3D Printed Models May Best CT/MRI for Renal Tumor Localization

By Marilynn Larkin

July 08, 2019

NEW YORK (Reuters Health) - Experienced surgeons had trouble identifying the locations of kidney tumors on 3-dimensional models based only on information from typical 2-dimensional preoperative imaging, a new study found. The authors say 3D models could improve surgical planning.

"Typically, when planning for surgical procedures, surgeons rely on CT and MR imaging data," Dr. Nicole Wake of Montefiore Medical Center in New York City told Reuters Health by email. "However, the way that each surgeon mentally translates this data into 3D may not always accurately reflect the true 3D anatomy. In this study, we show how renal tumor localization is significantly improved by using 3D printed models as compared to conventional CT or MR imaging."

Dr. Wake and colleagues randomly selected 20 patients with renal masses for the study, including 14 with preoperative MRIs and six with preoperative CTs. Seven of the 20 patients had preoperative 3D printed models created.

Three surgeons reviewed the CT/MRI data, and using computer-aided design software, they translated the renal tumor to the position on the kidney that corresponded with the image interpretation.

The tumor location determined by each surgeon was compared to the true renal mass location. The Dice Similarity Coefficient (DSC) was calculated to evaluate spatial overlap accuracy. Correlation effects sizes for DSC are 0-0.19 (very weak), 0.2-0.39 (weak), 0.4-0.59 (moderate), 0.6-0.79 (strong), and 0.8-1.0 (very strong).

The process was repeated for the subset of patients with a 3D printed model.

As reported online June 21 in Urology, the mean DSC was 0.243 for the entire cohort (three surgeons analyzing 20 images each). In 16/60 cases (26.67%), no overlap was seen between the actual renal tumor and the renal tumor as identified by the surgeons.

Excluding the cases with no overlap, the overall mean DSC improved to 0.329.

For the seven cases reviewed again in a different setting with a 3D printed model, the mean DSC improved from 0.277 using imaging only to 0.796 with the 3D printed model.

"Cognitive renal tumor localization based on CT and MRI data was poor," the authors state. "This study demonstrates that experienced surgeons cannot always translate 2D imaging studies into 3D. Furthermore, 3D printed models can improve tumor localization and potentially assist with appropriate surgical approach."

"3D printing is being utilized in our respective institutions," Dr. Wake said. "It can be used to facilitate surgeries for all types of cancers and other complex surgical procedures."

CPT Category III codes for 3D printed anatomic models and guides (0559T, 0560T, 0561T and 0562T) were released on July 1st. (https://go.cms.gov/2XIBzx2)

"It will be important for point-of-care facilities to utilize these codes," Dr. Wake said. "In addition, we need to acquire more quantitative data demonstrating the added value of 3D printed models in clinical care."

Oncologist Dr. Stephen Jackman, Associate Professor of Urology at the University of Pittsburgh School of Medicine, commented by email, "The big question is, does this translate to some advantage during surgery? It is intuitive that better knowledge would help speed the process of finding the tumor but this has yet to be proven."

"At UPMC, for the last three years we have been using 3D printed models of the kidney that include anatomic detail of the kidney, tumor, blood vessels and collecting system (urinary plumbing)," he told Reuters Health. "We have found these useful in facilitating the planning the excision of the tumors as well as reconstruction of the kidney. We are currently studying whether a measurable effect can be proven."

"Some type of 3D imaging, whether a solid 3D printed model or a virtual reality (VR) model, will likely become routine for challenging partial nephrectomy cases," he added. "VR is probably the future of this technology since it is quicker and cheaper than actually printing the model."

SOURCE: http://bit.ly/2XR8fo1

Urology 2019.