Date Published: February 19, 2019
Publisher: Springer International Publishing
Author(s): Nicole Wake, Andrew B. Rosenkrantz, Richard Huang, Katalina U. Park, James S. Wysock, Samir S. Taneja, William C. Huang, Daniel K. Sodickson, Hersh Chandarana.
Patient-specific 3D models are being used increasingly in medicine for many applications including surgical planning, procedure rehearsal, trainee education, and patient education. To date, experiences on the use of 3D models to facilitate patient understanding of their disease and surgical plan are limited. The purpose of this study was to investigate in the context of renal and prostate cancer the impact of using 3D printed and augmented reality models for patient education.
Patients with MRI-visible prostate cancer undergoing either robotic assisted radical prostatectomy or focal ablative therapy or patients with renal masses undergoing partial nephrectomy were prospectively enrolled in this IRB approved study (n = 200). Patients underwent routine clinical imaging protocols and were randomized to receive pre-operative planning with imaging alone or imaging plus a patient-specific 3D model which was either 3D printed, visualized in AR, or viewed in 3D on a 2D computer monitor. 3D uro-oncologic models were created from the medical imaging data. A 5-point Likert scale survey was administered to patients prior to the surgical procedure to determine understanding of the cancer and treatment plan. If randomized to receive a pre-operative 3D model, the survey was completed twice, before and after viewing the 3D model. In addition, the cohort that received 3D models completed additional questions to compare usefulness of the different forms of visualization of the 3D models. Survey responses for each of the 3D model groups were compared using the Mann-Whitney and Wilcoxan rank-sum tests.
All 200 patients completed the survey after reviewing their cases with their surgeons using imaging only. 127 patients completed the 5-point Likert scale survey regarding understanding of disease and surgical procedure twice, once with imaging and again after reviewing imaging plus a 3D model. Patients had a greater understanding using 3D printed models versus imaging for all measures including comprehension of disease, cancer size, cancer location, treatment plan, and the comfort level regarding the treatment plan (range 4.60–4.78/5 vs. 4.06–4.49/5, p < 0.05). All types of patient-specific 3D models were reported to be valuable for patient education. Out of the three advanced imaging methods, the 3D printed models helped patients to have the greatest understanding of their anatomy, disease, tumor characteristics, and surgical procedure.
Navigating a cancer diagnosis and making decisions about cancer treatment can be challenging for many patients. Individual treatment plans vary and depend on the type of cancer, stage of the disease, and other comorbidities. Recently, there has been a clear move towards shared decision making and patients want to assume an increasing role in medical decision making, with 92.5% of men with newly diagnosed prostate cancer wanting to play either an active or a collaborative role in decision making with their physician .
Patients with magnetic resonance imaging (MRI)-visible prostate cancer (PI-RADS v2 score ≥ 3) and biopsy confirmed cancer undergoing either robotic assisted radical prostatectomy or focal ablative therapy or patients with renal masses (nephrometry score (NS) ≥ 7, diameter ≥ 4 cm, or polar lesions) undergoing partial nephrectomy were prospectively enrolled in this IRB approved study (n = 200). Of the 200 total patients, 151 had prostate cancer: 104 patients with 146 lesions underwent prostatectomy and 47 patients with 69 lesions underwent focal ablative therapy. The breakdown of PI-RADS scores was as follows: PI-RADS 2 = 28, PI-RADS 3 = 68, PI-RADS 4 = 82, PI-RADS 5 = 28, and no PI-RADS could be assigned in 9 cases with biopsy confirmed prostate cancer in the region of the MR defined lesion. There were 49 patients with kidney cancer (29 males and 20 females) with the following NS breakdown: NS 4 = 2, NS 5 = 2, NS 6 = 7, NS 7 = 14, NS 8 = 13, NS 9 = 8, NS 10 = 3. The mean age and range was 63.64 ± 8.22 years. Patients underwent routine clinical imaging protocols and were randomized to receive pre-operative planning with imaging alone or imaging plus a patient-specific 3D model which was either 3D printed, visualized in AR, or viewed in 3D on a 2D computer monitor.
All 200 patients completed the survey after reviewing their cases with their surgeons using imaging only. 127 patients completed the 5-point Likert scale survey regarding understanding of disease and surgical procedure twice, once with imaging and again after reviewing imaging plus a 3D model. Overall, the 3D printed models performed better than imaging, 3D computer models, and AR models (Table 3). Patients had a greater understanding using 3D printed models versus imaging for all measures including comprehension of disease (4.70 ± 0.54, p < 0.001), cancer size (4.60 ± 0.54, p < 0.001), cancer location (4.75 ± 0.50, p < 0.001), treatment plan (4.78 ± 0.45, p < 0.001), and comfort level regarding the treatment plan (4.69 ± 0.57, p = 0.013). Patients also had a greater understanding of their anatomy and disease as well as improved comfort level using 3D printed models as compared to AR models (range 4.60–4.70/5 vs 3.50–4.23/5, p < 0.05). There was no improvement in understanding for any of the measures for the AR model group as compared to the imaging group or the 3D printed versus computer model groups.Table 3Likert scale survey responses for understanding of cancer/disease, tumor size, tumor location, treatment plan, and comfort level. Bold values with a * next to the value indicates statistically significant improvement with the 3D model (p < 0.05)Imaging (n = 200)3D Printed Model (n = 55)AR Model (n = 26)3D Computer Model (n = 46)Disease4.28 ± 0.804.70 ± 0.54*4.23 ± 0.594.50 ± 0.66Cancer Size4.06 ± 0.914.60 ± 0.54*4.04 ± 0.924.48 ± 0.59*Cancer Location4.34 ± 0.694.75 ± 0.50*4.23 ± 0.824.65 ± 0.48*Treatment Plan4.49 ± 0.624.78 ± 0.45*4.35 ± 0.854.70 ± 0.47*Comfort Level4.40 ± 0.764.69 ± 0.57*3.50 ± 1.97*4.53 ± 0.61 At our institution, consultations for patients with kidney and prostate malignancies are routinely performed using imaging only to explain the disease and surgical procedure. We have previously demonstrated that patient-specific 3D printed models of renal malignancies influence pre-surgical planning decisions . In addition, 3D printed models can facilitate nerve-sparing prostatectomy . Source: http://doi.org/10.1186/s41205-019-0041-3