Objective

We report the development and use of MRI-compatible and MRI-visible 3D printed models in conjunction with advanced visualization software models to plan and simulate safe access routes to achieve a theoretic zone of cryoablation for percutaneous image-guided treatment of a C7 pedicle osteoid osteoma and an L1 lamina osteoblastoma. Both models altered procedural planning and patient care.

Conclusion

Patient-specific MRI-visible models can be helpful in planning complex percutaneous image-guided cryoablation procedures.

Background

Medical 3D printing is expanding exponentially, with tremendous potential yet to be realized in nearly all facets of medicine. Unfortunately, multiple informal subdomain-specific isolated terminological 'silos' where disparate terminology is used for similar concepts are also arising as rapidly. It is imperative to formalize the foundational terminology at this early stage to facilitate future knowledge integration, collaborative research, and appropriate reimbursement. The purpose of this work is to develop objective, literature-based consensus-building methodology for the medical 3D printing domain to support expert consensus.

Results

We first quantitatively survey the temporal, conceptual, and geographic diversity of all existing published applications within medical 3D printing literature and establish the existence of self-isolating research clusters. We then demonstrate an automated objective methodology to aid in establishing a terminological consensus for the field based on objective analysis of the existing literature. The resultant analysis provides a rich overview of the 3D printing literature, including publication statistics and trends globally, chronologically, technologically, and within each major medical discipline. The proposed methodology is used to objectively establish the dominance of the term "3D printing" to represent a collection of technologies that produce physical models in the medical setting. We demonstrate that specific domains do not use this term in line with objective consensus and call for its universal adoption.

Conclusion

Our methodology can be applied to the entirety of medical 3D printing literature to obtain a complete, validated, and objective set of recommended and synonymous definitions to aid expert bodies in building ontological consensus.

Background and objectives

3D-printed models are increasingly used for surgical planning. We assessed the utility, accuracy, and reproducibility of 3D printing to assist visualization of complex thoracic tumors for surgical planning.

Methods

Models were created from pre-operative images for three patients using a standard radiology 3D workstation. Operating surgeons assessed model utility using the Gillespie scale (1 = inferior to 4 = superior), and accuracy compared to intraoperative findings. Model variability was assessed for one patient for whom two models were created independently. The models were compared subjectively by surgeons and quantitatively based on overlap of depicted tissues, and differences in tumor volume and proximity to tissues.

Results

Models were superior to imaging and 3D visualization for surgical planning (mean score = 3.4), particularly for determining surgical approach (score = 4) and resectability (score = 3.7). Model accuracy was good to excellent. In the two models created for one patient, tissue volumes overlapped by >86.5%, and tumor volume and area of tissues ≤1 mm to the tumor differed by <15% and <1.8 cm² , respectively. Surgeons considered these differences to have negligible effect on surgical planning.

Conclusion

3D printing assists surgical planning for complex thoracic tumors. Models can be created by radiologists using routine practice tools with sufficient accuracy and clinically negligible variability.

The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the heterogeneity of how these data are formatted. Indeed, although there is movement toward structured reporting in radiology (ie, hierarchically itemized reporting with use of standardized terminology), the majority of radiology reports remain unstructured and use free-form language. To effectively "mine" these large datasets for hypothesis testing, a robust strategy for extracting the necessary information is needed. Manual extraction of information is a time-consuming and often unmanageable task. "Intelligent" search engines that instead rely on natural language processing (NLP), a computer-based approach to analyzing free-form text or speech, can be used to automate this data mining task. The overall goal of NLP is to translate natural human language into a structured format (ie, a fixed collection of elements), each with a standardized set of choices for its value, that is easily manipulated by computer programs to (among other things) order into subcategories or query for the presence or absence of a finding. The authors review the fundamentals of NLP and describe various techniques that constitute NLP in radiology, along with some key applications.

Medical 3-dimensional (3D) printing is emerging as a clinically relevant imaging tool in directing preoperative and intraoperative planning in many surgical specialties and will therefore likely lead to interdisciplinary collaboration between engineers, radiologists, and surgeons. Data from standard imaging modalities such as computed tomography, magnetic resonance imaging, echocardiography, and rotational angiography can be used to fabricate life-sized models of human anatomy and pathology, as well as patient-specific implants and surgical guides. Cardiovascular 3D-printed models can improve diagnosis and allow for advanced preoperative planning. The majority of applications reported involve congenital heart diseases and valvular and great vessels pathologies. Printed models are suitable for planning both surgical and minimally invasive procedures. Added value has been reported toward improving outcomes, minimizing perioperative risk, and developing new procedures such as transcatheter mitral valve replacements. Similarly, thoracic surgeons are using 3D printing to assess invasion of vital structures by tumors and to assist in diagnosis and treatment of upper and lower airway diseases. Anatomic models enable surgeons to assimilate information more quickly than image review, choose the optimal surgical approach, and achieve surgery in a shorter time. Patient-specific 3D-printed implants are beginning to appear and may have significant impact on cosmetic and life-saving procedures in the future. In summary, cardiothoracic 3D printing is rapidly evolving and may be a potential game-changer for surgeons. The imager who is equipped with the tools to apply this new imaging science to cardiothoracic care is thus ideally positioned to innovate in this new emerging imaging modality.

OBJECTIVE:Results of the use of the transluminal attenuation gradient (TAG) at coronary CT angiography (CCTA) to predict hemodynamically significant disease vary widely. This study tested whether diagnostic performance of TAG to predict fractional flow reserve (FFR) ≤ 0.8 is improved when applied separately to subsets of coronary arteries that carry similar physiological flow. METHODS:28 patients with 64 × 0.5 mm CCTA and invasive FFR in ≥1 major coronary artery were retrospectively evaluated. Two readers assessed TAG in each artery. The receiver operating characteristic (ROC) area under the curve (AUC) was used to assess the diagnostic performance of TAG to detect hemodynamically significant disease following a clinical use rule [negative: FFR > 0.8 or ≤ 25% diameter stenosis (DS) at invasive catheter angiography; positive: FFR ≤ 0.8 or ≥ 90% DS at invasive catheter angiography]. ROC AUC was compared for all arteries pooled together, vs separately for arteries carrying similar physiological flow (Group 1: all left anterior descending plus right-dominant left circumflex; Group 2: right-dominant RCA plus left/co-dominant left circumflex). RESULTS:Of the 84 arteries, 30 had FFR measurements, 30 had ≤25% DS and 13 had ≥90% DS. 11 arteries with 26-89% DS and no FFR measurement were excluded. TAG interobserver reproducibility was excellent (Pearson r = 0.954, Bland-Altman bias: 0.224 Hounsfield unit cm-1). ROC AUC to detect hemodynamically significant disease was higher when considering arteries separately (Group 1 AUC = 0.841, p = 0.039; Group 2 AUC = 0.840, p = 0.188), than when pooling all arteries together (AUC = 0.661). CONCLUSION:Incorporating information on the physiology of coronary flow via the particular vessel interrogated and coronary dominance may improve the accuracy of TAG, a simple measurement that can be quickly performed at the time of CCTA interpretation to detect hemodynamically significant stenosis in individual coronary arteries. Advances in knowledge: The interpretation of TAG may benefit by incorporating information regarding which coronary artery is being interrogated.

Background and aims

Low and high endothelial shear stress (ESS) is associated with coronary atherosclerosis progression and high-risk plaque features. Coronary ESS is currently assessed via computational fluid dynamic (CFD) simulation of coronary blood flow in the lumen geometry determined from invasive imaging such as intravascular ultrasound and optical coherence tomography. This process typically omits side branches of the target vessel in the CFD model as invasive imaging of those vessels is not usually clinically-indicated. The purpose of this study was to determine the extent to which this simplification affects the determination of those regions of the coronary endothelium subjected to pathologic ESS.

Methods

We determined the diagnostic accuracy of ESS profiling without side branches to detect pathologic ESS in the major coronary arteries of 5 hearts imaged ex vivo with computed tomography angiography (CTA). ESS of the three major coronary arteries was calculated both without (test model), and with (reference model) inclusion of all side branches >1.5 mm in diameter, using previously-validated CFD approaches. Diagnostic test characteristics (accuracy, sensitivity, specificity and negative and positive predictive value [NPV/PPV]) with respect to the reference model were assessed for both the entire length as well as only the proximal portion of each major coronary artery, where the majority of high-risk plaques occur.

Results

Using the model without side branches overall accuracy, sensitivity, specificity, NPV and PPV were 83.4%, 54.0%, 96%, 95.9% and 55.1%, respectively to detect low ESS, and 87.0%, 67.7%, 90.7%, 93.7% and 57.5%, respectively to detect high ESS. When considering only the proximal arteries, test characteristics differed for low and high ESS, with low sensitivity (67.7%) and high specificity (90.7%) to detect low ESS, and low sensitivity (44.7%) and high specificity (95.5%) to detect high ESS.

Conclusions

The exclusion of side branches in ESS vascular profiling studies greatly reduces the ability to detect regions of the major coronary arteries subjected to pathologic ESS. Single-conduit models can in general only be used to rule out pathologic ESS.

Purpose To compare the diagnostic accuracy of different computed tomographic (CT) fractional flow reserve (FFR) algorithms for vessels with intermediate stenosis. Materials and Methods This cross-sectional HIPAA-compliant and human research committee-approved study applied a four-step CT FFR algorithm in 61 patients (mean age, 69 years ± 10; age range, 29-89 years) with a lesion of intermediate-diameter stenosis (25%-69%) at CT angiography who underwent FFR measurement within 90 days. The per-lesion diagnostic performance of CT FFR was tested for three different approaches to estimate blood flow distribution for CT FFR calculation. The first two, the Murray law and the Huo-Kassab rule, used coronary anatomy; the third used contrast material opacification gradients. CT FFR algorithms and CT angiography percentage diameter stenosis (DS) measurements were compared by using the area under the receiver operating characteristic curve (AUC) to detect FFRs of 0.8 or lower. Results Twenty-five lesions (41%) had FFRs of 0.8 or lower. The AUC of CT FFR determination by using contrast material gradients (AUC = 0.953) was significantly higher than that of the Huo-Kassab (AUC = 0.882, P = .043) and Murray law models (AUC = 0.871, P = .033). All three AUCs were higher than that for 50% or greater DS at CT angiography (AUC = 0.596, P < .001). Correlation of CT FFR with FFR was highest for gradients (Spearman ρ = 0.80), followed by the Huo-Kassab rule (ρ = 0.68) and Murray law (ρ = 0.67) models. All CT FFR algorithms had small biases, ranging from -0.015 (Murray) to -0.049 (Huo-Kassab). Limits of agreement were narrowest for gradients (-0.182, 0.147), followed by the Huo-Kassab rule (-0.246, 0.149) and the Murray law (-0.285, 0.256) models. Conclusion Clinicians can perform CT FFR by using a four-step approach on site to accurately detect hemodynamically significant intermediate-stenosis lesions. Estimating blood flow distribution by using coronary contrast opacification variations may improve CT FFR accuracy. ^© RSNA, 2017 Online supplemental material is available for this article.

Hand-held three dimensional models of the human anatomy and pathology, tailored-made protheses, and custom-designed implants can be derived from imaging modalities, most commonly Computed Tomography (CT). However, standard DICOM format images cannot be 3D printed; instead, additional image post-processing is required to transform the anatomy of interest into Standard Tessellation Language (STL) format is needed. This conversion, and the subsequent 3D printing of the STL file, requires a series of steps. Initial post-processing involves the segmentation-demarcation of the desired for 3D printing parts and creating of an initial STL file. Then, Computer Aided Design (CAD) software is used, particularly for wrapping, smoothing and trimming. Devices and implants that can also be 3D printed, can be designed using this software environment. The purpose of this article is to provide a tutorial on 3D Printing with the test case of complex congenital heart disease (CHD). While the infant was born with double outlet right ventricle (DORV), this hands-on guide to be featured at the 2015 annual meeting of the Radiological Society of North America Hands-on Course in 3D Printing focused on the additional finding of a ventricular septal defect (VSD). The process of segmenting the heart chambers and the great vessels will be followed by optimization of the model using CAD software. A virtual patch that accurately matches the patient's VSD will be designed and both models will be prepared for 3D printing.

Background

The effects of reduced radiation dose CT for the generation of maxillofacial bone STL models for 3D printing is currently unknown. Images of two full-face transplantation patients scanned with non-contrast 320-detector row CT were reconstructed at fractions of the acquisition radiation dose using noise simulation software and both filtered back-projection (FBP) and Adaptive Iterative Dose Reduction 3D (AIDR3D). The maxillofacial bone STL model segmented with thresholding from AIDR3D images at 100 % dose was considered the reference. For all other dose/reconstruction method combinations, a "residual STL volume" was calculated as the topologic subtraction of the STL model derived from that dataset from the reference and correlated to radiation dose.

Results

The residual volume decreased with increasing radiation dose and was lower for AIDR3D compared to FBP reconstructions at all doses. As a fraction of the reference STL volume, the residual volume decreased from 2.9 % (20 % dose) to 1.4 % (50 % dose) in patient 1, and from 4.1 % to 1.9 %, respectively in patient 2 for AIDR3D reconstructions. For FBP reconstructions it decreased from 3.3 % (20 % dose) to 1.0 % (100 % dose) in patient 1, and from 5.5 % to 1.6 %, respectively in patient 2. Its morphology resembled a thin shell on the osseous surface with average thickness <0.1 mm.

Conclusion

The residual volume, a topological difference metric of STL models of tissue depicted in DICOM images supports that reduction of CT dose by up to 80 % of the clinical acquisition in conjunction with iterative reconstruction yields maxillofacial bone models accurate for 3D printing.