X hits on this document





35 / 55




When lung nodules are detected, the next step is to help clinicians determine their clini- cal significance and track findings in follow- up examinations. Current technology, devel- oped by Siemens Corporate Research (SCR) in Princeton, New Jersey, makes it possible to compare two lung scans to see if a suspected nodule has changed over time. “That’s very difficult and time consuming to do without a powerful IT-based function like CAD,” says Gupta. Adds Ingo Schmuecking, M.D., who heads SMS’s marketing activities for the CAD

What happens when we think and when we feel? Here, an ad- vanced MR tomography process shows the structure of nerve paths (see also p. 62).

Group, “Clinicians need to be supported in making the best possible decisions for their patients - every time. This means catching cancers as early as possible and avoiding un- necessary biopsies. We believe that CAD has great potential to help by learning to detect changes as clinical experts do, and by learn- ing to combine multiple parameters in order to increase predictive value.”

Automated Screening of Colon Polyps? Another CAD area in which SMS and SCR have worked closely is virtual colonography. Ac-







cording to the International Agency for Re- search on Cancer, colon cancer is the second leading cancer worldwide. Today, the most advanced medical centers perform colon ex- ams using a technique called “virtual fly- through” (see Pictures of the Future, Spring 2003, p.64), which was pioneered by Siemens Corporate Research.

But like conventional colonography, fly- throughs can miss polyps. With a view to maximizing accuracy, Siemens Medical Solu- tions recently introduced its syngo Colon-

ography with PEV (Polyp Enhanced Viewing) software, the first FDA-cleared second reader product to support CT colonography. As with NEV, PEV uses algorithms based on expert knowledge, as well as machine learning to detect and analyze features known to be as- sociated with polyps. “The sensitivity of this automated tool is extremely high,” say SMS’s Colon CAD Program Manager Luca Bogoni, Ph.D. “In the size range of 6mm and up — the threshold for danger is around 1cm — CAD has an accuracy level in the 90s — which is close to that of an expert.”

This support will be welcomed by radiolo- gists, especially when virtual colonography as a colon cancer screening test becomes widely accepted and procedure volumes increase. “It’s a question of trust and acceptance,” says

Gupta. “PEV has the potential to allow radiol- ogists to concentrate their time on patholo- gies that present tangible health risks.”

Toward Data-Based Diagnostics. Whether a radiologist is looking for breast cancer, lung nodules or polyps in the colon, detection is al- ways followed by a critical step: characteriza- tion and diagnosis. But determining whether an anomaly may be cancer requires years of practice. Here, even experts rely on second opinions, comparative studies, lab tests and biopsies for answers. Considering the im- mense cost of such efforts, the U.S.’s National Cancer Institute (NCI) and National Institutes

of Health (NIH) recently launched a far-reach- ing IT initiative for health informatics. An im- portant part of this is a large-scale database to support the development of knowledge- driven diagnostic systems, a project that is strongly supported by SMS. “By pooling the combined expertise of NCI, leading medical institutions and industry, this approach pro- vides uniform and accurate criteria for the de- velopment of next-generation diagnostic sys- tems,” says Marcos Salganicoff, Ph.D., SMS’ Lung CAD Program Manager. “Active partici- pation in this project will ensure that Siemens is in the forefront of innovation in knowledge- driven medical decision support.”

At Siemens, teams specialized in pattern recognition, image processing and data min- ing are involved in translating early versions

of such databases into algorithms that will be the basis of learning systems. “Once the un- derlying knowledge from thousands of cases has been distilled into algorithms, systems based on the latest machine learning con- cepts will be able to examine a new case, compare it to a knowledge base, and provide clinical decision support via a probability- based determination as to whether a nodule, polyp or microcalcification is cancerous,” says SMS’s Schmuecking.

When will the first computer-aided charac- terization systems become available? No one knows for sure. But with SMS’s purchase of Jerusalem, Israel-based CADVision Medical

Technologies in 2004, Siemens took a major step in the direction of providing powerful di- agnostic support for physicians in evaluating the 90 million screening mammograms per- formed each year in the U.S. and Europe. “Mammography was the first application for which CAD was introduced, and it may very well be one of the first where we will see clas- sification technologies,” says Gupta.

Another major area of computer-aided de- tection and classification is cardiac ultra- sound. Here, patented algorithms developed at SCR and SMS make it possible to automati- cally find and track the outlines of a moving heart — something extremely difficult to do with the human eye. The tracking technique is based on the characteristics that top cardi- ologists look for. “We then teach a program to

look for the same things,” explains Sriram Krishnan, Ph.D., Cardiac CAD Ultrasound Pro- gram Manager at SMS. This helps specialists to quantify the change in volume between systole and diastole (ejection fraction), which is a crucial measure of cardiac health.

Even in CT and MR — diagnostic modali- ties known for their sharp images — ad- vances in information technology are on the way that will make diagnostic decisions and

Saving Hearts with Image Fusion. Not only is IT transforming diagnostics and med- ical management, it is also radically changing what happens in the operating room (see p. 70). Take the treatment of cardiac arrhyth- mias, for instance. Until recently, a cure for this potentially life-threatening condition re- quired open heart surgery. Specialized heart centers have been developing a minimally in- vasive treatment alternative, that involves ad-

Computers are providing second opinions to help detect intestinal, lung and breast cancer.

vancing an ablation catheter from a small in- cision at the patient’s groin up into the heart. Correct navigation of the catheter in the heart, however, is a very difficult and lengthy procedure.

But now, thanks to advances in image mapping and registration technologies pio- neered by Siemens Corporate Research, the catheter procedure can be conducted much more efficiently and safely. “The key to pre- cise catheter navigation is that we can seam- lessly map the catheter into a pre-operative CT image, which shows the patient’s anatomy with a resolution of under 1mm,” explains James Williams, Ph.D., who heads SCR’s Imag- ing and Visualization Department. Once the correct anatomical location of the arrhythmia has been pinpointed the ablation catheter, which has a heatable tip, burns the errant tis- sue away. “The procedure is now in clinical use. It is curative, and it has a very high suc- cess rate,” says Williams.

Advanced software is already being used for automated detection of colon polyps in virtual fly-throughs of the intestine (cen- ter image), and in the detection of poten- tial lung nodules (right) in CT data sets.

treatments more precise (see Pictures of the Future, Spring 2003, p.61). For instance, sep- arating the contours of a tumor from sur- rounding tissues is a difficult and time-con- suming task. Yet such information is essential when it comes to planning sensitive proce- dures such as radiation treatment. With this in mind, Prof. Ulrich Lauther, a specialist in mathematical optimization at Siemens Corpo- rate Technology in Munich, has developed a program that could cut the time needed to determine the contours of a tumor from hours to minutes.

The importance of information technology in the operating room will continue to grow. Earlier this year, SCR and Johns Hopkins Uni- versity in Baltimore, Maryland began explor- ing processing and alignment techniques that could automate the reconstruction of images produced by magnetic resonance (MR) scan- ning. Given that MR is radiation-free, this could lead to safe, real time, high resolution imaging during the course of an entire opera- tion. Advanced image processing will in turn make it possible to perfectly visualize minus- cule catheters and other instruments as they are guided to a target. “In ten years,” predicts Williams, “the technology will have reached the point that we will be able to perform what today requires major surgery, such as mitral valve replacement in the heart, using only s p e c i a l i z e d c a t h e t e r s a n d r e a l - t i m e m a g n e t i c A r t h u r F P e a s e resonance ”

Pictures of the Future | Fall 2005


Document info
Document views209
Page views209
Page last viewedThu Jan 19 07:53:37 UTC 2017