3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment.

BACKGROUND: The detectability performance of a CT scanner is difficult to precisely quantify when nonlinearities are present in reconstruction. An efficient detectability assessment method that is sensitive to small effects of dose and scanner settings is desirable. We previously proposed a method using a search challenge instrument: a phantom is embedded with hundreds of lesions at random locations, and a model observer is used to detect lesions. Preliminary tests in simulation and a prototype showed promising results. PURPOSE: In this work, we fabricated a full-size search challenge phantom with design updates, including changes to lesion size, contrast, and number, and studied our implementation by comparing the lesion detectability from a nonprewhitening (NPW) model observer between different reconstructions at different exposure levels, and by estimating the instrument sensitivity to detect changes in dose. METHODS: Designed to fit into QRM anthropomorphic phantoms, our search challenge phantom is a cylindrical insert 10 cm wide and 4 cm thick, embedded with 12 000 lesions (nominal width of 0.6 mm, height of 0.8 mm, and contrast of -350 HU), and was fabricated using PixelPrint, a 3D printing technique. The insert was scanned alone at a high dose to assess printing accuracy. To evaluate lesion detectability, the insert was placed in a QRM thorax phantom and scanned from 50 to 625 mAs with increments of 25 mAs, once per exposure level, and the average of all exposure levels was used as high-dose reference. Scans were reconstructed with three different settings: filtered-backprojection (FBP) with Br40 and Br59, and Sinogram Affirmed Iterative Reconstruction (SAFIRE) with strength level 5 and Br59 kernel. An NPW model observer was used to search for lesions, and detection performance of different settings were compared using area under the exponential transform of free response ROC curve (AUC). Using propagation of uncertainty, the sensitivity to changes in dose was estimated by the percent change in exposure due to one standard deviation of AUC, measured from 5 repeat scans at 100, 200, 300, and 400 mAs. RESULTS: The printed insert lesions had an average position error of 0.20 mm compared to printing reference. As the exposure level increases from 50 mAs to 625 mAs, the lesion detectability AUCs increase from 0.38 to 0.92, 0.42 to 0.98, and 0.41 to 0.97 for FBP Br40, FBP Br59, and SAFIRE Br59, respectively, with a lower rate of increase at higher exposure level. FBP Br59 performed best with AUC 0.01 higher than SAFIRE Br59 on average and 0.07 higher than FBP Br40 (all P < 0.001). The standard deviation of AUC was less than 0.006, and the sensitivity to detect changes in mAs was within 2% for FBP Br59. CONCLUSIONS: Our 3D-printed search challenge phantom with 12 000 submillimeter lesions, together with an NPW model observer, provide an efficient CT detectability assessment method that is sensitive to subtle effects in reconstruction and is sensitive to small changes in dose.

Patient-specific, echocardiography compatible flow loop model of aortic valve regurgitation in the setting of a mechanical assist device.

Background: Aortic regurgitation (AR) occurs commonly in patients with continuous-flow left ventricular assist devices (LVAD). No gold standard is available to assess AR severity in this setting. Aim of this study was to create a patient-specific model of AR-LVAD with tailored AR flow assessed by Doppler echocardiography. Methods: An echo-compatible flow loop incorporating a 3D printed left heart of a Heart Mate II (HMII) recipient with known significant AR was created. Forward flow and LVAD flow at different LVAD speed were directly measured and AR regurgitant volume (RegVol) obtained by subtraction. Doppler parameters of AR were simultaneously measured at each LVAD speed. Results: We reproduced hemodynamics in a LVAD recipient with AR. AR in the model replicated accurately the AR in the index patient by comparable Color Doppler assessment. Forward flow increased from 4.09 to 5.61 L/min with LVAD speed increasing from 8,800 to 11,000 RPM while RegVol increased by 0.5 L/min (2.01 to 2.5 L/min). Conclusions: Our circulatory flow loop was able to accurately replicate AR severity and flow hemodynamics in an LVAD recipient. This model can be reliably used to study echo parameters and aid clinical management of patients with LVAD.

A dense search challenge phantom fabricated with pixel-based 3D printing for precise detectability assessment.

The performance of a CT scanner for detectability tasks is difficult to precisely measure. Metrics such as contrast-to-noise ratio, modulation transfer function, and noise power spectrum do not predict detectability in the context of nonlinear reconstruction. We propose to measure detectability using a dense search challenge: a phantom is embedded with hundreds of target objects at random locations, and a human or numerical observer analyzes the reconstruction and reports on suspected locations of all target objects. The reported locations are compared to ground truth to produce a figure of merit, such as area under the curve (AUC), that is sensitive to the acquisition dose and the dose efficiency of the CT scanner. We used simulations to design such a dense search challenge phantom and found that detectability could be measured with precision better than 5%. Test 3D prints using the PixelPrint technique showed the feasibility of this technique.

Scout-guided needle placement-a technical approach for dose reduction in CT-guided periradicular infiltration.

PURPOSE: To develop and evaluate a technical approach for CT-guided periradicular infiltration using quantitative needle access and guidance parameters extracted from CT scout images. METHODS: Five 3D-printed phantoms of the abdomen mimicking different patients were used to develop a technical approach for scout-guided periradicular infiltration. The needle access point, puncture depth, and needle angulation were calculated using measurements extracted from anterior-posterior and lateral CT scout images. Fifty needle placements were performed with the technique thus developed. Dose exposure and number of image acquisitions were compared with ten procedures performed using a conventional free-hand technique. Data were analyzed with the Mann-Whitney U test. RESULTS: Parameters derived solely from scout images provided adequate guidance for successful and reliable needle placement. Needle guidance was performed with the same equipment as the standard periradicular infiltration. Two scout images and 3.5 ± 2.3 (mean ± SD) single-shot images for needle positioning were acquired. Mean DLP ± SD was 3.8 ± 2.5 mGy cm. The number of single-shot acquisitions was reduced by 68% and the overall dose was reduced by 84% in comparison with the conventional free-hand technique (p < 0.0001). CONCLUSION: Scout-guided needle placement for periradicular infiltration is feasible and reduces radiation exposure significantly.

Initial evaluation of three-dimensionally printed patient-specific coronary phantoms for CT-FFR software validation.

We developed three-dimensionally (3D) printed patient-specific coronary phantoms that are capable of sustaining physiological flow and pressure conditions. We assessed the accuracy of these phantoms from coronary CT acquisition, benchtop experimentation, and CT-FFR software. Five patients with coronary artery disease underwent 320-detector row coronary CT angiography (CCTA) (Aquilion ONE, Canon Medical Systems) and a catheter lab procedure to measure fractional flow reserve (FFR). The aortic root and three main coronary arteries were segmented (Vitrea, Vital Images) and 3D printed (Eden 260V, Stratasys). Phantoms were connected into a pulsatile flow loop, which replicated physiological flow and pressure gradients. Contrast was introduced and the phantoms were scanned using the same CT scanner model and CCTA protocol as used for the patients. Image data from the phantoms were input to a CT-FFR research software (Canon Medical Systems) and compared to those derived from the clinical data, along with comparisons between image measurements and benchtop FFR results. Phantom diameter measurements were within 1 mm on average compared to patient measurements. Patient and phantom CT-FFR results had an absolute mean difference of 4.34% and Pearson correlation of 0.95. We have demonstrated the capabilities of 3D printed patient-specific phantoms in a diagnostic software.