Quantitative PET Imaging Technology

Visual analysis of positron emission tomography (PET) scans for non-Hodgkin lymphoma
may be improved by using standardized uptake value in monitoring response to treatment.
Evaluating a patient’s response to chemotherapy for non-Hodgkin lymphoma (NHL) typically involves visual interpretation of scans of cancerous tumors. Researchers have found that measuring a quantitative index – one that reflects the reduction of metabolic activity after chemotherapy first begins – adds accurate information about patients’ responses to first-line chemotherapy, according to a study published in the October 2007 issue of the Journal of Nuclear Medicine. “In our study, we demonstrated that a quantitative assessment of therapeutic
response for patients with diffuse large B-cell lymphoma [DLBCL] is more accurate than visual analysis alone when using the radiotracer FDG [fluorodeoxyglucose] with PET scans,” said Dr. Michel Meignan, professor of nuclear medicine at Henri Mondor Hospital (Creteil, France; www.chu-mondor.aphp.fr). “The ability to predict tumor response early in the course of treatment is very valuable clinically, allowing intensification of treatment in those patients who are unlikely to response to firstline chemotherapy,” he added. “Similarly, treatment could possibly be shortened in those patients who show a favorable response after one or two cycles of chemotherapy, and quantification also may help identify the disease’s transformation from low-grade to aggressive stage. However, visual interpretation of PET scans will always be the first step of analysis and will prevail in case of difficulties to quantify images.”
Diffuse large B-cell lymphoma is a fast-growing, aggressive form of non-Hodgkin lymphoma, a cancer of the body’s lymphatic system. Although there are more than 20 types of NHL, DLBCL is the most common type, making up about 30% of all lymphomas. Ninety-two patients with DLBCL were evaluated before and after two cycles of chemotherapy, and tumor response was assessed visually and by various quantitative parameters, explained Dr. Meignan, co-author of the study. “We found that quantification of tumor FDG uptake [the ratio of tissue radioactivity concentration] can markedly improve the accuracy of FDG PET for prediction of patient outcome.”

Additional research needs to be done, according to Dr. Meignan, stressing that the future monitoring of cancer tumor response will probably include a combination of quantitative analysis
and visual assessment. PET is a powerful molecular imaging procedure that uses very small amounts of radioactive materials that are targeted to specific organs, bones, or tissues. When PET is used to image cancer, a radiopharmaceutical (such as FDG, which includes both glucose and a radionuclide) is injected into a patient. Cancer cells metabolize glucose at higher rates than normal cells, and the radiopharmaceutical is drawn in higher amounts to cancerous regions. PET scanning provides information about the body’s chemistry, metabolic activity, and body function.

Automated RBC blood film classification based on external morphological properties

The examination of peripheral blood films is time consuming, requires highly trained staff and remains subject to significant statistical variance and also a human visual error. In the past decades, efforts have been made to develop automated morphological analysis systems. The automated analysis of blood cell images was first described by Prewitt and Mendlesohn in 1966. Subsequently, other authors showed that digital image processing can be used for automated leucocyte recognition. In this work , we develope an automated blood cells image analysis based on external morphologocal properties of the erythrocyted and leukocytes (RBC and WBC) cells.
The differential counting of blood cells is an important diagnostic tool for successful treatment and management of patients. Additionally, the blood cells smear films need precise histological preperation to gain a good microscopic results. The reliable and efficient analysis of patient samples is therefore crucial. Current automated cell counters are based on laser-light scatter and flow-cytochemical principles, and offer a leukocyte, red cell and platelet count, including a five-part leucocyte differential and a panel for screening red blood cell (erythrocyte) abnormalities. A drawback of automated cell counters is that they offer very limited morphological information and are unable to reliably classify immature and abnormal cells. When abnormalities are suspected in a sample, results are automatically marked. In these cases or when quantification of the pathological cells is needed, a blood film is prepared for microscopical examination and cell classification. The optical microscopically review rate is about 23% of all processed blood samples, resulting in a huge amount of laboratory-intensive work.