Context-aware deep network for coronary artery stenosis classification in coronary CT angiography

Automatic coronary artery stenosis grading plays an important role in the diagnosis of coronary artery disease. Due to the difficulty of learning the informative features from varying grades of stenosis, it is still a challenging task to identify coronary artery stenosis from coronary CT angiography (CCTA). In this paper, we propose a context-aware deep network (CADN) for coronary artery stenosis classification. The proposed method integrates 3D CNN with Transformer to improve the feature representation of coronary artery stenosis in CCTA. We evaluate the proposed method on a multicenter dataset (APOLLO study with NCT05509010). Experimental results show that our proposed method can achieve the accuracy of 0.84, 0.83, and 0.86 for stenosis diagnosis on the lesion, artery, and patient levels, respectively.

Medical Imaging Compatibility of Magnesium- and Iron-Based Bioresorbable Flow Diverters

BACKGROUND AND PURPOSE

Bioresorbable flow diverters are under development to mitigate complications associated with conventional flow-diverter technology. One proposed advantage is the ability to reduce metal-induced artifacts in follow-up medical imaging. In the current work, the medical imaging compatibility of magnesium- and iron-based bioresorbable flow diverters is assessed relative to an FDA-approved control in phantom models.

MATERIALS AND METHODS

Bioresorbable flow diverters, primarily composed of braided magnesium or antiferromagnetic iron alloy wires, were compared with an FDA-approved control flow diverter. The devices were assessed for MR imaging safety in terms of magnetically induced force and radiofrequency heating using 1.5T, 3T, and 7T field strength clinical scanners. The devices were deployed in phantom models, and metal-induced image artifacts were assessed in the 3 MR imaging scanners and a clinical CT scanner following clinical scan protocols; device visibility was assessed under fluoroscopy.

RESULTS

The magnesium-based bioresorbable flow diverter, iron-based bioresorbable flow diverter, and the control device all demonstrated MR imaging safety in terms of magnetically induced force and radiofrequency heating at all 3 field strengths. The bioresorbable flow diverters did not elicit excessive MR imaging artifacts at any field strength relative to the control. Furthermore, the bioresorbable flow diverters appeared to reduce blooming artifacts in CT relative to the control. The iron-based bioresorbable flow diverter and control device were visible under standard fluoroscopy.

CONCLUSIONS

We have demonstrated the baseline medical imaging compatibility of magnesium and antiferromagnetic iron alloy bioresorbable flow diverters. Future work will evaluate the medical imaging characteristics of the bioresorbable flow diverters in large-animal models.

NLRP3 Disturbs Treg/Th17 Cell Balance to Aggravate Apical Periodontitis

Apical periodontitis is an inflammatory condition that is considered an immunological reaction of the periapical tissue to invading bacteria and their pathogenic components. Recent research has revealed that NLR family pyrin domain containing 3 (NLRP3) is crucial to the pathogenesis of apical periodontitis and serves as a link between innate and adaptive immunity. The balance between regulatory T-cell (Treg) and T helper cell 17 (Th17 cell) determines the direction of the inflammatory response. Therefore, this study aimed to investigate whether NLRP3 exacerbated periapical inflammation by disturbing Treg/Th17 balance and the underlying regulatory mechanisms. In the present study, NLRP3 was raised in apical periodontitis tissues as opposed to healthy pulp tissues. Low NLRP3 expression in dendritic cells (DCs) increased transforming growth factor β secretion while decreasing interleukin (IL)-1β and IL-6 production. The Treg ratio and IL-10 secretion rose when CD4⁺ T cells were cocultured with DCs primed with IL-1β neutralizing antibody (anti-IL-1β) and specific small interfering RNA (siRNA) targeting NLRP3 (siRNA NLRP3), but the proportion of Th17 cells and IL-17 release dropped. Furthermore, siRNA NLRP3-mediated suppression of NLRP3 expression aided Treg differentiation and elevated Foxp3 expression as well as IL-10 production in CD4⁺ T cells. Inhibition of NLRP3 activity by MCC950 boosted the percentage of Tregs while decreasing the ratio of Th17 cells, leading to reduced periapical inflammation and bone resorption. Nigericin administration, however, exacerbated periapical inflammation and bone destruction with an unbalanced Treg/Th17 response. These findings demonstrate that NLRP3 is a pivotal regulator by regulating the release of inflammatory cytokines from DCs or directly suppressing Foxp3 expression to disturb Treg/Th17 balance, thus exacerbating apical periodontitis.

Machine learning accurately quantifies epicardial adipose tissue from non-contrast CT images in coronary artery disease

Funding Acknowledgements

Type of funding sources: Other. Main funding source(s): Industry Alignment Fund – Pre-positioning Programme

Background

Epicardial adipose tissue (EAT) is the visceral fat deposit within the pericardium that surrounds the heart and the coronary arteries. EAT volume measured from non-contrast CT (NCCT) has been demonstrated to be significantly associated with adverse cardiovascular risk,1 particularly in patients with coronary artery disease.2 However, routine measurement of EAT volume is still challenging in clinical practice, as it is a tedious manual process and prone to human error.

Purpose

We aimed to develop a fully automated AI toolkit (i.e., AI EAT) for the quantification of EAT from routine NCCT scans and assess its performance in reference to clinical ground truth.

Methods

This is a multicenter study which performs CT scans in 5000 Asian Admixture patients (APOLLO study NCT05509010). In the current stage of this study, NCCT data analysis were conducted in 551 patients with 26,037 images. AI EAT was developed via a novel deep learning framework using an ensemble region-based UNet. The region-based UNet uses 2 component UNet models to perform segmentation of pericardium at the apex region and non-apex region (middle and basal). EAT volume was obtained by automated thresholding of the voxels (-190 to -30 Hounsfield Unit) within the pericardium (Figure 1). The network was trained in 501 patients with 23,712 NCCT images and tested in 50 patients with 2,325 NCCT images. The performance of AI EAT was evaluated with respect to clinical ground truth using Dice similarity coefficient (DSC), Pearson correlation, and Bland-Altman analysis.

Results

The AI EAT quantification process took less than 10 seconds per subject, compared with 20-30 minutes for expert readers. Compared to clinical ground truth, our AI EAT achieved a DSC of 0.96±0.01 and 0.91±0.02 for pericardium and EAT segmentations, respectively. There was strong agreement between the AI EAT and clinical ground truth in deriving the EAT volume (r=0.99, P<0.001) with minimal error of 7±5%.

Conclusion

End-to-end deep learning system accurately quantifies epicardial adipose tissue in standard NCCT images without manual segmentation.

Utility of Dual-Energy CT to Improve Diagnosis of CSF Leaks on CT Myelography following Lateral Decubitus Digital Subtraction Myelography with Negative Findings

CSF leaks, including CSF-venous fistulas, which cause spontaneous intracranial hypotension, remain difficult to diagnose, even on digital subtraction myelography and CT myelography. Dual-energy CT technology has been used to improve diagnostic utility within multiple organ systems. The capability of dual-energy CT to create virtual monoenergetic images can be leveraged to increase conspicuity of contrast in CSF-venous fistulas and direct epidural CSF leakage to improve the diagnostic utility of CT myelography. Six cases (in 5 patients) are shown in which virtual monoenergetic images demonstrate a leak location that was either occult or poorly visible on high- or low-kilovolt series. This clinical report describes the novel application of dual-energy CT for the detection of subtle CSF leaks including CSF-venous fistulas.

A New Frontier in Temporal Bone Imaging: Photon-Counting Detector CT Demonstrates Superior Visualization of Critical Anatomic Structures at Reduced Radiation Dose

BACKGROUND AND PURPOSE

Photon-counting detector CT is a new technology with a limiting spatial resolution of ≤150 μm. In vivo comparisons between photon-counting detector CT and conventional energy-integrating detector CT are needed to determine the clinical impact of photon counting-detector CT in temporal bone imaging.

MATERIALS AND METHODS

Prospectively recruited patients underwent temporal bone CT examinations on an investigational photon-counting detector CT system after clinically indicated temporal bone energy-integrating detector CT. Photon-counting detector CT images were obtained at an average 31% lower dose compared with those obtained on the energy-integrating detector CT scanner. Reconstructed images were evaluated in axial, coronal, and Pöschl planes using the smallest available section thickness on each system (0.4 mm on energy-integrating detector CT; 0.2 mm on photon-counting detector CT). Two blinded neuroradiologists compared images side-by-side and scored them using a 5-point Likert scale. A post hoc reassignment of readers' scores was performed so that the scores reflected photon-counting detector CT performance relative to energy-integrating detector CT.

RESULTS

Thirteen patients were enrolled, resulting in 26 image sets (left and right sides). The average patient age was 63.6 [SD, 13.4] years; 7 were women. Images from the photon-counting detector CT scanner were significantly preferred by the readers in all reconstructed planes (P < .001). Photon-counting detector CT was rated superior for the evaluation of all individual anatomic structures, with the oval window (4.79) and incudostapedial joint (4.75) receiving the highest scores on a Likert scale of 1-5.

CONCLUSIONS

Temporal bone CT images obtained on a photon-counting detector CT scanner were rated as having superior spatial resolution and better critical structure visualization than those obtained on a conventional energy-integrating detector scanner, even with a substantial dose reduction.

[CRL4B complex promotes the development of pancreatic cancer by inhibiting secreted frizzled related protein 1]

Objective: To investigate the role of CUL4B-RING E3 ubiquitin ligase (CRL4B) complex in pancreatic tumorigenesis and the molecular mechanism. Methods: Pancreatic cells were divided into control group (transfected with negative control lentivirus), shCUL4B group (transfected with CUL4B lentivirus), shDDB1 group [transfected with DNA damage binding protein 1 (DDB1) lentivirus], and shCUL4B+ siSFRP1 group (transfected with CUL4B lentivirus and SFRP1-siRNA). RNA-seq was performed in pancreatic cancer cell lines with CUL4B and DDB1 knocked down respectively, to identify the target genes regulated by CRL4B complex. Real-time fluorescent quantitative polymerase chain reaction (qRT-PCR) was used to detect the mRNA expression levels of target genes. Chromatin immunoprecipitation (ChIP) assay was used to identify the target genes directly regulated by CUL4B and DDB1. Western blot was used to detect the protein expression levels of the epithelial-mesenchymal transition (EMT) markers. The EdU cell proliferation test was used to detect cell proliferation ability. The scratch repair test and Transwell cell invasion test were used to detect cell migration and invasion ability. Finally, the sequencing data of pancreatic cancer-related tumor samples and normal samples in GEO, TCGA and GTEx databases were used to analyze the expression correlations of CUL4B, DDB1 and their downstream target genes. Results: RNA-seq results showed that target genes regulated by CRL4B complex involved in a number of malignant tumor-related signaling pathways. qRT-PCR results verified that the mRNA expression levels of the target genes of CUL4B or DDB1 knockdown groups were higher than those of the control group, and the difference was statistically significant (P<0.05). ChIP-PCR results showed that CRL4B complex directly bound to the promoter regions of the target genes, NME1 and SFRP1, and the enrichment of monoubiquitination of lysine at 119 of histone H2A (H2AK119ub1) in the promoter region of target gene was reduced after CUL4B knockdown. The proliferation rate in PANC-1 cell line of the control group was (32.10±3.58)%, higher than (13.95±1.66)% in the shCUL4B group and (22.38±0.77)% in the shCUL4B+ siSFRP1 group (P<0.05). The proliferation rate in AsPC-1 cell line of the control group was (35.47±7.80)%, higher than (19.60±3.58)% in the shCUL4B group and (30.09±0.81)% in the shCUL4B+ siSFRP1 group (P<0.05). The scratch repair experiment showed that the migration rate of PANC-1 cell line control group was (53.18±3.70)%, higher than that (17.46±2.62)% in the shCUL4B group and (44.99±9.18)% in the shCUL4B + siSFRP1 group (P<0.05). Western blot showed the expression levels of epithelial markers including α-catenin and γ-catenin in the control group were 1.00±0.03 and 1.01±0.11, respectively, lower than 1.44±0.01 and 1.21±0.06 in the shCUL4B group (P<0.05). The expression levels of mesenchymal markers including fibronectin and vimentin in the control group were 1.01±0.14 and 1.02±0.18, respectively, higher than 1.53±0.13 and 1.22±0.07 in the shCUL4B+ siSFRP1 group (P<0.05). The cell metastasis rate of the control group was (100.00±3.96)%, higher than the (35.49±0.34)% in the shCUL4B group and (107.06±2.77)% in the shCUL4B+ siSFRP1 group, the difference was statistically significant (P<0.05). The expressions of CUL4B and DDB1 were significantly upregulated in the pancreatic cancer tissues, and were negatively correlated with the expression of SFRP1 (r=-0.342 and r=-0.264, respectively). Conclusions: CRL4B complex inhibits the transcription of target gene SFRP1 and promotes the development of pancreatic cancer. Moreover, CRL4B complex is upregulated in pancreatic cancer, which provide a potential of therapeutic target for pancreatic cancer.

Mechanical stimuli for left ventricular growth during pressure overload

BACKGROUND

The mechanical stimulus (i.e. stress or stretch) for growth occurring in the pressure-overloaded left ventricle (LV) is not exactly known.

OBJECTIVE

To address this issue, we investigate the correlation between local ventricular growth (indexed by local wall thickness) and the local acute changes in mechanical stimuli after aortic banding.

METHODS

LV geometric data were extracted from 3D echo measurements at baseline and 2 weeks in the aortic banding swine model (n = 4). We developed and calibrated animal-specific finite element (FE) model of LV mechanics against pressure and volume waveforms measured at baseline. After the simulation of the acute effects of pressure-overload, the local changes of maximum, mean and minimum myocardial stretches and stresses in three orthogonal material directions (i.e., fiber, sheet and sheet-normal) over a cardiac cycle were quantified. Correlation between mechanical quantities and the corresponding measured local changes in wall thickness was quantified using the Pearson correlation number (PCN) and Spearman rank correlation number (SCN).

RESULTS

At 2 weeks after banding, the average septum thickness decreased from 10.6 ± 2.92mm to 9.49 ± 2.02mm, whereas the LV free-wall thickness increased from 8.69 ± 1.64mm to 9.4 ± 1.22mm. The FE results show strong correlation of growth with the changes in maximum fiber stress (PCN = 0.5471, SCN = 0.5111) and changes in the mean sheet-normal stress (PCN= 0.5266, SCN = 0.5256). Myocardial stretches, however, do not have good correlation with growth.

CONCLUSION

These results suggest that fiber stress is the mechanical stimuli for LV growth in pressure-overload.

Use of artificial intelligence in computed tomography dose optimisation

The field of artificial intelligence (AI) is transforming almost every aspect of modern society, including medical imaging. In computed tomography (CT), AI holds the promise of enabling further reductions in patient radiation dose through automation and optimisation of data acquisition processes, including patient positioning and acquisition parameter settings. Subsequent to data collection, optimisation of image reconstruction parameters, advanced reconstruction algorithms, and image denoising methods improve several aspects of image quality, especially in reducing image noise and enabling the use of lower radiation doses for data acquisition. Finally, AI-based methods to automatically segment organs or detect and characterise pathology have been translated out of the research environment and into clinical practice to bring automation, increased sensitivity, and new clinical applications to patient care, ultimately increasing the benefit to the patient from medically justified CT examinations. In summary, since the introduction of CT, a large number of technical advances have enabled increased clinical benefit and decreased patient risk, not only by reducing radiation dose, but also by reducing the likelihood of errors in the performance and interpretation of medically justified CT examinations.

Evaluation of Lower-Dose Spiral Head CT for Detection of Intracranial Findings Causing Neurologic Deficits

BACKGROUND AND PURPOSE

Despite the frequent use of unenhanced head CT for the detection of acute neurologic deficit, the radiation dose for this exam varies widely. Our aim was to evaluate the performance of lower-dose head CT for detection of intracranial findings resulting in acute neurologic deficit.

MATERIALS AND METHODS

Projection data from 83 patients undergoing unenhanced spiral head CT for suspected neurologic deficits were collected. Cases positive for infarction, intra-axial hemorrhage, mass, or extra-axial hemorrhage required confirmation by histopathology, surgery, progression of findings, or corresponding neurologic deficit; cases negative for these target diagnoses required negative assessments by two neuroradiologists and a clinical neurologist. A routine dose head CT was obtained using 250 effective mAs and iterative reconstruction. Lower-dose configurations were reconstructed (25-effective mAs iterative reconstruction, 50-effective mAs filtered back-projection and iterative reconstruction, 100-effective mAs filtered back-projection and iterative reconstruction, 200-effective mAs filtered back-projection). Three neuroradiologists circled findings, indicating diagnosis, confidence (0-100), and image quality. The difference between the jackknife alternative free-response receiver operating characteristic figure of merit at routine and lower-dose configurations was estimated. A lower 95% CI estimate of the difference greater than -0.10 indicated noninferiority.

RESULTS

Forty-two of 83 patients had 70 intracranial findings (29 infarcts, 25 masses, 10 extra- and 6 intra-axial hemorrhages) at routine head CT (CT dose index = 38.3 mGy). The routine-dose jackknife alternative free-response receiver operating characteristic figure of merit was 0.87 (95% CI, 0.81-0.93). Noninferiority was shown for 100-effective mAs iterative reconstruction (figure of merit difference, -0.04; 95% CI, -0.08 to 0.004) and 200-effective mAs filtered back-projection (-0.02; 95% CI, -0.06 to 0.02) but not for 100-effective mAs filtered back-projection (-0.06; 95% CI, -0.10 to -0.02) or lower-dose levels. Image quality was better at higher-dose levels and with iterative reconstruction (P < .05).

CONCLUSIONS

Observer performance for dose levels using 100-200 eff mAs was noninferior to that observed at 250 effective mAs with iterative reconstruction, with iterative reconstruction preserving noninferiority at a mean CT dose index of 15.2 mGy.

Comparison of a Photon-Counting-Detector CT with an Energy-Integrating-Detector CT for Temporal Bone Imaging: A Cadaveric Study

BACKGROUND AND PURPOSE

Evaluating abnormalities of the temporal bone requires high-spatial-resolution CT imaging. Our aim was to assess the performance of photon-counting-detector ultra-high-resolution acquisitions for temporal bone imaging and compare the results with those of energy-integrating-detector ultra-high-resolution acquisitions.

MATERIALS AND METHODS

Phantom studies were conducted to quantify spatial resolution of the ultra-high-resolution mode on a prototype photon-counting-detector CT scanner and an energy-integrating-detector CT scanner that uses a comb filter. Ten cadaveric temporal bones were scanned on both systems with the radiation dose matched to that of the clinical examinations. Images were reconstructed using a sharp kernel, 0.6-mm (minimum) thickness for energy-integrating-detector CT, and 0.6- and 0.25-mm (minimum) thicknesses for photon-counting-detector CT. Image noise was measured and compared using adjusted 1-way ANOVA. Images were reviewed blindly by 3 neuroradiologists to assess the incudomallear joint, stapes footplate, modiolus, and overall image quality. The ranking results for each specimen and protocol were compared using the Friedman test. The Krippendorff α was used for interreader agreement.

RESULTS

Photon-counting-detector CT showed an increase of in-plane resolution compared with energy-integrating-detector CT. At the same thickness (0.6 mm), images from photon-counting-detector CT had significantly lower (P < .001) image noise compared with energy-integrating-detector CT. Readers preferred the photon-counting-detector CT images to the energy-integrating-detector images for all 3 temporal bone structures. A moderate interreader agreement was observed with the Krippendorff α = 0.50. For overall image quality, photon-counting-detector CT image sets were ranked significantly higher than images from energy-integrating-detector CT (P < .001).

CONCLUSIONS

This study demonstrated substantially better delineation of fine anatomy for the temporal bones scanned with the ultra-high-resolution mode of photon-counting-detector CT compared with the ultra-high-resolution mode of a commercial energy-integrating-detector CT scanner.

Ultra-High Spatial Resolution, Multi-Energy CT using Photon Counting Detector Technology

Two ultra-high-resolution (UHR) imaging modes, each with two energy thresholds, were implemented on a research, whole-body photon-counting-detector (PCD) CT scanner, referred to as sharp and UHR, respectively. The UHR mode has a pixel size of 0.25 mm at iso-center for both energy thresholds, with a collimation of 32 × 0.25 mm. The sharp mode has a 0.25 mm pixel for the low-energy threshold and 0.5 mm for the high-energy threshold, with a collimation of 48 × 0.25 mm. Kidney stones with mixed mineral composition and lung nodules with different shapes were scanned using both modes, and with the standard imaging mode, referred to as macro mode (0.5 mm pixel and 32 × 0.5 mm collimation). Evaluation and comparison of the three modes focused on the ability to accurately delineate anatomic structures using the high-spatial resolution capability and the ability to quantify stone composition using the multi-energy capability. The low-energy threshold images of the sharp and UHR modes showed better shape and texture information due to the achieved higher spatial resolution, although noise was also higher. No noticeable benefit was shown in multi-energy analysis using UHR compared to standard resolution (macro mode) when standard doses were used. This was due to excessive noise in the higher resolution images. However, UHR scans at higher dose showed improvement in multi-energy analysis over macro mode with regular dose. To fully take advantage of the higher spatial resolution in multi-energy analysis, either increased radiation dose, or application of noise reduction techniques, is needed.

Dual Energy CT Kidney Stone Differentiation in Photon Counting Computed Tomography

This study evaluates the capabilities of a whole-body photon counting CT system to differentiate between four common kidney stone materials, namely uric acid (UA), calcium oxalate monohydrate (COM), cystine (CYS),and apatite (APA) ex vivo. Two different x-ray spectra (120 kV and 140 kV) were applied and two acquisition modes were investigated; The macro-mode generates two energy threshold based image-volumes and two energy bin based image-volumes. In the chesspattern-mode, however, four energy thresholds are applied. A virtual low energy image, as well as a virtual high energy image are derived from initial threshold-based images, while considering their statistically correlated nature. The energy bin based images of the macro-mode, as well as the virtual low and high energy image of the chesspattern-mode serve as input for our dual energy evaluation. The dual energy ratio of the individually segmented kidney stones were utilized to quantify the discriminability of the different materials. The dual energy ratios of the two acquisition modes showed high correlation for both applied spectra. Wilcoxon-rank sum tests and the evaluation of the area under the receiver operating characteristics curves suggest that the UA kidney stones are best differentiable from all other materials (AUC = 1.0), followed by CYS (AUC ≈ 0.9 compared against COM and APA). COM and APA, however, are hardly distinguishable (AUC between 0.63 and 0.76). The results hold true for the measurements of both spectra and both acquisition modes.

Renal Stone Characterization using High Resolution Imaging Mode on a Photon Counting Detector CT System

In addition to the standard-resolution (SR) acquisition mode, a high-resolution (HR) mode is available on a research photon-counting-detector (PCD) whole-body CT system. In the HR mode each detector consists of a 2x2 array of 0.225 mm × 0.225 mm subpixel elements. This is in contrast to the SR mode that consists of a 4x4 array of the same sub-elements, and results in 0.25 mm isotropic resolution at iso-center for the HR mode. In this study, we quantified ex vivo the capabilities of the HR mode to characterize renal stones in terms of morphology and mineral composition. Forty pure stones - 10 uric acid (UA), 10 cystine (CYS), 10 calcium oxalate monohydrate (COM) and 10 apatite (APA) - and 14 mixed stones were placed in a 20 cm water phantom and scanned in HR mode, at radiation dose matched to that of routine dual-energy stone exams. Data from micro CT provided a reference for the quantification of morphology and mineral composition of the mixed stones. The area under the ROC curve was 1.0 for discriminating UA from CYS, 0.89 for CYS vs COM and 0.84 for COM vs APA. The root mean square error (RMSE) of the percent UA in mixed stones was 11.0% with a medium-sharp kernel and 15.6% with the sharpest kernel. The HR showed qualitatively accurate characterization of stone morphology relative to micro CT.

Lung Nodule Volume Quantification and Shape Differentiation with an Ultra-High Resolution Technique on a Photon Counting Detector CT System

A new ultra high-resolution (UHR) mode has been implemented on a whole body photon counting-detector (PCD) CT system. The UHR mode has a pixel size of 0.25 mm by 0.25 mm at the iso-center, while the conventional (macro) mode is limited to 0.5 mm by 0.5 mm. A set of synthetic lung nodules (two shapes, five sizes, and two radio-densities) was scanned using both the UHR and macro modes and reconstructed with 2 reconstruction kernels (4 sets of images in total). Linear regression analysis was performed to compare measured nodule volumes from CT images to reference volumes. Surface curvature was calculated for each nodule and the full width half maximum (FWHM) of the curvature histogram was used as a shape index to differentiate sphere and star shape nodules. Receiver operating characteristic (ROC) analysis was performed and area under the ROC curve (AUC) was used as a figure of merit for the differentiation task. Results showed strong linear relationship between measured nodule volume and reference standard for both UHR and macro mode. For all nodules, volume estimation was more accurate using UHR mode with sharp kernel (S80f), with lower mean absolute percent error (MAPE) (6.5%) compared with macro mode (11.1% to 12.9%). The improvement of volume measurement from UHR mode was more evident particularly for small nodule size (3mm, 5mm), or star-shape nodules. Images from UHR mode with sharp kernel (S80f) consistently demonstrated the best performance (AUC = 0.85) when separating star from sphere shape nodules among all acquisition and reconstruction modes. Our results showed the advantages of UHR mode on a PCD CT scanner in lung nodule characterization. Various clinical applications, including quantitative imaging, can benefit substantially from this high resolution mode.

A High-Resolution Imaging Technique using a Whole-body, Research Photon Counting Detector CT System

A high-resolution (HR) data collection mode has been introduced to the whole-body, research photon-counting-detector CT system installed in our laboratory. In this mode, 64 rows of 0.45 mm × 0.45 mm detectors pixels were used, which corresponded to a pixel size of 0.225 mm × 0.225 mm at the iso-center. Spatial resolution of this HR mode was quantified by measuring the MTF from a scan of a 50 micron wire phantom. An anthropomorphic lung phantom, cadaveric swine lung, temporal bone and heart specimens were scanned using the HR mode, and image quality was subjectively assessed by two experienced radiologists. Comparison of the HR mode images against their energy integrating system (EID) equivalents using comb filters was also performed. High spatial resolution of the HR mode was evidenced by the MTF measurement, with 15 lp/cm and 20 lp/cm at 10% and 2% MTF. Images from anthropomorphic phantom and cadaveric specimens showed clear delineation of small structures, such as lung vessels, lung nodules, temporal bone structures, and coronary arteries. Temporal bone images showed critical anatomy (i.e. stapes superstructure) that was clearly visible in the PCD system but hardly visible with the EID system. These results demonstrated the potential application of this imaging mode in lung, temporal bone, and vascular imaging. Other clinical applications that require high spatial resolution, such as musculoskeletal imaging, may also benefit from this high resolution mode.

Temporal Bone CT: Improved Image Quality and Potential for Decreased Radiation Dose Using an Ultra-High-Resolution Scan Mode with an Iterative Reconstruction Algorithm

BACKGROUND AND PURPOSE

Radiation dose in temporal bone CT imaging can be high due to the requirement of high spatial resolution. In this study, we assessed whether CT imaging of the temporal bone by using an ultra-high-resolution scan mode combined with iterative reconstruction provides higher spatial resolution and lower image noise than a z-axis ultra-high-resolution mode.

MATERIALS AND METHODS

Patients with baseline temporal bone CT scans acquired by using a z-axis ultra-high-resolution protocol and a follow-up scan by using the ultra-high-resolution-iterative reconstruction technique were identified. Images of left and right temporal bones were reconstructed in the axial, coronal, and Poschl planes. Three neuroradiologists assessed the spatial resolution of the following structures: round and oval windows, incudomallear and incudostapedial joints, basal turn spiral lamina, and scutum. The paired z-axis ultra-high-resolution and ultra-high-resolution-iterative reconstruction images were displayed side by side in random order, with readers blinded to the imaging protocol. Image noise was compared in ROIs over the posterior fossa.

RESULTS

We identified 8 patients, yielding 16 sets of temporal bone images (left and right). Three sets were excluded because the patient underwent surgery between the 2 examinations. Spatial resolution was comparable (Poschl) or slightly better (axial and coronal planes) with ultra-high-resolution-iterative reconstruction than with z-axis ultra-high-resolution. A paired t test indicated that noise was significantly lower with ultra-high-resolution-iterative reconstruction than with z-axis ultra-high-resolution (P < .001), with a mean noise reduction of 37% (range, 18%-49%).

CONCLUSIONS

The ultra-high-resolution-iterative reconstruction scan mode has similar or slightly better resolution relative to the z-axis ultra-high-resolution mode for CT of the temporal bone but significantly (P < .01) lower image noise, which may enable the dose to be reduced by approximately 50%.

Initial results from a prototype whole-body photon-counting computed tomography system

X-ray computed tomography (CT) with energy-discriminating capabilities presents exciting opportunities for increased dose efficiency and improved material decomposition analyses. However, due to constraints imposed by the inability of photon-counting detectors (PCD) to respond accurately at high photon flux, to date there has been no clinical application of PCD-CT. Recently, our lab installed a research prototype system consisting of two x-ray sources and two corresponding detectors, one using an energy-integrating detector (EID) and the other using a PCD. In this work, we report the first third-party evaluation of this prototype CT system using both phantoms and a cadaver head. The phantom studies demonstrated several promising characteristics of the PCD sub-system, including improved longitudinal spatial resolution and reduced beam hardening artifacts, relative to the EID sub-system. More importantly, we found that the PCD sub-system offers excellent pulse pileup control in cases of x-ray flux up to 550 mA at 140 kV, which corresponds to approximately 2.5×10¹¹ photons per cm² per second. In an anthropomorphic phantom and a cadaver head, the PCD sub-system provided image quality comparable to the EID sub-system for the same dose level. Our results demonstrate the potential of the prototype system to produce clinically-acceptable images in vivo.

RIP1 maintains DNA integrity and cell proliferation by regulating PGC-1α-mediated mitochondrial oxidative phosphorylation and glycolysis

Aerobic glycolysis or the Warburg effect contributes to cancer cell proliferation; however, how this glucose metabolism pathway is precisely regulated remains elusive. Here we show that receptor-interacting protein 1 (RIP1), a cell death and survival signaling factor, regulates mitochondrial oxidative phosphorylation and aerobic glycolysis. Loss of RIP1 in lung cancer cells suppressed peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) expression, impairing mitochondrial oxidative phosphorylation and accelerating glycolysis, resulting in spontaneous DNA damage and p53-mediated cell proliferation inhibition. Thus, although aerobic glycolysis within a certain range favors cancer cell proliferation, excessive glycolysis causes cytostasis. Our data suggest that maintenance of glycolysis by RIP1 is pivotal to cancer cell energy homeostasis and DNA integrity and may be exploited for use in anticancer therapy.

Dual-energy CT for the evaluation of urinary calculi: image interpretation, pitfalls and stone mimics

Urolithiasis is a common disease with a reported prevalence between 4% and 20% in developed countries. Determination of urinary calculi composition is a key factor in preoperative evaluation, treatment, and stone recurrence prevention. Prior to the introduction of dual-energy computed tomography (DECT), available methods for determining urinary stone composition were only available after stone extraction, and thereby unable to aid in optimized stone management prior to intervention. DECT utilizes the attenuation difference produced by two different x-ray energy spectra to quantify urinary calculi composition as uric acid or non-uric acid (with likely further classification in the future) while still providing the information attained with a conventional CT. Knowledge of DECT imaging pitfalls and stone mimics is important, as the added benefit of dual-energy analysis is the determination of stone composition, which in turn affects all aspects of stone management. This review briefly describes DECT principles, scanner types and acquisition protocols for the evaluation of urinary calculi as they relate to imaging pitfalls (inconsistent characterization of small stones, small dual-energy field of view, and mischaracterization from surrounding material) and stone mimics (drainage devices) that may adversely impact clinical decisions. We utilize our clinical experience from scanning over 1200 patients with this new imaging technique to present clinically relevant examples of imaging pitfalls and possible mechanisms for resolution.

WE-D-213AB-03: Preparing for the ABR Diagnostic Medical Physics Board Exams - Oral Exam

Part III (oral exam) is the final part of ABR board exam for Diagnostic Medical Physics. In this exam, each of five oral examiners questions the candidate in each of five question categories. Oral exam has unique challenges to the candidate compared with the written exams. The candidate is expected to have not only adequate knowledge on each aspect of imaging physics, but also extensive clinical experience on different imaging modalities. The candidate needs to demonstrate her/his knowledge and clinical experience by correctly and effectively answering specific questions during the exam. Depending on the response of the candidate to original question, different follow-up questions are usually asked. Therefore, the interaction with examiners plays a critical role in the oral exam. The format and question categories of the oral exam in diagnostic medical physics will be reviewed. Study materials and effective study methods will be discussed. Practical tips on answering questions and interactions with examiners during the oral exam will also be shared.

LEARNING OBJECTIVES

1. Understand the format and scope of oral exam. 2. Develop an effective method for exam preparation. 3. Learn how to effectively answer questions and interact with examiners during the exam.