Philips introduces ‘big-bore’ PET/CT
In a bid to extend radiation oncology applications, engineers at Philips Healthcare have widened the bore of the company’s premium Gemini TF PET/CT scanner to create the industry’s first big-bore hybrid. Priced north of $2 million, the Gemini TF Big Bore is scheduled to begin shipping next year. Philips is showcasing the Big Bore this week on the RSNA exhibit floor, and beta testing will begin at the University of Pennsylvania Hospital in the next several months.
In a bid to extend radiation oncology applications, engineers at Philips Healthcare have widened the bore of the company's premium Gemini TF PET/CT scanner to create the industry's first big-bore hybrid. Priced north of $2 million, the Gemini TF Big Bore is scheduled to begin shipping next year. Philips is showcasing the Big Bore this week on the RSNA exhibit floor, and beta testing will begin at the University of Pennsylvania Hospital in the next several months.
Philips' proprietary TruFlight time-of-flight technology, which characterizes the Gemini TF, allowed the company to widen the bore from 71.7 cm to 85 cm without compromising image quality or scan time, according to the company. The new system offers a combination of accessories and localization devices designed specifically for use in radiation oncology. Its large bore meets treatment planning requirements for patients who must be scanned in extended positions, as in cases of breast and colorectal scanning, by allowing them to be positioned for simulation in the same manner as they would be positioned to receive therapy.
Precise measurements are particularly important in radiation treatment planning. Toward that end, the company has integrated a more rigid table than the one used on the conventional Gemini PET/CT, providing very precise localization based on rigid patient framing.
What is the Best Use of AI in CT Lung Cancer Screening?
April 18th 2025In comparison to radiologist assessment, the use of AI to pre-screen patients with low-dose CT lung cancer screening provided a 12 percent reduction in mean interpretation time with a slight increase in specificity and a slight decrease in the recall rate, according to new research.
The Reading Room: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.
Can CT-Based AI Radiomics Enhance Prediction of Recurrence-Free Survival for Non-Metastatic ccRCC?
April 14th 2025In comparison to a model based on clinicopathological risk factors, a CT radiomics-based machine learning model offered greater than a 10 percent higher AUC for predicting five-year recurrence-free survival in patients with non-metastatic clear cell renal cell carcinoma (ccRCC).
Could Lymph Node Distribution Patterns on CT Improve Staging for Colon Cancer?
April 11th 2025For patients with microsatellite instability-high colon cancer, distribution-based clinical lymph node staging (dCN) with computed tomography (CT) offered nearly double the accuracy rate of clinical lymph node staging in a recent study.
