomy, approximately half who had no recurrence and half who did.
The instrument was programmed to scan microscope slides containing 320–360 individual cores. The resulting SLIM image contained rich information about tissue morphology, with the glandular epithelium and stroma structures clearly resolved. This allowed the investigators to interrogate scattering changes specific to prostate stroma.
Results suggested that SLIM showed promise in assisting pathologists to improve prediction of prostate cancer recurrence. The data revealed that a lower value of anisotropy corresponded to a higher risk for recurrence, meaning that the stroma adjoining the glands of recurrent patients was more fractionated than in non-recurrent patients. Anisotropy is the property of being directionally dependent, as opposed to isotropy, which implies identical properties in all directions. It can be defined as a difference, when measured along different axes, in a material's physical or mechanical properties.
"For every 20 surgery procedures to take out the prostate, it is estimated that only one life is saved," said senior author Dr. Gabriel Popescu, associate professor of electrical and computer engineering at the University of Illinois. "For the other 19 people, they would be better left alone, because with removing the prostate, the quality of life goes down dramatically. So if you had a tool that could tell which patient will actually be more likely to have a bad outcome, then you could more aggressively treat that case."
"What SLIM is very good at is to make invisible objects visible with nanoscale sensitivity," said Dr. Popescu. "So we pick these structural details without the need for staining, which can introduce new variables into the specimen. Our dream is for everyone to have SLIM capabilities in their labs. One can imagine that a SLIM-based tissue imager will scan biopsies in a clinic and, paired with software that is intelligent enough to look for these specific markers, will provide the pathologist with valuable new information. This additional information will translate into more accurate diagnosis and prognosis."
The paper describing the use of SLIM to predict prostate cancer recurrence was published in the May 15, 2015, online edition of the journal Scientific Reports.
Related Links:
University of Illinois
The method is called spatial light interference microscopy or SLIM. SLIM uses a commercial phase contrast microscope and white light illumination, resulting in nanometer scale sensitivity to optical path-length shifts. In essence, SLIM combines phase contrast microscopy with holography.
Investigators at the University of Illinois (Urbana, USA) have introduced a new instrument for SLIM imaging. Their real-time fast SLIM technique could image at a maximum rate of 50 frames per second and provided real-time quantitative phase images at 12.5 frames per second. They were able to achieve this fast rate by combining rapid LCPM (linear pulse-code modulation) and a fast sCMOS camera. In addition, they developed the software to perform phase reconstruction and display the quantitative phase images in real-time.
In the current study, the investigators used the SLIM technique to examine 181 tissue samples obtained from the [US] National Cancer Institute-sponsored Cooperative Prostate Tissue Resource (CPCTR), The specimens were taken from individuals who had a prostatectomy, approximately half who had no recurrence and half who did.
The instrument was programmed to scan microscope slides containing 320–360 individual cores. The resulting SLIM image contained rich information about tissue morphology, with the glandular epithelium and stroma structures clearly resolved. This allowed the investigators to interrogate scattering changes specific to prostate stroma.
Results suggested that SLIM showed promise in assisting pathologists to improve prediction of prostate cancer recurrence. The data revealed that a lower value of anisotropy corresponded to a higher risk for recurrence, meaning that the stroma adjoining the glands of recurrent patients was more fractionated than in non-recurrent patients. Anisotropy is the property of being directionally dependent, as opposed to isotropy, which implies identical properties in all directions. It can be defined as a difference, when measured along different axes, in a material's physical or mechanical properties.
"For every 20 surgery procedures to take out the prostate, it is estimated that only one life is saved," said senior author Dr. Gabriel Popescu, associate professor of electrical and computer engineering at the University of Illinois. "For the other 19 people, they would be better left alone, because with removing the prostate, the quality of life goes down dramatically. So if you had a tool that could tell which patient will actually be more likely to have a bad outcome, then you could more aggressively treat that case."
"What SLIM is very good at is to make invisible objects visible with nanoscale sensitivity," said Dr. Popescu. "So we pick these structural details without the need for staining, which can introduce new variables into the specimen. Our dream is for everyone to have SLIM capabilities in their labs. One can imagine that a SLIM-based tissue imager will scan biopsies in a clinic and, paired with software that is intelligent enough to look for these specific markers, will provide the pathologist with valuable new information. This additional information will translate into more accurate diagnosis and prognosis."
The paper describing the use of SLIM to predict prostate cancer recurrence was published in the May 15, 2015, online edition of the journal Scientific Reports.
Related Links:
University of Illinois
Latest Pathology News
- AI Tool Simultaneously Identifies Genetic Mutations and Disease Type
- Rapid Low-Cost Tests Can Prevent Child Deaths from Contaminated Medicinal Syrups
- Tumor Signals in Saliva and Blood Enable Non-Invasive Monitoring of Head and Neck Cancer
- Common Health Issues Can Influence New Blood Tests for Alzheimer’s Disease
- Blood Test Formula Identifies Chronic Liver Disease Patients with Higher Cancer Risk
- Tunable Cell-Sorting Device Holds Potential for Multiple Biomedical Applications
- AI Tool Outperforms Doctors in Spotting Blood Cell Abnormalities
- AI Tool Rapidly Analyzes Complex Cancer Images for Personalized Treatment
- Diagnostic Technology Performs Rapid Biofluid Analysis Using Single Droplet
- Novel Technology Tracks Hidden Cancer Cells Faster
- AI Tool Improves Breast Cancer Detection
- AI Tool Predicts Treatment Success in Rectal Cancer Patients
- Blood Test and Sputum Analysis Predict Acute COPD Exacerbation
- AI Tool to Transform Skin Cancer Detection with Near-Perfect Accuracy
- Unique Immune Signatures Distinguish Rare Autoimmune Condition from Multiple Sclerosis
- Simple Optical Microscopy Method Reveals Hidden Structures in Remarkable Detail
Channels
Clinical Chemistry
view channel
Compact Raman Imaging System Detects Subtle Tumor Signals
Accurate cancer diagnosis often depends on labor-intensive tissue staining and expert pathological review, which can delay results and limit access to rapid screening. These conventional methods also make... Read more
Noninvasive Blood-Glucose Monitoring to Replace Finger Pricks for Diabetics
People with diabetes often need to measure their blood glucose multiple times a day, most commonly through finger-prick blood tests or implanted sensors. These methods can be painful, inconvenient, and... Read moreMolecular Diagnostics
view channel
Neuron-Derived Extracellular Vesicles Could Improve Alzheimer’s Diagnosis
Alzheimer’s disease is becoming increasingly common as global populations age, yet effective treatments for advanced stages remain limited. Early detection is therefore critical, but current diagnostic... Read more
Sample Prep Instrument to Empower Decentralized PCR Testing for Tuberculosis
Tuberculosis remains the deadliest infectious disease worldwide despite being both treatable and curable when diagnosed early. A major barrier to timely diagnosis is that PCR-based TB testing is still... Read more
Endometriosis Blood Test Could Replace Invasive Laparoscopic Diagnosis
Endometriosis affects an estimated 1 in 10 women globally, yet diagnosis can take 7 to 10 years on average due to the invasive nature of laparoscopy and lack of accurate, non-invasive tests.... Read more
World's First NGS-Based Diagnostic Platform Fully Automates Sample-To-Result Process Within Single Device
Rapid point-of-need diagnostics are of critical need, especially in the areas of infectious disease and cancer testing and monitoring. Now, a direct-from-specimen platform that performs genomic analysis... Read moreHematology
view channel
MRD Tests Could Predict Survival in Leukemia Patients
Acute myeloid leukemia is an aggressive blood cancer that disrupts normal blood cell production and often relapses even after intensive treatment. Clinicians currently lack early, reliable markers to predict... Read more
Platelet Activity Blood Test in Middle Age Could Identify Early Alzheimer’s Risk
Early detection of Alzheimer’s disease remains one of the biggest unmet needs in neurology, particularly because the biological changes underlying the disorder begin decades before memory symptoms appear.... Read more
Microvesicles Measurement Could Detect Vascular Injury in Sickle Cell Disease Patients
Assessing disease severity in sickle cell disease (SCD) remains challenging, especially when trying to predict hemolysis, vascular injury, and risk of complications such as vaso-occlusive crises.... Read more
ADLM’s New Coagulation Testing Guidance to Improve Care for Patients on Blood Thinners
Direct oral anticoagulants (DOACs) are one of the most common types of blood thinners. Patients take them to prevent a host of complications that could arise from blood clotting, including stroke, deep... Read moreImmunology
view channel
Ultrasensitive Liquid Biopsy Demonstrates Efficacy in Predicting Immunotherapy Response
Immunotherapy has transformed cancer treatment, but only a small proportion of patients experience lasting benefit, with response rates often remaining between 10% and 20%. Clinicians currently lack reliable... Read more
Blood Test Could Identify Colon Cancer Patients to Benefit from NSAIDs
Colon cancer remains a major cause of cancer-related illness, with many patients facing relapse even after surgery and chemotherapy. Up to 40% of people with stage III disease experience recurrence, highlighting... Read moreMicrobiology
view channel
New UTI Diagnosis Method Delivers Antibiotic Resistance Results 24 Hours Earlier
Urinary tract infections affect around 152 million people every year, making them one of the most common bacterial infections worldwide. In routine medical practice, diagnosis often relies on rapid urine... Read more
Breakthroughs in Microbial Analysis to Enhance Disease Prediction
Microorganisms shape human health, ecosystems, and the planet’s climate, yet identifying them and understanding how they are related remains a major scientific challenge. Even with modern DNA sequencing,... Read moreTechnology
view channel
AI Predicts Colorectal Cancer Survival Using Clinical and Molecular Features
Colorectal cancer is one of the most common and deadly cancers worldwide, and accurately predicting patient survival remains a major clinical challenge. Traditional prognostic tools often rely on either... Read more
Diagnostic Chip Monitors Chemotherapy Effectiveness for Brain Cancer
Glioblastoma is one of the most aggressive and fatal brain cancers, with most patients surviving less than two years after diagnosis. Treatment is particularly challenging because the tumor infiltrates... Read moreIndustry
view channel
BD and Penn Institute Collaborate to Advance Immunotherapy through Flow Cytometry
BD (Becton, Dickinson and Company, Franklin Lakes, NJ, USA) has entered into a strategic collaboration with the Institute for Immunology and Immune Health (I3H, Philadelphia, PA, USA) at the University... Read more







