ASE: Speckle tracking US could replace biopsy to detect transplant rejections
Researchers from South Korea have successfully used 2D ultrasound (US) speckle tracking imaging (STI) to detect heart transplant rejection, according to research presented at the 2008 American Society of Echocardiography (ASE) meeting held in Toronto this week. 

Soo Jin Cho, MD, and colleagues from the Samsung Medical Center in Seoul, South Korea, conducted the study.

“A non-invasive option is a huge benefit to heart transplant patients,” said study author Sang-Chol Lee, MD. "The ultrasound speckle tracking imaging will be an important tool as scientists continue to search for alternatives to invasive right ventricular endomyocardial biopsies.”

Right ventricular endomyocardial biopsy has stood as the gold standard for diagnosing rejection but this method carries risk owing to its invasiveness. The researchers said they believed that STI could have value in early detection for subclinical acute allograft rejection after a heart transplant.

The study involved 17 consecutive heart transplant patients, who underwent a total of 42 routine follow-up endomyocardial biopsies. The researchers obtained conventional echocardiographic images and additional apical images in high-frame rate for STI within two days of each biopsy. They measured peak systolic longitudinal strain (PSLS) of each segment by automated tracking system.
According to the International Society of Heart and Lung Transplantation criteria, 26 biopsies (Group A) had no rejection and 16 biopsies (Group B) had various degrees of rejection.

All echocardiographic exams showed no regional wall motion abnormalities with normal ejection fractions, the investigators said.

Cho and colleagues found that the average PSLS of all segments was reduced in Group B; the average PSLS of basal segments was not different in the two groups; however, those of mid and apical segments were significantly lower in Group B.

The researchers found that the average PSLS of all segments for <-15.8 percent could predict rejection with a sensitivity and specificity of 78 percent.