Dual energy CT angiography: pros and cons of dual-energy metal artifact reduction algorithm in patients after endovascular aortic repair

Enhancing image quality in computed tomography angiography follow-ups after endovascular aneurysm repair: a comparative study of reconstruction techniques

BACKGROUND

The image quality of computed tomography angiography (CTA) images following endovascular aneurysm repair (EVAR) is not satisfactory, since artifacts resulting from metallic implants obstruct the clear depiction of stent and isolation lumens, and also adjacent soft tissues. However, current techniques to reduce these artifacts still need further advancements due to higher radiation doses, longer processing times and so on. Thus, the aim of this study is to assess the impact of utilizing Single-Energy Metal Artifact Reduction (SEMAR) alongside a novel deep learning image reconstruction technique, known as the Advanced Intelligent Clear-IQ Engine (AiCE), on image quality of CTA follow-ups conducted after EVAR.

MATERIALS

This retrospective study included 47 patients (mean age ± standard deviation: 68.6 ± 7.8 years; 37 males) who underwent CTA examinations following EVAR. Images were reconstructed using four different methods: hybrid iterative reconstruction (HIR), AiCE, the combination of HIR and SEMAR (HIR + SEMAR), and the combination of AiCE and SEMAR (AiCE + SEMAR). Two radiologists, blinded to the reconstruction techniques, independently evaluated the images. Quantitative assessments included measurements of image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), the longest length of artifacts (AL), and artifact index (AI). These parameters were subsequently compared across different reconstruction methods.

RESULTS

The subjective results indicated that AiCE + SEMAR performed the best in terms of image quality. The mean image noise intensity was significantly lower in the AiCE + SEMAR group (25.35 ± 6.51 HU) than in the HIR (47.77 ± 8.76 HU), AiCE (42.93 ± 10.61 HU), and HIR + SEMAR (30.34 ± 4.87 HU) groups (p < 0.001). Additionally, AiCE + SEMAR exhibited the highest SNRs and CNRs, as well as the lowest AIs and ALs. Importantly, endoleaks and thrombi were most clearly visualized using AiCE + SEMAR.

CONCLUSIONS

In comparison to other reconstruction methods, the combination of AiCE + SEMAR demonstrates superior image quality, thereby enhancing the detection capabilities and diagnostic confidence of potential complications such as early minor endleaks and thrombi following EVAR. This improvement in image quality could lead to more accurate diagnoses and better patient outcomes.

Review of Clinical Applications of Dual-Energy CT in Patients after Endovascular Aortic Repair

Abdominal aortic aneurysms (AAAs) are a significant cause of mortality in developed countries. Endovascular aneurysm repair (EVAR) is currently the leading treatment method for AAAs. Due to the high sensitivity and specificity of post-EVAR complication detection, CT angiography (CTA) is the reference method for imaging surveillance in patients after EVAR. Many studies have shown the advantages of dual-energy CT (DECT) over standard polyenergetic CTA in vascular applications. In this article, the authors briefly discuss the technical principles and summarize the current body of literature regarding dual-energy computed tomography angiography (DECTA) in patients after EVAR. The authors point out the most useful applications of DECTA in this group of patients and its advantages over conventional CTA. To conduct this review, a search was performed using the PubMed, Google Scholar, and Web of Science databases.

The value of metal artifact reduction and iterative algorithms in dual energy CT angiography in patients after complex endovascular aortic aneurysm repair

Rationale and objectives

Evaluation of the diagnostic value of linearly blended (LB) and virtual monoenergetic images (VMI) reconstruction techniques with and without metal artifacts reduction (MAR) and of adaptive statistical iterative reconstructions (ASIR) in the assessment of target vessels after branched/fenestrated endovascular aortic repair (f/brEVAR) procedures.

Materials and methods

CT scans of 28 patients were used in this study. Arterial phase of examination was obtained using a dual-energy fast-kVp switching scanner. CT numbers in the aorta, celiac trunk, superior mesenteric artery, and renal arteries were measured in the following reconstructions: LB, VMI 60 keV, VMI MAR 60 keV, VMI ASIR 60 % 60 keV. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated for each reconstruction. Luminal diameters (measurements at 2 levels of stent) and subjective image quality (5-point Likert scale) were assessed (2 readers, blinded to the type of reconstruction).

Results

The highest mean values of CNR and SNR in vascular structures were obtained in VMI MAR 60 keV (CNR 12.526 ± 2.46, SNR 17.398 ± 2.52), lower in VMI 60 keV (CNR 11.508 ± 2.01, SNR 16.524 ± 2.07) and VMI ASIR (CNR 11.086 ± 1.78, SNR 15.928 ± 1.82), and the lowest in LB (CNR 6.808 ± 0.79, SNR 11.492 ± 0.79) reconstructions. There were no statistically significant differences in the measurements of the stent width between reconstructions (p > 0.05). The highest subjective image quality was obtained in the ASIR VMI (4.25 ± 0.44) and the lowest in the MAR VMI (1.57 ± 0.5) reconstruction.

Conclusion

Despite obtaining the highest values of SNR and CNR in the MAR VMI reconstruction, the subjective diagnostic value was the lowest for this technique due to significant artifacts. The type of reconstruction did not significantly affect vessel diameter measurements (p > 0.05). Iterative reconstructions raised both objective and subjective image quality.

A deep-learning system to help make the surgical planning of coil embolization for unruptured intracranial aneurysms

BACKGROUND

Coil embolization is a common method for treating unruptured intracranial aneurysms (UIAs). To effectively perform coil embolization for UIAs, clinicians must undergo extensive training with the assistance of senior physicians over an extended period. This study aimed to establish a deep-learning system for measuring the morphological features of UIAs and help the surgical planning of coil embolization for UIAs.

METHODS

Preoperative computational tomography angiography (CTA) data and surgical data from UIA patients receiving coil embolization in our medical institution were retrospectively reviewed. A convolutional neural network (CNN) model was trained on the preoperative CTA data, and the morphological features of UIAs were measured automatically using this CNN model. The intraclass correlation coefficient (ICC) was utilized to examine the similarity between the morphologies measured by the CNN model and those determined by experienced clinicians. A deep neural network model to determine the diameter of first coil was further established based on the CNN model within the derivation set (75% of all patients) using neural factorization machines (NFM) model and was validated using a validation set (25% of all patients). The general match ratio (the difference was within ± 1 mm) between the predicted diameter of first coil by model and that used in practical scenario was calculated.

RESULTS

One-hundred fifty-three UIA patients were enrolled in this study. The CNN model could diagnose UIAs with an accuracy of 0.97. The performance of this CNN model in measuring the morphological features of UIAs (i.e., size, height, neck diameter, dome diameter, and volume) was comparable to the accuracy of senior clinicians (all ICC > 0.85). The diameter of first coil predicted by the model established based on CNN model and the diameter of first coil used actually exhibited a high general match ratio (0.90) within the derivation set. Moreover, the model performed well in recommending the diameter of first coil within the validation set (general match ratio as 0.91).

CONCLUSION

This study presents a deep-learning system which can help to improve surgical planning of coil embolization for UIAs.

Comparison of Image Quality and Radiation Dose Between Single-Energy and Dual-Energy Images for the Brain With Stereotactic Frames on Dual-Energy Cerebral CT

Background

Preoperative stereotactic planning of deep brain stimulation (DBS) using computed tomography (CT) imaging in patients with Parkinson's disease (PD) is of clinical interest. However, frame-induced metal artifacts are common in clinical practice, which can be challenging for neurosurgeons to visualize brain structures.

Objectives

To evaluate the image quality and radiation exposure of patients with stereotactic frame brain CT acquired using a dual-source CT (DSCT) system in single- and dual-energy modes.

Materials and Methods

We included 60 consecutive patients with Parkinson's disease (PD) and randomized them into two groups. CT images of the brain were performed using DSCT (Group A, an 80/Sn150 kVp dual-energy mode; Group B, a 120 kVp single-energy mode). One set of single-energy images (120 kVp) and 10 sets of virtual monochromatic images (50-140 keV) were obtained. Subjective image analysis of overall image quality was performed using a five-point Likert scale. For objective image quality evaluation, CT values, image noise, signal-to-noise ratio (SNR), and contrast-to-noise (CNR) were calculated. The radiation dose was recorded for each patient.

Results

The mean effective radiation dose was reduced in the dual-energy mode (1.73 mSv ± 0.45 mSv) compared to the single-energy mode (3.16 mSv ± 0.64 mSv) (p < 0.001). Image noise was reduced by 46-52% for 120-140 keV VMI compared to 120 kVp images (both p < 0.01). CT values were higher at 100-140 keV than at 120 kVp images. At 120-140 keV, CT values of brain tissue showed significant differences at the level of the most severe metal artifacts (all p < 0.05). SNR was also higher in the dual-energy mode 90-140 keV compared to 120 kVp images, showing a significant difference between the two groups at 120-140 keV (all p < 0.01). The CNR was significantly better in Group A for 60-140 keV VMI compared to Group B (both p < 0.001). The highest subjective image scores were found in the 120 keV images, while 110-140 keV images had significantly higher scores than 120 kVp images (all p < 0.05).

Conclusion

DSCT images using dual-energy modes provide better objective and subjective image quality for patients with PD at lower radiation doses compared to single-energy modes and facilitate brain tissue visualization with stereotactic frame DBS procedures.

Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network

The computed tomography angiography (CTA) postprocessing manually recognized by technologists is extremely labor intensive and error prone. We propose an artificial intelligence reconstruction system supported by an optimized physiological anatomical-based 3D convolutional neural network that can automatically achieve CTA reconstruction in healthcare services. This system is trained and tested with 18,766 head and neck CTA scans from 5 tertiary hospitals in China collected between June 2017 and November 2018. The overall reconstruction accuracy of the independent testing dataset is 0.931. It is clinically applicable due to its consistency with manually processed images, which achieves a qualification rate of 92.1%. This system reduces the time consumed from 14.22 ± 3.64 min to 4.94 ± 0.36 min, the number of clicks from 115.87 ± 25.9 to 4 and the labor force from 3 to 1 technologist after five months application. Thus, the system facilitates clinical workflows and provides an opportunity for clinical technologists to improve humanistic patient care.

Manual postprocessing of computed tomography angiography (CTA) images is extremely labor intensive and error prone. Here, the authors propose an artificial intelligence reconstruction system that can automatically achieve CTA reconstruction in healthcare services.

Frequency and causes of delayed diagnosis of visceral artery pseudoaneurysms with CT: Lessons learned

Objective

Visceral artery pseudoaneurysms (VAPA) are associated with a high morbidity and mortality, but sometimes are missed in initial computed tomography (CT) examinations. The aims of this study were to determine the frequency and causes of misdiagnoses of VAPA with CT.

Materials and Methods

We retrospectively identified 77 patients with VAPA in our database who underwent contrast-enhanced CT. The frequency of delayed diagnosis was determined and the reasons were noted. We identified the etiology of VAPA, measured size, and noted the affected vessels.

Results

Forty-five of the 77 patients (58 %) had a delayed diagnosis of VAPA. There was no difference in the rate of missed VAPA in symptomatic compared to asymptomatic patients (p = 0.255). The majority of VAPA were associated with previous surgery or interventions (n = 48/62 %). The major affected vessel was the hepatic (n = 31) followed by the splenic artery (n = 17). The main reasons for misdiagnosis were a missed arterial phase in CT (n = 16/36 %), artifacts masking the aneurysm (n = 9/20 %), overlooked pseudoaneurysm (n = 19/42 %), and misinterpretation by attending radiologists (n = 1/2 %). Missed VAPA were smaller (median 8 mm) than those VAPA that were initially diagnosed (median 13 mm, p < 0.01), but occurred with a similar frequency in larger and smaller visceral arteries (p = 0.601).

Conclusions

Our study showed that 58 % of VAPA were diagnosed with delay, with the following four reasons for misdiagnosis: Lack of an arterial contrast phase in CT, no techniques for artifact reduction, and lack of awareness of the radiologists. Avoiding delayed diagnosis will most probably improve outcome of patients with VAPA.

Contemporary imaging methods for the follow-up after endovascular abdominal aneurysm repair: a review

Abdominal aortic aneurysm (AAA) is defined as a localized enlargement of the aortic cross-section where the diameter is greater than 3 cm or more than 50% larger than the diameter in a normal segment. The most important complication of AAA is rupture, which, if untreated, results in mortality rates of up to 90%. Conventional open surgical repair is associated with significant 30-day mortality. Endovascular aneurysm repair (EVAR) is a significantly less invasive procedure; it is related to a lower early mortality rate and a lower number of perioperative complications. Although EVAR is a minimally invasive technique, lifelong follow-up imaging is necessary due to possible late complications including endoleak, recurrent aneurysm formation, graft infection, migration, kinking and thrombosis. The total rate of complications after EVAR is estimated at approximately 30%, and the rate of complications that require intervention is 2–3%. Early detection and progression analysis of such situations is crucial for proper intervention.

Iterative algorithms for metal artifact reduction in children with orthopedic prostheses: preliminary results

BACKGROUND

Increased computational power allows computed tomography (CT) software to process very advanced mathematical algorithms to generate better quality images at lower doses. One such algorithm, iterative metal artifact reduction (iMAR) has proven to decrease metal artifacts seen in CT images of adults with orthopedic implants.

OBJECTIVES

To evaluate artifact reduction capability of the algorithm in lower-dose pediatric CT compared to our routine third-generation advanced modeled iterative reconstruction (ADMIRE) algorithm.

MATERIALS AND METHODS

Thirteen children (11-17 years old) with metal implants underwent routine clinically indicated CT. Data sets were reconstructed with an iMAR algorithm. Hounsfield units and image noise were measured in bone, muscle and fat in the streak artifact (near the implant) and at the greatest distance from the artifact (far from the implant). A regression model compared the effects of the algorithm (standard ADMIRE vs. iMAR) near and far from the implant.

RESULTS

Near the implant, Hounsfield units with iMAR were significantly different in our standard ADMIRE vs. iMAR for bone, muscle and fat (P<0.001). Noise was significantly different in standard ADMIRE vs. iMAR in bone (P<0.003). Far from the implant, Hounsfield units and noise were not significantly different for ADMIRE vs. iMAR, for the three tissue types.

CONCLUSION

These preliminary results demonstrate that iMAR algorithms improves Hounsfield units near the implant and decreases image noise in bone in low-dose pediatric CT. It does this without changing baseline tissue density or noise far from the implant.

Single-energy metal artifact reduction technique for reducing metallic coil artifacts on post-interventional cerebral CT and CT angiography

PURPOSE

To evaluate the effects of the single-energy metal artifact reduction (SEMAR) algorithm on image quality of cerebral CT and CT angiography (CTA) for patients who underwent intracranial aneurysm coiling.

METHODS

Twenty patients underwent cerebral CT and CTA using a 320-detector row CT after intracranial aneurysm coiling. Images with and without application of the SEMAR algorithm (SEMAR CT and standard CT images, respectively) were reconstructed for each patient. The images were qualitatively assessed by two independent radiologists in a blinded manner for the depiction of anatomical structures around the coil, delineation of the arteries around the coil, and the depiction of the status of coiled aneurysms. Artifact strength was quantitatively assessed by measuring the standard deviation of attenuation values around the coil.

RESULTS

The strength of artifacts measured in SEMAR CT images was significantly lower than that in standard CT images (25.7 ± 10.2 H.U. vs. 80.4 ± 67.2 H.U., p < 0.01, Student's paired t test). SEMAR CT images were significantly improved compared with standard CT images in the depiction of anatomical structures around the coil (p < 0.01, the sign test), delineation of the arteries around the coil (p < 0.01), and the depiction of the status of coiled aneurysms (p < 0.01).

CONCLUSION

The SEMAR algorithm significantly reduces metal artifacts from intracranial aneurysm coiling and improves visualization of anatomical structures and arteries around the coil, and depiction of the status of coiled aneurysms on post-interventional cerebral CT.

Utility of Lung Ultrasonography for Detection of Pleural Adhesions in Dogs

OBJECTIVES

To assess lung respiratory movement ("lung sliding") in dogs using B-mode ultrasonography (US) and to develop a method that assesses adhesions between the parietal pleura and the lung.

METHODS

Seventeen male beagles were anesthetized, and respiratory management was performed with intermittent positive pressure ventilation. Lung-sliding assessments and adhesion examinations were performed with lung US under general anesthesia before and 2 weeks after thoracotomy. Lung sliding was scored on a 4-level scale based on the percentage of the area that showed lung sliding (3, an area of roughly ≥80% of the intercostal space; 2, about 50% of the area of the intercostal space; 1, a small area of the intercostal space; or 0, movement absent); scores of 0, 1, and 2 indicated adhesions, whereas a score of 3 indicated no adhesions. The animals were then euthanized, and necropsy was performed to examine pleural adhesions.

RESULTS

Lung US and necropsy findings were compared. The median lung-sliding score for the 12 sites with pleural adhesions on necropsy was 1.5, whereas it was 3.0 for the 532 sites without pleural adhesions. The lung-sliding score was significantly lower in the group with adhesions (P < .0001). Adhesion sites detected on necropsy were in accordance with the sites that had decreased lung-sliding scores. Lung US could detect pleural adhesions with sensitivity of 100.0% and specificity of 87.8%.

CONCLUSIONS

Examination of lung sliding by thoracic US has high diagnostic value for detecting canine pleural adhesions and is useful in predicting adhesion sites before thoracic surgery in healthy dogs.

Pancreatic adenocarcinoma: cross-sectional imaging techniques

Pancreatic adenocarcinoma is a common malignancy that has a poor prognosis. Imaging is vital in its detection, staging, and management. Although a variety of imaging techniques are available, MDCT is the preferred imaging modality for staging and assessing the resectability of pancreatic adenocarcinoma. MR also has an important adjunct role, and may be used in addition to CT or as a problem-solving tool. A dedicated pancreatic protocol should be acquired as a biphasic technique optimized for the detection of pancreatic adenocarcinoma and to allow accurate local and distant disease staging. Emerging techniques like dual-energy CT and texture analysis of CT and MR images have a great potential in improving lesion detection, characterization, and treatment monitoring.

Evaluation of CT Angiography Image Quality Acquired with Single-Energy Metal Artifact Reduction (SEMAR) Algorithm in Patients After Complex Endovascular Aortic Repair

Purpose

To evaluate the value of single-energy metal artifact reduction (SEMAR) algorithm on image quality in patients after complex endovascular aortic repair (EVAR) with fenestrated and branched devices.

Methods

Routine follow-up computed tomography angiography (CTA) examinations were performed between February 2016 and May 2017 in 18 patients who underwent a complex EVAR procedure at our institution. Objective analysis was performed by measuring the standard deviation (SD) of attenuation (Hounsfield Units), and the contrast-to-noise ratio (CNR) in regions of interests in the stented visceral arteries. Subjective analysis of the degree of artifacts and stent visualization was performed independently by two interventional radiologists, blinded to the image reconstruction.

Results

The SD of attenuation was significantly lower in all target visceral arteries (p < .001), the celiac artery (p = .002), the superior mesenteric artery (SMA; p = .043), and renal arteries (p < .001) in the CT images with SEMAR reconstruction. The CNR significantly increased in all SEMAR-reconstructed target visceral arteries (overall: p < .001, celiac artery: p = .009; SMA: p = .003; renal arteries: p < .001). The reviewers rated a significantly lower artifact degree in all target vessels (overall: p < .001, celiac artery: p = .001; SMA: p = .008; renal arteries: p < .001) and a significantly improved visualization of the stent patency in all target vessels (overall: p < .001, celiac artery: p = .031; SMA: p = .047; renal arteries: p < .001) in the SEMAR images. Overall preference of both reviewers was in favor of the SEMAR reconstruction in 15/18 cases (83%).

Conclusion

Reconstruction with SEMAR algorithm significantly improves CTA image quality in patients after complex EVAR.

Level of Evidence

Level 4, Case series.

Split-bolus intravenous contrast material injection vs. single-bolus injection in patients following endovascular abdominal aortic repair (EVAR)

PURPOSE

To investigate the feasibility and accuracy of a split-bolus contrast injection CTA (SB-CTA) compared to a single-bolus injection CTA (SI-CTA) protocol of post-EVAR patients.

MATERIALS AND METHODS

In this IRB-approved study, patients who underwent SB-CTA and SI-CTA after EVAR were evaluated. Attenuation and contrast-to-noise ratio (CNR) of vessels and parenchymal organs were assessed. Subjective enhancement of vessels, quality of 3D reconstructions, and enhancement phase of parenchymal organs were assessed by two independent readers. Endoleak visibility and incidental findings were evaluated.

RESULTS

Fifty-six patients with SB-CTA and SI-CTA at two different time points after EVAR were included in the study (112 imaging studies, mean age 75 ± 9 years). There was no difference in attenuation and CNR for aorta between SB-CTA and SI-CTA (310 ± 87 vs. 311 ± 80 HU, p = 0.88; 31.1 ± 12.6 vs. 29.0 ± 12.2, p = 0.20), although both were improved in the venous structures and parenchymal organs with SB-CTA (portal vein: 149 ± 33 vs. 88 ± 32 HU, 11.6 ± 5.6 vs. 4.3 ± 3.4; liver: 91 ± 19 vs. 68 ± 20 HU, 4.4 ± 2.8 vs. 2.1 ± 2.0; pancreas: 108 ± 27 vs. 82 ± 23 HU, 6.4 ± 3.1 vs. 3.6 ± 2.4; p < 0.0001). Subjectively, enhancement of veins, liver, spleen, bowel, and kidneys was improved (p < 0.001), while there was no difference for the aorta (p = 0.46) and 3D reconstructions (p = 0.58). None of the 18/56 (32.1%) endoleaks was missed with the SB-CTA. More incidental findings were detected with SB-CTA (158/56) compared to SI-CTA (135/56), p < 0.001. SB-CTA was able to adequately characterize 7/15 (47%) of the findings that needed further evaluation in SI-CTA. 4/15 (26%) incidental findings that were missed with SI-CTA but seen with SB-CTA required further evaluation.

CONCLUSION

Split-bolus injection CTA in the follow-up of EVAR patients allows reliable visualization of endoleaks with improved subjective and objective image quality.