Early Intraluminal Frozen Elephant Trunk Stent Graft Thrombosis After Aortic Arch Surgery.

BACKGROUND: Partial intraluminal thrombosis of the frozen elephant trunk (FET) stent graft is a poorly described but not infrequent complication after aortic arch surgery. This study aims to describe and analyze the occurrence of early FET stent graft thrombosis. METHODS: Retrospective single-center analysis including patients who underwent aortic arch replacement with FET technique between 2006 and 2020. Stent graft thrombosis was diagnosed through computed tomography scan. Several computed tomography scan parameters and clinical variables were analyzed as predictors of this event. RESULTS: A total of 125 patients were included for analysis. Among these, 21 (16.8%) patients developed early postoperative FET stent graft thrombosis. Mean volumetric size of the aorta was 12.2 ± 2.0 mL in patients with FET stent graft thrombosis and 10.1 ± 2.8 mL in patients without thrombosis (P < .01). Thrombosis occurred more frequently among patients requiring thoracic endovascular aortic repair completion (15 of 21 [71.4%] patients) than in patients with completely excluded aneurysms (6 of 21 [28.6%] patients) (P = .01). Mean stent-to-aneurysm diameter ratio was 0.8 ± 0.2 among patients with thrombosis and 1.0 ± 0.2 among patients without thrombosis (P < .01). Thrombosis was more frequently observed among patients with conservative management of postoperative bleeding (P = .04). Patients with early FET thrombosis had a nonsignificantly higher in-hospital all-cause mortality than patients without thrombosis (19.0% vs 8.7%; P = .3). CONCLUSIONS: Early postoperative intraluminal thrombosis is a frequent complication post FET surgery. Smaller stent graft sizes, larger or partially covered aneurysms, and major bleeding are associated with early thrombosis. Slight FET oversizing, prompt thoracic endovascular aortic repair completion, and early reintervention for major bleeding may prevent early thrombosis.

Interrater variability of ML-based CT-FFR during TAVR-planning: influence of image quality and coronary artery calcifications.

Objective: To compare machine learning (ML)-based CT-derived fractional flow reserve (CT-FFR) in patients before transcatheter aortic valve replacement (TAVR) by observers with differing training and to assess influencing factors. Background: Coronary computed tomography angiography (cCTA) can effectively exclude CAD, e.g. prior to TAVR, but remains limited by its specificity. CT-FFR may mitigate this limitation also in patients prior to TAVR. While a high reliability of CT-FFR is presumed, little is known about the reproducibility of ML-based CT-FFR. Methods: Consecutive patients with obstructive CAD on cCTA were evaluated with ML-based CT-FFR by two observers. Categorization into hemodynamically significant CAD was compared against invasive coronary angiography. The influence of image quality and coronary artery calcium score (CAC) was examined. Results: CT-FFR was successfully performed on 214/272 examinations by both observers. The median difference of CT-FFR between both observers was -0.05(-0.12-0.02) (p < 0.001). Differences showed an inverse correlation to the absolute CT-FFR values. Categorization into CAD was different in 37/214 examinations, resulting in net recategorization of Δ13 (13/214) examinations and a difference in accuracy of Δ6.1%. On patient level, correlation of absolute and categorized values was substantial (0.567 and 0.570, p < 0.001). Categorization into CAD showed no correlation to image quality or CAC (p > 0.13). Conclusion: Differences between CT-FFR values increased in values below the cut-off, having little clinical impact. Categorization into CAD differed in several patients, but ultimately only had a moderate influence on diagnostic accuracy. This was independent of image quality or CAC.

CT Planning prior to Transcatheter Mitral Valve Replacement (TMVR). / CT-Planung vor kathetergestütztem Mitralklappenersatz (TMVR).

BACKGROUND: Transcatheter mitral valve replacement (TMVR) is a treatment option for patients with therapy refractory high-grade mitral valve regurgitation and a high perioperative risk.During TMVR, the mitral annulus cannot be visualized directly. Therefore, comprehensive pre-interventional planning and a precise visualization of the patient's specific mitral valve anatomy, outflow tract anatomy and projected anchoring of the device are necessary.Aim of this review-article is, to assess the role of pre-procedural computed tomography (CT) for TMVR-planning METHODS: Screening and evaluation of relevant guidelines (European Society of Cardiology [ESC], American Heart Association [AHA/ACC]), meta-analyses and original research using the search terms "TVMR" or "TMVI" and "CT". In addition to this, the authors included insight from their own clinical experience. RESULTS: CT allows for accurate measurement of the mitral annulus with high special and adequate temporal resolution in all cardiac phases. Therefore, CT represents a valuable method for accurate prosthesis-sizing.In addition to that, CT can provide information about the valvular- and outflow-tract-anatomy, mitral valve calcifications, configuration of the papillary muscles and of the left ventricle. Additionally, the interventional access-route may concomitantly be visualized. CONCLUSION: CT plays, in addition to echocardiographic imaging, a central role in pre-interventional assessment prior to TMVR. Especially the precise depiction of the left ventricular outflow tract (LVOT) provides relevant additional information, which is very difficult or not possible to be acquired in their entirety with other imaging modalities. KEY POINTS: · CT plays a central role in pre-interventional imaging for TMVR.. · CT-measurements allow for accurate prosthesis-sizing.. · CT provides valuable information about LVOT-anatomy, mitral calcifications and interventional access-route.. CITATION FORMAT: · Heiser L, Gohmann RF, Noack T et al. CT Planning prior to Transcatheter Mitral Valve Replacement (TMVR). Fortschr Röntgenstr 2022; 194: 373 - 383.

Combined cCTA and TAVR Planning for Ruling Out Significant CAD: Added Value of ML-Based CT-FFR.

OBJECTIVES: The purpose of this study was to analyze the ability of machine-learning (ML)-based computed tomography (CT)-derived fractional flow reserve (CT-FFR) to further improve the diagnostic performance of coronary CT angiography (cCTA) for ruling out significant coronary artery disease (CAD) during pre-transcatheter aortic valve replacement (TAVR) evaluation in patients with a high pre-test probability for CAD. BACKGROUND: CAD is a frequent comorbidity in patients undergoing TAVR. Current guidelines recommend its assessment before TAVR. If significant CAD can be excluded on cCTA, invasive coronary angiography (ICA) may be avoided. Although cCTA is a very sensitive test, it is limited by relatively low specificity and positive predictive value, particularly in high-risk patients. METHODS: Overall, 460 patients (age 79.6 ± 7.4 years) undergoing pre-TAVR CT were included and examined with an electrocardiogram-gated CT scan of the heart and high-pitch scan of the vascular access route. Images were evaluated for significant CAD. Patients routinely underwent ICA (388/460), which was omitted at the discretion of the local Heart Team if CAD could be effectively ruled out on cCTA (72/460). CT examinations in which CAD could not be ruled out (CAD+) (n = 272) underwent additional ML-based CT-FFR. RESULTS: ML-based CT-FFR was successfully performed in 79.4% (216/272) of all CAD+ patients and correctly reclassified 17 patients as CAD negative. CT-FFR was not feasible in 20.6% because of reduced image quality (37/56) or anatomic variants (19/56). Sensitivity, specificity, positive predictive value, and negative predictive value were 94.9%, 52.0%, 52.2%, and 94.9%, respectively. The additional evaluation with ML-based CT-FFR increased accuracy by Δ+3.4% (CAD+: Δ+6.0%) and raised the total number of examinations negative for CAD to 43.9% (202/460). CONCLUSIONS: ML-based CT-FFR may further improve the diagnostic performance of cCTA by correctly reclassifying a considerable proportion of patients with morphological signs of obstructive CAD on cCTA during pre-TAVR evaluation. Thereby, CT-FFR has the potential to further reduce the need for ICA in this challenging elderly group of patients before TAVR.

Combined Coronary CT-Angiography and TAVI Planning: Utility of CT-FFR in Patients with Morphologically Ruled-Out Obstructive Coronary Artery Disease.

Background: Coronary artery disease (CAD) is a frequent comorbidity in patients undergoing transcatheter aortic valve implantation (TAVI). If significant CAD can be excluded on coronary CT-angiography (cCTA), invasive coronary angiography (ICA) may be avoided. However, a high plaque burden may make the exclusion of CAD challenging, particularly for less experienced readers. The objective was to analyze the ability of machine learning (ML)-based CT-derived fractional flow reserve (CT-FFR) to correctly categorize cCTA studies without obstructive CAD acquired during pre-TAVI evaluation and to correlate recategorization to image quality and coronary artery calcium score (CAC). Methods: In total, 116 patients without significant stenosis (≥50% diameter) on cCTA as part of pre-TAVI CT were included. Patients were examined with an electrocardiogram-gated CT scan of the heart and high-pitch scan of the torso. Patients were re-evaluated with ML-based CT-FFR (threshold = 0.80). The standard of reference was ICA. Image quality was assessed quantitatively and qualitatively. Results: ML-based CT-FFR was successfully performed in 94.0% (109/116) of patients, including 436 vessels. With CT-FFR, 76/109 patients and 126/436 vessels were falsely categorized as having significant CAD. With CT-FFR 2/2 patients but no vessels initially falsely classified by cCTA were correctly recategorized as having significant CAD. Reclassification occurred predominantly in distal segments. Virtually no correlation was found between image quality or CAC. Conclusions: Unselectively applied, CT-FFR may vastly increase the number of false positive ratings of CAD compared to morphological scoring. Recategorization was virtually independently from image quality or CAC and occurred predominantly in distal segments. It is unclear whether or not the reduced CT-FFR represent true pressure ratios and potentially signifies pathophysiology in patients with severe aortic stenosis.

Texture analysis parameters derived from T1-and T2-weighted magnetic resonance images can reflect Ki67 index in soft tissue sarcoma.

BACKGROUND AND OBJECTIVES: Texture analysis derived from morphological magnetic resonance (MR) images might be associated with histopathology in tumors. The present study sought to elucidate possible associations between texture features derived from T1-and T2-weighted images with proliferation index Ki67 in soft tissue sarcomas. METHODS: Overall, 29 patients (n = 13, 44.8% female) with a median age of 52 years were included into this retrospective study. Several soft tissue sarcomas were investigated. Texture analysis was performed on pre-contrast T1-weighted and T2-weighted images using the free available Mazda software. RESULTS: The best correlation coefficients with Ki67 index were identified for the following parameters: T1-weighted images "45dgr_RLNonUni (p = 0.50, P = 0.006), T2-weighted images "S (4,0)SumAverg" (p = -0.45, P = 0.02). A ROC analysis was performed for Ki67-index with a threshold of 10%. The highest area under the curve (AUC) was found for the parameter "T1_WavEnHL_s-7" with an AUC of 0.90. For the threshold of Ki67 = 20% the highest AUC was identified for the parameter "T2_S (1,1)Entropy" with an AUC of 0.77. CONCLUSION: Several texture features derived from T1-and T2-weighted images correlated with proliferation index Ki67 and might be used as valuable novel biomarkers in soft tissue sarcomas.