Enhanced Treatment Assessment for Liver Cancer Using New Imaging Analysis Technique
By MedImaging International staff writers Posted on 10 Jan 2016 |

Image: Liver images from before, and after treatment. The bottom-right image shows that less cancer is visible after treatment (Photo courtesy of RSNA).
A study presented at the annual Radiological Society of North America (RSNA 2015) meeting in Chicago USA has shown that a novel MRI analysis technique can significantly speed up the assessment of the effectiveness of liver cancer treatment compared to existing methods.
Hepatocellular Carcinoma (HCC) is the second most deadly cancer worldwide and treatment consists of an image-guided procedure called Transarterial Chemoembolization (TACE). During the procedure chemotherapeutic drugs are delivered to the tumor while at the same time the blood supply to the tumor is blocked. If a patient does not respond to TACE treatment the clinician needs treat them again, or change their therapy, as rapidly as possible. Infiltrative HCC is very difficult to treat after TACE with traditional methods because of the large number of lesions and their ill-defined borders.
The researchers used a new approach developed together with Philips Research North America (Cambridge, MA, USA), called the quantitative European Association for the Study of the Liver (qEASL) technique. The new 3D technology provides whole liver volumetric enhancement quantification on Magnetic Resonance Imaging (MRI) and enables a radiologist to segment and delineate an entire tumor in 15–20 seconds in a semi-automated process. The researchers assessed 68 liver cancer patients with infiltrative HCC, using the qEASL technique, before their first TACE procedure, and again one month after the procedure. The researchers measured treatment response, and predicted survival, and segmented the entire liver of the patients while identifying tumors. The researchers found that responders had an overall survival rate of around 21 months and a mean 57.8% decrease in enhancing volume. Non-responders had a survival rate of 6.8 months and a 19.1% increase enhancing volume on average.
According to the researchers, the qEASL approach can also be used with modalities such as cone-beam Computed Tomography (CT), Multidetector CT (MDCT), and Single-Photon Emission Computed Tomography (SPECT), and has also been validated for benign brain, and uterine lesions, and might also be applicable for systemic therapy.
Coauthor of the study, Julius Chapiro, MD, Yale University School of Medicine, said, "In clinical oncology, it is very challenging to assess tumor response to treatment. Up until now, we could measure the extent of tumor diameter or uptake with manual tools like the caliper on the screen, which are highly unreliable due to reader bias. The radiologist can segment the entire tumor with the assistance of the computer. It's a work-flow efficient, semi-automated process that takes 15 to 20 seconds to segment and allows you to delineate the tumor in 3D. The findings show that quantitative tumor enhancement is possible with 3-D qEASL and can predict survival after TACE for infiltrative and multifocal HCC. qEASL is not a diagnostic tool but rather a means of comparing differences before and after treatment to identify non-responders. The earlier the non-responders are identified and treated, the better their outcomes."
Related Links:
Philips Research North America
Hepatocellular Carcinoma (HCC) is the second most deadly cancer worldwide and treatment consists of an image-guided procedure called Transarterial Chemoembolization (TACE). During the procedure chemotherapeutic drugs are delivered to the tumor while at the same time the blood supply to the tumor is blocked. If a patient does not respond to TACE treatment the clinician needs treat them again, or change their therapy, as rapidly as possible. Infiltrative HCC is very difficult to treat after TACE with traditional methods because of the large number of lesions and their ill-defined borders.
The researchers used a new approach developed together with Philips Research North America (Cambridge, MA, USA), called the quantitative European Association for the Study of the Liver (qEASL) technique. The new 3D technology provides whole liver volumetric enhancement quantification on Magnetic Resonance Imaging (MRI) and enables a radiologist to segment and delineate an entire tumor in 15–20 seconds in a semi-automated process. The researchers assessed 68 liver cancer patients with infiltrative HCC, using the qEASL technique, before their first TACE procedure, and again one month after the procedure. The researchers measured treatment response, and predicted survival, and segmented the entire liver of the patients while identifying tumors. The researchers found that responders had an overall survival rate of around 21 months and a mean 57.8% decrease in enhancing volume. Non-responders had a survival rate of 6.8 months and a 19.1% increase enhancing volume on average.
According to the researchers, the qEASL approach can also be used with modalities such as cone-beam Computed Tomography (CT), Multidetector CT (MDCT), and Single-Photon Emission Computed Tomography (SPECT), and has also been validated for benign brain, and uterine lesions, and might also be applicable for systemic therapy.
Coauthor of the study, Julius Chapiro, MD, Yale University School of Medicine, said, "In clinical oncology, it is very challenging to assess tumor response to treatment. Up until now, we could measure the extent of tumor diameter or uptake with manual tools like the caliper on the screen, which are highly unreliable due to reader bias. The radiologist can segment the entire tumor with the assistance of the computer. It's a work-flow efficient, semi-automated process that takes 15 to 20 seconds to segment and allows you to delineate the tumor in 3D. The findings show that quantitative tumor enhancement is possible with 3-D qEASL and can predict survival after TACE for infiltrative and multifocal HCC. qEASL is not a diagnostic tool but rather a means of comparing differences before and after treatment to identify non-responders. The earlier the non-responders are identified and treated, the better their outcomes."
Related Links:
Philips Research North America
Latest Nuclear Medicine News
- Novel Radiolabeled Antibody Improves Diagnosis and Treatment of Solid Tumors
- Novel PET Imaging Approach Offers Never-Before-Seen View of Neuroinflammation
- Novel Radiotracer Identifies Biomarker for Triple-Negative Breast Cancer
- Innovative PET Imaging Technique to Help Diagnose Neurodegeneration
- New Molecular Imaging Test to Improve Lung Cancer Diagnosis
- Novel PET Technique Visualizes Spinal Cord Injuries to Predict Recovery
- Next-Gen Tau Radiotracers Outperform FDA-Approved Imaging Agents in Detecting Alzheimer’s
- Breakthrough Method Detects Inflammation in Body Using PET Imaging
- Advanced Imaging Reveals Hidden Metastases in High-Risk Prostate Cancer Patients
- Combining Advanced Imaging Technologies Offers Breakthrough in Glioblastoma Treatment
- New Molecular Imaging Agent Accurately Identifies Crucial Cancer Biomarker
- New Scans Light Up Aggressive Tumors for Better Treatment
- AI Stroke Brain Scan Readings Twice as Accurate as Current Method
- AI Analysis of PET/CT Images Predicts Side Effects of Immunotherapy in Lung Cancer
- New Imaging Agent to Drive Step-Change for Brain Cancer Imaging
- Portable PET Scanner to Detect Earliest Stages of Alzheimer’s Disease
Channels
Radiography
view channel
AI Improves Early Detection of Interval Breast Cancers
Interval breast cancers, which occur between routine screenings, are easier to treat when detected earlier. Early detection can reduce the need for aggressive treatments and improve the chances of better outcomes.... Read more
World's Largest Class Single Crystal Diamond Radiation Detector Opens New Possibilities for Diagnostic Imaging
Diamonds possess ideal physical properties for radiation detection, such as exceptional thermal and chemical stability along with a quick response time. Made of carbon with an atomic number of six, diamonds... Read moreMRI
view channel
New MRI Technique Reveals True Heart Age to Prevent Attacks and Strokes
Heart disease remains one of the leading causes of death worldwide. Individuals with conditions such as diabetes or obesity often experience accelerated aging of their hearts, sometimes by decades.... Read more
AI Tool Predicts Relapse of Pediatric Brain Cancer from Brain MRI Scans
Many pediatric gliomas are treatable with surgery alone, but relapses can be catastrophic. Predicting which patients are at risk for recurrence remains challenging, leading to frequent follow-ups with... Read more
AI Tool Tracks Effectiveness of Multiple Sclerosis Treatments Using Brain MRI Scans
Multiple sclerosis (MS) is a condition in which the immune system attacks the brain and spinal cord, leading to impairments in movement, sensation, and cognition. Magnetic Resonance Imaging (MRI) markers... Read more
Ultra-Powerful MRI Scans Enable Life-Changing Surgery in Treatment-Resistant Epileptic Patients
Approximately 360,000 individuals in the UK suffer from focal epilepsy, a condition in which seizures spread from one part of the brain. Around a third of these patients experience persistent seizures... Read moreUltrasound
view channel.jpeg)
AI-Powered Lung Ultrasound Outperforms Human Experts in Tuberculosis Diagnosis
Despite global declines in tuberculosis (TB) rates in previous years, the incidence of TB rose by 4.6% from 2020 to 2023. Early screening and rapid diagnosis are essential elements of the World Health... Read more
AI Identifies Heart Valve Disease from Common Imaging Test
Tricuspid regurgitation is a condition where the heart's tricuspid valve does not close completely during contraction, leading to backward blood flow, which can result in heart failure. A new artificial... Read moreNuclear Medicine
view channel
Novel Radiolabeled Antibody Improves Diagnosis and Treatment of Solid Tumors
Interleukin-13 receptor α-2 (IL13Rα2) is a cell surface receptor commonly found in solid tumors such as glioblastoma, melanoma, and breast cancer. It is minimally expressed in normal tissues, making it... Read more
Novel PET Imaging Approach Offers Never-Before-Seen View of Neuroinflammation
COX-2, an enzyme that plays a key role in brain inflammation, can be significantly upregulated by inflammatory stimuli and neuroexcitation. Researchers suggest that COX-2 density in the brain could serve... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read more
Patient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more