London, — 17 June 2008 — Data presented at the recent European Society of Gastrointestinal and Abdominal Radiology (ESGAR) in Istanbul showed that the use of the Medicsight Computer-Aided Detection (CAD) helped radiographers to detect 100% of cancers when examining more than 300 patients in routine primary reporting of virtual colonoscopy (VC).

"These findings are exciting because whilst demand for colorectal cancer investigation is on the rise, there is a shortage of radiologists trained to report VC in many countries," said Dr David Burling, Consultant Radiologist from St Mark's Hospital, London. "If radiographers can be trained to interpret scans more effectively using CAD technology, both radiology teams and patients will benefit, with the ultimate goal of decreasing the incidence and morbidity of colorectal cancer, the second most common cause of death from cancer in Europe."

In the study, 304 patients (61% female) underwent VC as part of routine clinical care.  Examinations were read by two trained radiographers supplemented by CAD as a 'second reader'.  Radiographers recorded colonic abnormalities and interpretation times and proposed one of six different codes for each examination (Categories S0-5: inadequate/normal/6-9 mm polyp/10mm+ polyp/cancer/diverticular stricture).  Findings were compared to that of an experienced radiologist and supplemented by colonoscopic findings if available.

The radiographers, assisted by CAD detected 100% (17/17) of cancers; 72% (21/29) of 10 mm+ polyps and 67% (42/63) of 6-9 mm polyps.  Overall agreement between radiographer and radiologist examinations was good, demonstrating that use of CAD by trained radiographers provides an effective triage strategy in initial patient management following VC.  Notably on retrospective analysis, CAD had actually detected 60% of polyps missed by radiographers.  Therefore, had radiographers accepted these correct CAD annotations, their detection rates would have been 83% and 89% for medium and large polyps respectively.

David Sumner, CEO of Medicsight commented "This study is yet another positive validated outcome for Medicsight ColonCAD.  It further confirms the CAD's accuracy in a user group (Radiographers) that will play a vital role in any colorectal screening programme being implemented in the world today."

For further information:
Medicsight plc
David Sumner, CEO
+44 (0)20 7605 7950
www.medicsight.com

Nomura Code Securities Limited
Juliet Thompson, Managing Director
+44 (0)20 777 61200

Jon Senior
www.nomuracode.com

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Notes to editors

Medicsight PLC is a UK-headquartered, research driven, leading developer of computer-aided detection (CAD) and image analysis software for the medical imaging market. The CAD software automatically highlights suspicious areas on computerised tomography (CT) scans of the colon and lung, helping radiologists to identify measure and analyse potential disease and early indicators of disease. Medicsight's CAD software has been validated using one of the world's largest and most population diverse databases of verified patient CT scan data. Medicsight's ColonCAD™ and LungCAD™ software products are seamlessly integrated with the advanced 3D visualisation workstations of several industry-leading imaging equipment partners.

About Computer-Aided Detection

With increasingly sophisticated radiological imaging hardware such as Multi-Detector CT scanners, radiologists are facing a growing challenge in the amount of detailed patient image data that they must review for each patient examination. Some CT scan examinations generate as many as 1000 images per patient. Review of this data by the radiologist is not only time-consuming but also prone to error due to reader fatigue. CAD software can help the reviewing radiologist by analysing the image data and automatically highlighting suspicious regions of interest for closer inspection. Without CAD software some potential abnormalities or areas of disease may be overlooked. This is critical for diagnosis and the management of patient outcomes as early detection of disease greatly increases the probability of successful treatment and a positive therapeutic outcome.

About Medicsight's CAD software

Medicsight's ColonCAD™ and LungCAD™ software use an advanced CAD algorithm to analyse CT scans of the colon and lung and automatically highlight suspicious areas that may be indicators of disease. CAD may highlight areas easily overlooked by the reviewing radiologist, such as small lesions or regions that are hidden from view behind folds in the colon or normal structures and surrounding tissue in the lung.

Both CAD products seamlessly integrate with the advanced 3D visualisation platforms of industry-leading imaging equipment partners. The integrated systems provide sophisticated image viewing capabilities, including 3D reconstructed image data, with the added advantage of demonstrating automatic CAD findings to assist clinical end users in the detection and analysis of disease. This allows clinical end users to perform either a 'second read', where CAD findings are displayed to the user after completion of an initial review of the CT scan data, or a 'concurrent read' where CAD findings are displayed during the user's initial review of the original CT scan images.

Since inception, Medicsight has developed close and lasting relationships with some of the world's foremost clinicians in product related areas. This provides the Company with a wealth of clinical expertise and dedicated clinical research to support ongoing product development. Medicsight also collaborates with a number of leading academic institutions and clinical research programmes worldwide to develop the Company's comprehensive database of population diverse verified patient CT scan data, thus allowing Medicsight's products to be validated to the highest possible standards.

About adenomas

An adenoma (sometimes known as a polyp) is a slow-growing benign tumour. This is the most common type of early-stage tumour found in the colon and typically projects into the colon from the wall. Adenomas are routinely removed on identification because of their tendency to become malignant.