Diagnosis Of Vascular Disease Research Articles

Effective diameter of the abdominal aorta in children.

Measure out of the standard interval in the aorta diameter is a clue for aortic aneurysm or hypoplasia. Pediatric studies focusing specifically on the normal diameter of the abdominal aorta (AA) were limited in the literature. Therefore, the main goal of this work was to determine changes in the effective diameter of AA in healthy children aged 1-18years for diagnosis of vascular diseases. This retrospective work focused on abdominopelvic computed tomography views of 180 children (sex: 90 males / 90 females, average age: 9.50 ± 5.20years) without any abdominopelvic disease to measure diameters of AA, common iliac artery (CIA), external iliac artery (EIA), and first lumbar vertebra (L1). Vessel and vertebra diameters increased in pediatric subjects between 1 and 18years (p < 0.001). Considering pediatric age periods, vessel diameters increased steadily, but L1 diameter showed an irregular growth pattern between age periods. All parameters were greater in males than females (p < 0.05), except from effective diameters of AA over the coeliac trunk (p = 0.084) and over the renal artery (p = 0.051). The ratios of diameters of vessels to L1 increased depending on ages between 1 and 18years. Considering pediatric age periods, the ratios increased from infancy period to postpubescent period in irregular pattern; however, the ratios for right and left CIA, and AA over the aortic bifurcation did not alter after late childhood period. All ratios for males were similar to females (p > 0.05). Our age-specific ratios may be beneficial for surgeons and radiologists for the diagnosis of vascular disorders such as aortic aneurysm.

Cross-modality cerebrovascular segmentation based on pseudo-label generation via paired data

Accurate segmentation of cerebrovascular structures from Computed Tomography Angiography (CTA), Magnetic Resonance Angiography (MRA), and Digital Subtraction Angiography (DSA) is crucial for clinical diagnosis of cranial vascular diseases. Recent advancements in deep Convolution Neural Network (CNN) have significantly improved the segmentation process. However, training segmentation networks for all modalities requires extensive data labeling for each modality, which is often expensive and time-consuming. To circumvent this limitation, we introduce an approach to train cross-modality cerebrovascular segmentation network based on paired data from source and target domains. Our approach involves training a universal vessel segmentation network with manually labeled source domain data, which automatically produces initial labels for target domain training images. We improve the initial labels of target domain training images by fusing paired images, which are then used to refine the target domain segmentation network. A series of experimental arrangements is presented to assess the efficacy of our method in various practical application scenarios. The experiments conducted on an MRA-CTA dataset and a DSA-CTA dataset demonstrate that the proposed method is effective for cross-modality cerebrovascular segmentation and achieves state-of-the-art performance.

Balloon angioplasty and stenting of lower extremity arteries in patients with critical limb ischemia

Lower extremity peripheral vascular disease is a typical, rapidly progressive, and disabling condition. In most patients, limb ischemia is detected at late stages of the disease. As a result, they are at high risk of limb loss, which makes a complete conventional treatment ineffective. In this situation, balloon angioplasty and stenting of lower extremity ar- teries are considered the optimal modern method of treating patients with critical limb ischemia. This study aims to evaluate the effectiveness of endovascular techniques to improve revascularization during the treatment of critical lower extremity ischemia. The research involved a comprehensive examination and endovascular treatment of 170 patients with occlusive-stenotic lesions of the lower extremity arteries. The patients were operated for critical ischemia between January 2016 and December 2022, and the effectiveness of the measures taken was analyzed. It was found that the pathology under the study requires timely diagnosis and identification of the severity of limb ischemia and circulatory disorders, with the subsequent preparation of an appropriate treatment plan. The authors discussed the main problems accompanying balloon angioplasty and stenting of the lower extremity arteries in patients with critical limb ischemia. Also, the experience of developed countries in the optimization and improvement of the studied tech- nique was studied. It has been proven that the diagnosis of lower extremity vascular disease is related to specific difficulties. However, it can be made on an outpatient basis by analyzing medical examination data and simple labor- atory methods. The authors also examined the feasibility and prospects of balloon angioplasty and stenting of the lower extremity arteries in patients with critical limb ischemia. The re-search findings have a practical value for improving the treatment of patients with occlusive and stenotic lesions of the lower extremities, as well as for improving the effec-tiveness of balloon angioplasty and stenting.

Discussion on pathological diagnosis of vascular diseases based on ISSVA classification

The diagnosis of vascular diseases is not only about distinguishing neoplastic or non-neoplastic lesions, but also focusing more on emphasizing the essence of the disease, namely the presence or absence of endothelial cell proliferation, and further to distinguishing true hemangioma tumors or vascular malformation. This article is based on the International Society for the Study of Vascular Anomalies (ISSVA) classification, which is widely used in clinical practice, and discusses the related pathological diagnosis issues of vascular diseases.

Diabetic Foot Ulcer Management and Treatment: An Overview of Published Patents.

One of the most challenging effects of diabetes is diabetic foot ulceration (DFU). DFU may occur in up to one-third of individuals with diabetes mellitus (D.M.) at some point in their lives. The major cause of morbidity in D.M. patients is DFU. The length of treatment is difficult, and DFU recurrence is common. The most crucial element for the treatment and prevention of DFUs require a multidisciplinary approach. Patients who are at risk should be identified, depending on the type of risk, prophylactic actions etc. It is imperative to identify at-risk patients and take preventative measures accordingly. The at-risk diabetes-related foot ulcer was identified based on the risk category classification, while the foot ulcers were evaluated using Wagner's classification system. Literature reported that patients with lower limb vascular insufficiency, loss of vibratory sensation, or protective sensation loss have an increased risk of developing foot ulcers. Proper categorization and therapeutic measures will be implemented after the DFU has been formed. The appropriate assessment and management of general health status should include glycemic control, the diagnosis and treatment of vascular disease, standard care for wounds, diagnosis, and infection treatments. The review reflects the updated awareness of the treatment and management of DFU based on the current and past literature and patent analysis.

Vascular Disease Patient Information Page: Coping with a serious vascular disease diagnosis.

Vascular Disease Patient Information Page: Coping with a serious vascular disease diagnosis.

Photoacoustic imaging of peripheral vessels in extremities by large-scale synthetic matrix array.

Various peripheral vascular diseases (PVD) in extremities, such as arterial atherosclerosis or venous occlusion in arm or legs, are a serious global health threat. Noninvasive vascular imaging is of great value for both diagnosis and assessment of PVD. By scanning a one-dimensional non-focusing linear array, an equivalent large two-dimensional (2D) matrix array with hundreds of thousands or more ultrasound elements is formed, thereby achieving a wide signal reception angle as well as large imaging area for three-dimensional (3D) imaging of peripheral extremities. To provide a feasible bedside and noninvasive imaging method for vascular imaging in extremities. Our system can achieve high-quality photoacoustic (PA) peripheral vessel imaging. The 3D subcutaneous vascular imaging results of the palms and arms of healthy volunteers demonstrate the superior performance of the system. This work proposes a clinically oriented PA 3D subcutaneous vascular imaging system for human extremities. The system employs a synthetic matrix array via scanning a one-dimensional non-focusing linear probe, providing noninvasive, high-resolution, and high-contrast images of human extremities. It has potential application value in the diagnosis and monitoring of vascular diseases.

An intravascular optical coherence tomography technique for in vivo carotid intima-media thickness measurement and mechanical characterization

Arterial characteristic parameters including the intima-media thickness (IMT), strain, strain rate, elastic modulus, and compliance may be unevenly distributed due to local lesion growth. Thus, a combination of the full-field distribution of these parameters may provide more effective guidance for the diagnosis and treatment of vascular diseases than either one of them. Here, we develop an intravascular coherence tomography (IVOCT) based full-field measurement method to characterize the mechanical properties of carotid artery in vivo. Image processing methods are proposed based on U-Net model and centroid detection for accurate IMT measurement. The strain, strain rate, incremental elastic modulus and volumetric compliance are obtained based on the geometric changes of intima-media. Ex vivo silica gel phantom tests demonstrate the accuracy of the vascular wall segmentation by the U-Net based method is greater than 92%, and the error for elastic modulus measurement is less than 2%. A porcine carotid artery was imaged by IVOCT in vivo, and the IMT and the mechanical characteristics during cardiac cycle were measured. The proposed method facilitates the study of the uneven pathological evolution of the vascular wall and provides an effective measurement method for the study of vascular mechanical properties in vivo.

Clinical application of intravascular forceps biopsy in the diagnosis of vascular obstructive diseases: a pilot study.

The sampling of vascular obstruction diseases remains a challenge in clinical practice. This retrospective study aimed to evaluate the feasibility, accuracy, and safety of intravascular forceps biopsy (IVFB) for the diagnosis of vascular obstructive diseases. From January 2015 to January 2022, of the total of 35 patients who underwent IVFB (21 male, 14 female; mean age 60±11 years; range, 39-81 years), 32 (91.4%) did so during interventional planned revascularization procedures and 3 (8.6%) did so due so due to inaccessible or failed percutaneous access. The outcomes of technical success, biopsy times, patient radiation dose (PRD), complications, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy rate (AR) were analyzed. The technical success of IVFB was 100%. The median number of biopsies taken per biopsy session and PRD were 4.0 (range, 3-6) and 712.6 mGy (range, 383.4-1,450.8), respectively. The sensitivity, specificity, PPV, NPV, and AR of IVFB were 87.5% (21/24), 100% (11/11), 100% (21/21), 78.6% (11/14), and 91.4% (32/35), respectively. There were no complications related to IVFB. IVFB is a technically feasible and safe technique with good diagnostic value. The procedure should be considered in patients who are not suitable for percutaneous access, show indistinct imaging characteristics, or are scheduled to undergo revascularization procedure.

DopUS-Net: Quality-Aware Robotic Ultrasound Imaging Based on Doppler Signal

Medical ultrasound (US) is widely used to evaluate and stage vascular diseases, in particular for the preliminary screening program, due to the advantage of being radiation-free. However, automatic segmentation of small tubular structures (e.g., the ulnar artery) from cross-sectional US images is still challenging. To address this challenge, this paper proposes the DopUS-Net and a vessel re-identification module that leverage the Doppler effect to enhance the final segmentation result. Firstly, the DopUS-Net combines the Doppler images with B-mode images to increase the segmentation accuracy and robustness of small blood vessels. It incorporates two encoders to exploit the maximum potential of the Doppler signal and recurrent neural network modules to preserve sequential information. Input to the first encoder is a two-channel duplex image representing the combination of the grey-scale Doppler and B-mode images to ensure anatomical spatial correctness. The second encoder operates on the pure Doppler images to provide a region proposal. Secondly, benefiting from the Doppler signal, this work first introduces an online artery re-identification module to qualitatively evaluate the real-time segmentation results and automatically optimize the probe pose for enhanced Doppler images. This quality-aware module enables the closed-loop control of robotic screening to further improve the confidence and robustness of image segmentation. The experimental results demonstrate that the proposed approach with the re-identification process can significantly improve the accuracy and robustness of the segmentation results (Dice score: from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.54$</tex-math> </inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.86$</tex-math> </inline-formula> ; intersection over union: from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.47$</tex-math> </inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.78$</tex-math> </inline-formula> ). <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The Doppler signal is important for the diagnosis of vascular disease, e.g., peripheral arterial disease, in clinical practices, nevertheless it is not of similar significance for state-of-the-art robotic ultrasound (US) examination systems yet. This paper explores various neural network structures to effectively extract the blood vessels from US images by incorporating the Doppler signal into the segmentation process. The final DopUS structure with two encoders extracting differentiated information from two different inputs and fusing the latent feature representations in the bottleneck layer can also inspire other tasks like multi-senor fusion. In addition, this work developed a Doppler-based tracker to assess the quality of the segmentation results in real-time. The assessment is subsequently used for a quality-aware module that enables closed-loop control of the robotic screening. Preliminary physical experiments suggest that the quality-aware robotic screening system can improve the confidence and robustness of autonomous US examination results. In the future, the Doppler signal could also be used to support clinical diagnosis. We believe the proposed quality-aware autonomous screening system is important for the development of large-scale robotic US screening programs. It will not only benefit the examination of limb arteries but also other vascular structures, e.g., carotid or aorta.

Volumetric B-mode ultrasound and Doppler Imaging: Automatic Tracking With One Single Camera.

Vascular diseases may occur in the upper extremities, and the lesions can span the entire length of the blood vessel. One of the most popular methods to identify vascular disorders is ultrasound Doppler imaging. However, traditional two-dimensional (2D) ultrasound Doppler imaging cannot capture the entire length of a long vessel in one image. Medical professionals often have to painstakingly reconstruct three-dimensional (3D) data using 2D ultrasound images to locate the lesions, especially for large blood vessels. 3D ultrasound Doppler imaging can display the morphological structure of blood vessels and the distribution of lesions more directly, providing a more comprehensive view compared to 2D imaging. In this work, we propose a wide-range 3D volumetric ultrasound Doppler imaging system with dual modality, in which a high-definition camera is adopted to automatically track the movement of the ultrasound transducer, simultaneously capturing a corresponding sequence of 2D ultrasound Doppler images. We conducted experiments on human arms using our proposed system and separately with X-ray computerized tomography (X-CT). The comparison results prove the potential value of our proposed system in the diagnosis of arm vascular diseases.

Clinical characteristics associated with elevated levels of lipoprotein(a) in patients with vascular risk.

Lipoprotein(a) (Lp(a)) is increasingly used in the evaluation of patients with vascular risk due to its association with cardiovascular events. The purpose of this study was to identify the clinical characteristics of patients with elevated levels of Lp(a) attended in an outpatient vascular risk unit. An observational, retrospective study was conducted to assess the clinical characteristics of patients with elevated levels of Lp(a) (≥50 mg/dL), as compared to patients with normal values (<50 mg/dL). The sample was composed of 878 patients identified as having a high vascular risk due to a diagnosis of vascular disease, attended in a vascular risk unit between 2021 and 2022. The highest levels of Lp(a) were independently associated with a higher probability of having a history of peripheral arterial disease (p=0.024), polygenic familial hypercholesterolemia (PH, p=0.030) and combined familial hypercholesterolemia (CFH, p=0.015); and using PCSK9 inhibitor treatment (p=0.029) and combination therapy with statins and ezetimibe (p=0.018). In contrast, there were no significant differences in relation to familial history of early cardiovascular disease (p=0.143) or personal history of cardiovascular disease (p=0.063), which contrasts with other series. Elevated levels of Lp(a) were associated with a history of peripheral arterial disease, diagnosis of FHP and CFH, and need for more intense lipid-lowering treatments.

Photoacoustic vector tomography for deep haemodynamic imaging.

Imaging deep haemodynamics non-invasively remains a quest. Although optical imaging techniques can be used to measure blood flow, they are generally limited to imaging within ∼1 mm below the skin's surface. Here we show that such optical diffusion limit can be broken through by leveraging the spatial heterogeneity of blood and its photoacoustic contrast. Specifically, successive single-shot wide-field photoacoustic images of blood vessels can be used to visualize the frame-to-frame propagation of blood and to estimate blood flow speed and direction pixel-wise. The method, which we named photoacoustic vector tomography (PAVT), allows for the quantification of haemodynamics in veins more than 5 mm deep, as we show for regions in the hands and arms of healthy volunteers. PAVT may offer advantages for the diagnosis and monitoring of vascular diseases and for the mapping of the function of the circulatory system.

Prevalence of carotid artery calcification detected by different dental imaging techniques and their relationship with cardiovascular risk factors, age and gender

BackgroundAtherosclerosis and its secondary diseases display a major threat to patient’s health. Sequelae, like carotid artery calcification (CAC), usually develop over decades and remain asymptomatic for a long time, making preventive measures to reduce mortality and morbidity extremely important. Through panoramic radiography (PR) and cone beam computed tomography (CBCT), dentists may have helpful tools in aiding the holistic care of patients. In this context, the correlation of atherosclerotic risk factors and CAC development have not yet been sufficiently investigated. Thus, the aim of this observational radiological study was to evaluate the diagnostic value of PR compared with CBCT for the detection of CAC in patients older than 60 years. The radiological findings were correlated with gender, age, and cardiac risk factors.MethodsPRs and CBCTs of N = 607 patients were used for the qualitative analysis and compared. Basic patient information such as age, gender, body mass index (BMI), smoking history as well as patient’s detailed medical history, including heart disease and cardiovascular risk factors such as hypercholesterolemia, arterial hypertension and diabetes mellitus type II were documented and their relation to CAC provided by radiological data was estimated in the form of odds ratios (OR), which were calculated using logistic regression models. Proportions of CAC in different risk groups were compared using Fisher’s exact test, the significance level was set to α ≤ 0.05. The interrater reliability of two physicians was estimated using Cohen’s kappa.ResultsWith an accuracy of 90.6%, a sensitivity of 67.5% and a specificity of 99.5% compared to CBCT, PR was a reliable method for the diagnosis of CAC. The overall detection rate for CAC was 27.8% across all age groups. Age (OR: 1.351; p = 0.021), the male sex (OR: 1.645; p = 0.006), arterial hypertension (OR: 2.217; p = < 0.001), heart disease (OR: 1.675; p = 0.006), hypercholesterolemia (OR: 1.904; p = 0.003) and chronic obstructive pulmonary disease (OR: 2.016; p = 0.036) were statistically significant risk factors. When correlated, neither history of stroke nor nicotine abuse showed any statistical significance.ConclusionsDue to the capabilities of PR in the diagnosis of CAC, dentists can play a vital role in the early diagnosis of vascular disease. Awareness should therefore be raised among dentists regarding the detection of CAC in patients over 60 years of age, with a particular focus on those with arterial hypertension and hypercholesterolaemia.

Features of cognitive impairment and anxiety-depressive disorders in patients in the acute period of stroke

Introduction. Cognitive impairment after a stroke remains one of the leading causes of disability. Despite the introduction of new methods of treatment, diagnosis, and prevention of acute vascular diseases, more than 50 % of patients experience cognitive disorders after a stroke, a third of which reach a severe degree of dementia. The purpose of the study is to identify and assess risk factors for the development of cognitive impairment disorders in patients after a stroke and evaluate the impact of anxiety and depressive phenomena on their course. Materials and methods. The combined retro-prospective study included 40 patients with mild stroke according to the NIHSS. The diagnosis of stroke in all subjects was verified based on the results of MSCT of the brain. All patients underwent a comprehensive clinical and laboratory monitoring: a general examination; an assessment of neurological and functional status; an assessment of cognitive functions and mental status by MMSE scale and the Frontal Assessment Battery; an assessment of anxiety-depressive disorders by the Spielberger State-Trait Anxiety Inventory, the Beck Depression Inventory, and the Hamilton Rating Scale. The influence of individual risk factors on the development of cognitive impairment was evaluated. Results. More than 80 % of the patients with mild stroke in the acute period experienced a decrease in cognitive functions, while 62 % of the subjects showed signs of frontal dementia of varying severity. In the presence of high comorbidity with forms of the circulatory system pathologies (hypertension, diabetes, atrial fibrillation, coronary heart disease), there was a high frequency of both frontal dementia (in 87 % of the patients), and a decrease in cognitive functions on the MMSE scale (67 % of cases). All patients were diagnosed with depression, and half of them — with severe depression. 80 % of the patients with severe depression had severe cognitive changes on the MMSE scale, and 75 % had severe frontal dysfunction. Conclusion. Thus, high vascular comorbidity and the presence of anxiety and depressive disorders are significant risk factors for the development of cognitive impairment after a stroke. In this regard, measures aimed at their timely detection, treatment, and correction will make it possible to effectively reduce the incidence of post-stroke cognitive impairment, which, in turn, will improve the quality of life not only for the patients themselves but also for their relatives.

Liver Transplantation in a Woman with Mahvash Disease

SummaryMahvash disease is an exceedingly rare genetic disorder of glucagon signaling characterized by hyperglucagonemia, hyperaminoacidemia, and pancreatic α-cell hyperplasia. Although there is no known definitive treatment, octreotide has been used to decrease systemic glucagon levels. We describe a woman who presented to our medical center after three episodes of small-volume hematemesis. She was found to have hyperglucagonemia and pancreatic hypertrophy with genetically confirmed Mahvash disease and also had evidence of portal hypertension (recurrent portosystemic encephalopathy and variceal hemorrhage) in the absence of cirrhosis. These findings established a diagnosis of portosinusoidal vascular disease, a presinusoidal type of portal hypertension previously known as noncirrhotic portal hypertension. Liver transplantation was followed by normalization of serum glucagon and ammonia levels, reversal of pancreatic hypertrophy, and resolution of recurrent encephalopathy and bleeding varices.

C-DARL: Contrastive diffusion adversarial representation learning for label-free blood vessel segmentation

Blood vessel segmentation in medical imaging is one of the essential steps for vascular disease diagnosis and interventional planning in a broad spectrum of clinical scenarios in image-based medicine and interventional medicine. Unfortunately, manual annotation of the vessel masks is challenging and resource-intensive due to subtle branches and complex structures. To overcome this issue, this paper presents a self-supervised vessel segmentation method, dubbed the contrastive diffusion adversarial representation learning (C-DARL) model. Our model is composed of a diffusion module and a generation module that learns the distribution of multi-domain blood vessel data by generating synthetic vessel images from diffusion latent. Moreover, we employ contrastive learning through a mask-based contrastive loss so that the model can learn more realistic vessel representations. To validate the efficacy, C-DARL is trained using various vessel datasets, including coronary angiograms, abdominal digital subtraction angiograms, and retinal imaging. Experimental results confirm that our model achieves performance improvement over baseline methods with noise robustness, suggesting the effectiveness of C-DARL for vessel segmentation.Our source code is available at https://github.com/boahK/MEDIA_CDARL.22This paper extends the work (Kim et al., 2023) presented at the Eleventh International Conference on Learning Representations (ICLR) 2023.

MedGCN: An IoT-edge thrombus graph convolutional network for accurate prediction and prescription diagnosis of vascular occlusive diseases from unstructured clinical reports

The timely and accurate prediction and diagnosis of vascular occlusive diseases are pivotal in enhancing patient outcomes. This research addresses this critical healthcare challenge by introducing MedGCN, a novel thrombus graph convolutional network model. MedGCN is specifically designed for the precise prediction of prescriptions and diagnoses based on unstructured clinical diagnostic reports. The model synergistically blends OpenAI’s GPT4 and a uniquely designed Cross Fusion Graph Convolutional Network (CF-GCN) to ensure the meticulous fusion of knowledge. We delve into nine distinct learning tasks, encompassing both prescription and diagnosis and employ a multi-label classification GCN pretraining technique to assess them. Our evaluation underscores MedGCN’s robust predictive prowess across various tasks. By amalgamating cutting-edge AI paradigms with IoT edge computing, this research not only bolsters the efficacy of medical decision-making but also champions patient privacy. The methodologies and findings presented herein hold immense potential for deployment in IoT frameworks, thus proffering swift and precise assistance in medical decision-making and addressing a paramount need in the contemporary healthcare landscape.

Ocular and eyelid involvement in collagen vascular diseases. Part II. Dermatomyositis, scleroderma, and sarcoidosis

Collagen vascular disease is a heterogeneous group of autoimmune diseases that affect multiple organ systems. Sjögren syndrome, dermatomyositis, scleroderma, systemic lupus erythematosus, and sarcoidosis are collagen vascular diseases that often present with characteristic cutaneous manifestations. Although less known, various ocular manifestations that affect both external and internal structures of the eye can also be seen in these conditions. Multidisciplinary management between dermatologists and ophthalmologists is essential in the early diagnosis and management of collagen vascular diseases affecting both the skin and eye. In part II of our series, we discuss the ocular manifestations, diagnosis, and therapeutic options of dermatomyositis, scleroderma, and sarcoidosis.

Exploring a frequency-domain attention-guided cascade U-Net: Towards spatially tunable segmentation of vasculature

Developing fully automatic and highly accurate medical image segmentation methods is critically important for vascular disease diagnosis and treatment planning. Although advances in convolutional neural networks (CNNs) have spawned an array of automatic segmentation models converging to saturated high performance, none have explored whether CNNs can achieve (spatially) tunable segmentation. As a result, we propose multiple attention modules from a frequency-domain perspective to construct a unified CNN architecture for segmenting vasculature with desired (spatial) scales. The proposed CNN architecture is named frequency-domain attention-guided cascaded U-Net (FACU-Net). Specifically, FACU-Net contains two innovative components: (1) a frequency-domain-based channel attention module that adaptively tunes channel-wise feature responses and (2) a frequency-domain-based spatial attention module that enables the deep network to concentrate on foreground regions of interest (ROIs) effectively.Furthermore, we devised a novel frequency-domain-based content attention module to enhance or weaken the high (spatial) frequency information, allowing us to strengthen or eliminate vessels of interest. Extensive experiments using clinical data from patients with intracranial aneurysms (IA) and abdominal aortic aneurysms (AAA) demonstrated that the proposed FACU-Net met its design goal. In addition, we further investigated the association between varying (spatial) frequency components and the desirable vessel size/scale attributes. In summary, our preliminary findings are encouraging, and further developments may lead to deployable image segmentation models that are spatially tunable for clinical applications.