Newsroom

SmartBrief interviews Lara^®-QI Project presenters Dr. David Townsend and Dr. Jackson Kiser .

The Triangle Business Journal notes that the Lara^®-QI project has been completed and presented at SNMMI (subscription required).

Lucerno Dynamics earns ISO 13485:2016 certification

“The quality and accuracy of the PET/CT image is important to oncologists and their patients. Our center’s 13.3% infiltration rate was similar to published rates. Using new technology led to significant and sustainable improvement in PET/CT radiotracer injections with minimal patient/procedure disruptions. Since a proper injection is critical to the PET/Ct image, ongoing monitoring of the injection is essential.” Poster

The Uptake newsletter of the SNMMI Technologist Section publishes an article written by two technologists that participated in Lucerno’s multi-center quality improvement project Lara^®-QI that describes their experiences as front-line users of Lara^® System.

The journal Frontiers in Medicine, Nuclear Medicine section, publishes a case report from Carilion Clinic highlighting the impact of an FDG PET/CT radiotracer injection infiltration on patient management.

“Dose extravasation in PET/CT has the potential of reducing image quality and affecting accurate SUV quantification. These case studies demonstrate how the ability to accurately identify, measure and implement a process improvement program to reduce dose extravasations can ultimately have a positive impact on patient outcomes in PET/CT.” Full Text

“Analysis of time activity curves from both detectors indicate that use of these detectors can provide specific information about a particular radioactive sphere infusion procedure. Data can be used to optimize techniques for a given Y90 therapy device or used to train radiology residents on proper technique. This method can also provide near real-time confirmation of a successful complete delivery of the desired patient dose which may also maximize therapy efficacy and improve patient outcomes.”
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“A combination of deep learning techniques and TACs from external sensors is a novel approach which can play a significant role in classifying infiltrated injections. With the date constraint factor, the highest accuracy achieved was in the range of 70%. However, the system could identify the good injections with 85% accuracy and with 90% accuracy when using only the original data. Future work aims at training the network with sufficient date with improved mode to achieve better accuracy.” Full Text

“Since infiltrations can resolve during uptake and as the standard imaging FOV does not always capture the injection site, many infiltrations may go undetected. Infiltrations result in underestimated SUVs that can impact patient care emphasizing that it is important to monitor injection quality. Thus, identifying contributing factors associated with infiltrations may help stimulate quality improvements, reduce infiltration rates, and potentially improve patient care.”
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Lucerno Dynamics second patent issued by USPTO.

“Even when the injection site was out of the field of view, the time–activity curves could still detect and characterize infiltration. Our initial experience showed that the quality assurance information obtained from the device helped reduce the rate and severity of infiltration.” Full Text