Imaging in Interventional Radiology: 2043 and Beyond

Abstract

Since its inception in the early 20th century, interventional radiology (IR) has evolved tremendously and is now a distinct clinical discipline with its own training pathway. The arsenal of modalities at work in IR includes x-ray radiography and fluoroscopy, CT, MRI, US, and molecular and multimodality imaging within hybrid interventional environments. This article briefly reviews the major developments in imaging technology in IR over the past century, summarizes technologies now representative of the standard of care, and reflects on emerging advances in imaging technology that could shape the field in the century ahead. The role of emergent imaging technologies in enabling high-precision interventions is also briefly reviewed, including image-guided ablative therapies.

Graphical abstract

Figure 1:

Volumetric fusion image of MRI, CT, and cone-beam CT digital subtraction angiography overlaid on real-time fluoroscopy for interventional guidance shows renal cell metastasis in the T10 vertebra.

Figure 2:

Three-dimensional–two-dimensional registration and overlay of a tumor (L3/L4 renal cell tumor) segmented from MRI, registered via cone-beam CT, and overlaid on real-time fluoroscopy. Prior kyphoplasty is also evident.

Figure 3:

Image shows falcotentorial meningioma with MRI tumor segmentation and image fusion with cone-beam CT digital subtraction angiography and cone-beam CT diameter spherical volume for preoperative mapping and assessment of the eloquence of venous structures. Occlusions of the straight sinus and vein of Galen are depicted.

Figure 4:

Image shows recurrent superior falcine meningioma with MRI tumor segmentation and image fusion with cone-beam CT digital subtraction angiography and cone-beam CT diameter spherical volume for preoperative mapping and assessment of the eloquence of venous structures. Occlusions of the sagittal sinus and middle meningeal tumor supply are depicted.

Figure 5:

For liver tumor ablation, multimodality images are segmented using deep learning–based tools and deformably registered to resolve geometric alignment in each phase of planning, treatment, and follow-up. (A) Pretreatment contrast-enhanced CT scan obtained at the start of the thermal ablation procedure with (B) three-dimensional (3D) visualization. Automatically segmented structures include the liver (cyan), tumor (green), and vasculature (purple). (C) Deformable image registration maps the tumor onto a noncontrast CT scan acquired for image guidance, showing the needle in position to ensure targeting accuracy. (D) Visualization of automatically segmented structures according to the color legend in A. Finally, deformable image registration maps the tumor onto posttreatment contrast-enhanced CT scan for visualization relative to the ablation margin (orange). Follow-up (E) MRI and (F) contrast-enhanced CT scans are shown with the liver segmented and tumor mapped with use of deformable image registration. A = anterior, P = posterior. Image series from the Cover-All Study (ClinicalTrials.gov identifier NCT04083378) for liver tumor ablation (courtesy of Bruno Odisio, MD, The University of Texas MD Anderson Cancer Center, principal investigator of the Cover-All Study).

Figure 6:

A view of the future in interventional radiology. With multimodality image guidance and robotic assistance, the radiologist approaches the target in a streamlined manner with minimal injury to normal tissues. Real-time deformable image registration accounts for tissue changes, visualized by the radiologist with use of an augmented reality (AR) viewer that maintains visual field on the patient and situational awareness throughout the interventional suite. Targeted therapy is delivered under image guidance with real-time, quantitative feedback measuring the distribution of therapeutic effect and validation of treatment delivery.