Ahmed Othman

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Verified

Ahmed verified their affiliation via an institutional email.

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• MD
• University Professor and Physician at Universitätsmedizin der Johannes Gutenberg-Universität Mainz

To examine the impact of denoising on ultra-low-dose volume perfusion CT (ULD-VPCT) imaging in acute stroke. Simulated ULD-VPCT data sets at 20 % dose rate were generated from perfusion data sets of 20 patients with suspected ischemic stroke acquired at 80 kVp/180 mAs. Four data sets were generated from each ULD-VPCT data set: not-denoised (ND); de...

To examine the influence of radiation dose reduction on image quality and sensitivity of Volume Perfusion CT (VPCT) maps regarding the detection of ischemic brain lesions. VPCT data of 20 patients with suspected ischemic stroke acquired at 80 kV and 180 mAs were included. Using realistic reduced-dose simulation, low-dose VPCT datasets with 144 mAs,...

To evaluate the suitability of whole body Ultralow-dose CT (ULD-CT) as a diagnostic tool for the evaluation of ventriculoperitoneal shunt (VP-shunt) complications with special regards to radiation dose and image quality. Fourteen VP-shunts were implanted in 7 swine cadavers (weight: 55-70 kg). Twenty-two mechanical complications (extracranial and e...

Background Numerous scoring systems have been developed to individualize estimation of functional outcome after endovascular thrombectomy (EVT) of acute ischemic stroke. The aim of our study was to assess their utility for clinical practice based on a large cohort from real-world care of EVT. Methods For 13 082 patients included in the German Stro...

Aim Post-stroke-delirium has been linked to worse outcome in patients with acute cerebrovascular disease; identification of individuals at risk may prevent delirium and thereby improve outcome. We investigate prognosis and factors associated with post-stroke-delirium in patients with large vessel occlusion (LVO) ischemic stroke treated by mechanica...

Online survey about the current status of CT protocols in hepatocellular carcinoma (HCC) in the year 2023/2024. Moreover, the usage of structured reporting using LI-RADS and mRECIST was surveyed and the results were compared with a survey from 2020. Radiologists working in outpatient or inpatient care in Germany were invited. The survey was conduct...

Objectives The aim of this study was to investigate the occurrence of motion artifacts and image quality of brain magnetic resonance imaging (MRI) T1-weighted imaging applying 3D motion correction via the Scout Accelerated Motion Estimation and Reduction (SAMER) framework compared with conventional T1-weighted imaging at 1.5 T. Materials and Metho...

Background Intrasaccular devices are increasingly used in endovascular therapy of intracranial aneurysms, in particular wide-necked and ruptured aneurysms. The Trenza Embolization Device (TED) is an innovative intrasaccular device for medium- to large-sized aneurysms. Currently, literature about the TED is scarce. Methods In eight participating Eu...

Over time, the distribution of medical image data drifts due to multiple factors, including shifts in patient demographics, acquisition devices, and disease manifestation. While human radiologists can extrapolate their knowledge to such changes, AI systems cannot. In fact, deep learning models are highly susceptible to even slight variations in ima...

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Background Several factors are frequently considered for outcome prediction rin stroke patients. We assessed the value of digital subtraction angiography (DSA)-based brain perfusion measurements after mechanical thrombectomy (MT) for outcome prediction in acute ischaemic stroke. Methods From DSA image data ( n = 90; 38 females; age 73.3 ± 13.1 yea...

Objectives: To evaluate the performance of a custom-made convolutional neural network (CNN) algorithm for fully automated lesion tracking and segmentation, as well as RECIST 1.1 evaluation, in longitudinal computed tomography (CT) studies compared to a manual Response Evaluation Criteria in Solid Tumors (RECIST 1.1) evaluation performed by three ra...

Intracranial Hemorrhage is a potentially lethal condition whose manifestation is vastly diverse and shifts across clinical centers worldwide. Deep-learning-based solutions are starting to model complex relations between brain structures, but still struggle to generalize. While gathering more diverse data is the most natural approach, privacy regula...

To evaluate the current status of the diagnosis of gastrointestinal tumors in Germany by means of a survey of the oncological imaging working group of the German Radiological Society (DRG) with a focus on the CT protocols being used. Radiologists working in outpatient or inpatient care in Germany were invited. The survey was conducted between 10/20...

Background We evaluated the capability of an AI application to independently detect, segment and classify intracranial tumors in MRI. Methods In this retrospective single-centre study, 138 patients (65 female and 73 male) with a mean age of 35 ± 26y were included. 97 were diagnosed with an intracranial neoplasm, while 41 exhibited no intracranial...

MRI is a non-invasive and cost-effective technique that uses magnetic fields to create images of the brain. Structural MRI is based on the fact that biological tissues have high water content. MR images provide high-resolution anatomical information with great contrast of both the gray matter (GM) and the white matter (WM). Advanced imaging and ana...

Background Neuroborreliosis is a tick-borne condition that affects the central and/or peripheral nervous system. Cerebral infarction associated with neuroborreliosis-related vasculitis has been reported in only a handful of cases. Therefore, specific patterns of vascular pathology and prognostic outcome factors in these patients are still incomplet...

Preoperative identification of intracranial meningiomas with aggressive behaviour may help in choosing the optimal treatment strategy. Radiomics is emerging as a powerful diagnostic tool with potential applications in patient risk stratification. In this study, we aimed to compare the predictive value of conventional, semantic based and radiomic an...

Introduction Intrasaccular devices are an increasingly recognized option in endovascular therapy of cerebral aneurysms, in particular in wide-necked and ruptured aneurysms. The Trenza Embolization Device (TED) is a novel intrasaccular device. Literature about TED is scarce, as the prospective post-market multicenter study TREAT is currently still r...

Whole-body CT is used for multi-trauma patients in the search of any and all injuries. Since an initial assessment needs to be rapid and the search for lesions is done for the whole body, very little time can be allocated for the inspection of a specific anatomy. In particular, intracranial hemorrhages are still missed, especially by clinical stude...

Background A study was undertaken to assess the effectiveness of open-source large language models (LLMs) in extracting clinical data from unstructured mechanical thrombectomy reports in patients with ischemic stroke caused by a vessel occlusion. Methods We deployed local open-source LLMs to extract data points from free-text procedural reports in...

Patients with Intracranial Hemorrhage (ICH) face a potentially life-threatening condition, and patient-centered individualized treatment remains challenging due to possible clinical complications. Deep-Learning-based methods can efficiently analyze the routinely acquired head CTs to support the clinical decision-making. The majority of early work f...

Diffusion‐based tractography in the optic nerve requires sampling strategies assisted by anatomical landmark information (regions of interest [ROIs]). We aimed to investigate the feasibility of expert‐placed, high‐resolution T1‐weighted ROI‐data transfer onto lower spatial resolution diffusion‐weighted images. Slab volumes from 20 volunteers were a...

Background: The prevalence of metastatic melanoma is increasing, necessitating the identification of patients who do not benefit from immunotherapy. This study aimed to develop a radiomic biomarker based on the segmentation of all metastases at baseline and the first follow-up CT for the endpoints best overall response (BOR), progression-free surv...

Objective To investigate whether choroid plexus volumes in subacute coronavirus disease 2019 (COVID‐19) patients with neurological symptoms could indicate inflammatory activation or barrier dysfunction and assess their association with clinical data. Methods Choroid plexus volumes were measured in 28 subacute COVID‐19 patients via cerebral magneti...

Objectives Achieving a consensus on a definition for different aspects of radiomics workflows to support their translation into clinical usage. Furthermore, to assess the perspective of experts on important challenges for a successful clinical workflow implementation. Materials and methods The consensus was achieved by a multi-stage process. Stage...

Purpose AI-assisted techniques for lesion registration and segmentation have the potential to make CT-based tumor follow-up assessment faster and less reader-dependent. However, empirical evidence on the advantages of AI-assisted volumetric segmentation for lymph node and soft tissue metastases in follow-up CT scans is lacking. The aim of this stud...

Invasive dental procedures, such as wisdom teeth removal, have been identified as potential triggers for vascular events due to the entry of oral bacteria into the bloodstream, leading to acute vascular inflammation and endothelial dysfunction. This study presents the case of a 27-year-old healthy male who developed ischemic stroke resulting from b...

To evaluate the effect of a vendor-agnostic deep learning denoising (DLD) algorithm on diagnostic image quality of non-contrast cranial computed tomography (ncCT) across five CT scanners. This retrospective single-center study included ncCT data of 150 consecutive patients (30 for each of the five scanners) who had undergone routine imaging after m...

The choroid plexus (ChP) plays a crucial function in neuroinflammation of the central nervous system and in the immune response of the brain during neurodegeneration. Recent studies described a massive ChP enlargement in patients with multiple sclerosis (MS) and active disease courses, but also in several other neuroinflammatory and neurodegenerati...

Purpose The objective of this study was to implement a 5-minute MRI protocol for the shoulder in routine clinical practice consisting of accelerated 2D turbo spin echo (TSE) sequences with deep learning (DL) reconstruction at 1.5 and 3 Tesla, and to compare the image quality and diagnostic performance to that of a standard 2D TSE protocol. Methods...

Objectives A hard lockdown was presumed to lead to delayed diagnosis and treatment of serious diseases, resulting in higher acuity at admission. This should be elaborated based on the estimated acuity of the cases, changes in findings during hospitalisation, age structure and biological sex. Design Retrospective monocentric cross-sectional study....

Background Deep learning (DL)-accelerated MRI can substantially reduce examination times. However, studies prospectively evaluating the diagnostic performance of DL-accelerated MRI reconstructions in acute suspected stroke are lacking. Purpose To investigate the interchangeability of DL-accelerated MRI with conventional MRI in patients with suspect...

Purpose To compare the image quality and diagnostic capability in detecting malignant liver tumors of low-dose CT (LDCT, 33% dose) with deep learning-based denoising (DLD) and standard-dose CT (SDCT, 100% dose) with model-based iterative reconstruction (MBIR). Materials and Methods In this prospective, multicenter, noninferiority study, individuals...

Background Checkpoint inhibitors have drastically improved the therapy of patients with advanced melanoma. 18F-FDG-PET/CT parameters might act as biomarkers for response and survival and thus can identify patients that do not benefit from immunotherapy. However, little literature exists on the association of baseline 18F-FDG-PET/CT parameters with...

Emerging from the development of single-energy Computed Tomography (CT) and Dual-Energy Computed Tomography, Multi-Energy Computed Tomography (MECT) is a promising tool allowing advanced material and tissue decomposition and thereby enabling the use of multiple contrast materials in preclinical research. The scope of this work was to evaluate wheth...

Simple Summary Despite the benign nature of these tumors, spinal meningiomas can cause significant neurological damage via compression of the spinal cord. In this study, we found that neurological function improves in a significant proportion of patients after surgery. Preoperative Frankel grade was a significant predictor of postoperative neurolog...

Background: The aim of this study was to investigate whether the combination of radiomics and clinical parameters in a machine-learning model offers additive information compared with the use of only clinical parameters in predicting the best response, progression-free survival after six months, as well as overall survival after six and twelve mon...

Objective To evaluate diagnostic image quality of ultra-high-resolution computed tomography angiography (UHR-CTA) in neurovascular imaging as compared to normal resolution CT-angiography (NR-CTA). Material and Methods In this retrospective single-center study brain and neck CT-angiography was performed using an ultra-high-resolution computed tomog...

Objective Mechanical thrombectomy (MT) has become standard treatment in acute ischemic stroke due to large vessel occlusion (LVO). However, optimal blood pressure (BP) management following successful recanalization remains unclear. We aim to investigate the association of strictly achieving BP targets of ≤160/90 mmHg with the extent of neuronal los...

The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural network...

Purpose The aim of this study was to evaluate the image quality and feasibility of a field map-based technique to correct for susceptibility-induced geometric distortions which are typical for diffusion EPI brain imaging. Methods We prospectively included 52 patients during clinical routine in this single-center study. All scans were performed on...

Objectives: Gender differences have been reported to influence medical training. We investigated gender differences encountered during training in interventional radiology maneuvers. Methods: Catheter handling was analyzed under standardized conditions in 64 participants naïve to endovascular procedures (26 women, 38 men). Objective (e.g., cathe...

Background Missing outcome data (MOD) is a common problem in clinical trials and registries, and a potential bias when drawing conclusions from these data. Identifying factors associated with MOD may help to increase follow-up rates and assess the need for imputation strategies. We investigated MOD in a multicenter, prospective registry study of me...

Diffusion-weighted images of the prostate can suffer from a “hazy” background in low signal-intensity areas. We hypothesize that enhanced image processing (EIP) using complex averaging reduces artifacts, noise, and distortion in conventionally acquired diffusion-weighted images and synthesized high b-value images, thus leading to higher image quali...

Background: Hybrid MRI linear accelerators (MR-Linac) might enable individualized online adaptation of radiotherapy using quantitative MRI sequences as diffusion-weighted imaging (DWI). The purpose of this study was to investigate the dynamics of lesion apparent diffusion coefficient (ADC) in patients with prostate cancer undergoing MR-guided radi...

(1) Background: To predict clinical outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH) and delayed cerebral ischemia (DCI) by assessment of the cerebral perfusion using a 2D perfusion angiography (2DPA) time–contrast agent (CA) concentration model. (2) Methods: Digital subtraction angiography (DSA) data sets of n = 26 subjects were...

As the enthusiasm surrounding Deep Learning grows, both medical practitioners and regulatory bodies are exploring ways to safely introduce image segmentation in clinical practice. One frontier to overcome when translating promising research into the clinical open world is the shift from static to continual learning. Continual learning, the practice...

Background: Type 2 diabetes mellitus (DM) is the most common metabolic disorder in the world and an important risk factor for peripheral arterial disease (PAD). CT angiography represents the method of choice for the diagnosis, pre-operative planning, and follow-up of vascular disease. Low-energy dual-energy CT (DECT) virtual mono-energetic imaging...

Rationale and objectives: To evaluate clinical feasibility and image quality of a comprehensive ultrafast brain MRI protocol with multi-shot echo planar imaging and deep learning-enhanced reconstruction at 1.5T. Materials and methods: Thirty consecutive patients who underwent clinically indicated MRI at a 1.5 T scanner were prospectively include...

Objectives: To assess the benefits of ultra-high-resolution CT (UHR-CT) with deep learning-based image reconstruction engine (AiCE) regarding image quality and radiation dose and intraindividually compare it to normal-resolution CT (NR-CT). Methods: Forty consecutive patients with head and neck UHR-CT with AiCE for diagnosed head and neck malign...

Rationale and objectives: To prospectively evaluate feasibility and robustness of an accelerated T2 mapping sequence (GRAPPATINI) in brain imaging and to assess its synthetic T2-weighted images (sT2w) in comparison with a standard T2-weighted sequence (T2 TSE). Material and methods: Volunteers were included to evaluate the robustness and consecu...

Purpose Successful utilization of anatomical templates in the evaluation of diffusion-weighted neuroimaging-studies requires accurate registration of intra-individual datasets. We investigated the feasibility of structural MRI image registration onto single-shot and read-out segmented echo-planar diffusion-weighted imaging variants for use in tract...

Background Arterial spin labeling (ASL) MRI can be used to assess organ perfusion but has yet to be implemented for perfusion evaluation of the lung. Purpose To evaluate pseudo-continuous ASL (PCASL) MRI for the detection of acute pulmonary embolism (PE) and its potential as an alternative to CT pulmonary angiography (CTPA). Materials and Methods B...

Due to its high morbidity and mortality, myocardial infarction is the leading cause of death worldwide. Against this background, rapid diagnosis is of immense importance. Especially in case of an atypical course, the correct diagnosis may be delayed and thus lead to increased mortality rates. In this report, we present a complex case of acute coron...

Purpose: To evaluate the effects of single-energy metal artifact reduction (SEMAR) on image quality of ultra-high-resolution CT-angiography (UHR-CTA) with intracranial implants after aneurysm treatment. Methods: Image quality of standard and SEMAR-reconstructed UHR-CT-angiography images of 54 patients who underwent coiling or clipping was retros...

Rationale and objectives: Magnetic resonance imaging (MRI) of the hand and wrist is a routine MRI examination and takes about 15-20 minutes, which can lead to problems resulting from the relatively long scan time, such as decreased image quality due to motion artifacts and lower patient throughput. The objective of this study was to evaluate a dee...

Purpose: Magnetic resonance imaging (MRI) scan time remains a limited and valuable resource. This study evaluates the diagnostic performance of a deep learning (DL)-based accelerated TSE study protocol compared to a standard TSE study protocol in ankle MRI. Material and methods: Between October 2020 and July 2021 forty-seven patients were enroll...

Objectives: CT low-dose simulation methods have gained significant traction in protocol development, as they lack the risk of increased patient exposure. However, in-vivo validations of low-dose simulations are as uncommon as prospective low-dose image acquisition itself. Therefore, we investigated the extent to which simulated low-dose CT dataset...

Automatic intracranial hemorrhage segmentation in 3D non-contrast head CT (NCCT) scans is significant in clinical practice. Existing hemorrhage segmentation methods usually ignores the anisotropic nature of the NCCT, and are evaluated on different in-house datasets with distinct metrics, making it highly challenging to improve segmentation performa...

(1) Purpose: Combination locks are frequently being used to protect personal property. Since hitherto not described in the literature, we evaluated whether locks can be picked using computed tomography imaging. (2) Materials and methods: Three different combination locks (1296-42875 possible combinations) were scanned using an ultra-high resolution...

Purpose: Differentiation between tumor recurrence and treatment-related contrast enhancement in MRI can be difficult. Late enhancement MRI up to 75 min after contrast agent application has been shown to improve differentiation between tumor recurrence and treatment-related changes. We investigated the diagnostic performance of late enhancement usi...

Background Deep learning (DL)-based MRI reconstructions can reduce examination times for turbo spin-echo (TSE) acquisitions. Studies that prospectively employ DL-based reconstructions of rapidly acquired, undersampled spine MRI are needed. Purpose To investigate the diagnostic interchangeability of an unrolled DL-reconstructed TSE (hereafter, TSEDL...

Purpose Tirofiban has been approved for the treatment of acute coronary syndrome. Meanwhile, tirofiban is frequently applied in emergency situations in interventional neuroradiology (INR). The objective of this study was to analyze the risk profile for the off-label use of tirofiban in INR patients. Methods Data of 86 patients, who underwent neuro...

Background and purpose: Radiographic shunt series are still the imaging technique of choice for radiologic evaluation of VP-shunt complications. Radiographic shunt series are associated with high radiation exposure and have a low diagnostic performance. Our aim was to investigate the diagnostic performance of whole-body ultra-low-dose CT for detec...

Objective: The Allan-Herndon-Dudley syndrome (AHDS) is a severe disease caused by dysfunctional central thyroid hormone transport due to functional loss of the monocarboxylate transporter 8 (MCT8). In this study, we assessed whether mice with concomitant deletion of the thyroid hormone transporters Mct8 and the organic anion transporting polypepti...

Purpose: The purpose of this study was to test the technical feasibility and the impact on the image quality of a deep learning-based super-resolution reconstruction algorithm in 1.5 T abdominopelvic MR imaging. Methods: 44 patients who underwent abdominopelvic MRI were retrospectively included, of which 4 had to be subsequently excluded. After...

Most continual learning methods are validated in settings where task boundaries are clearly defined and task identity information is available during training and testing. We explore how such methods perform in a task-agnostic setting that more closely resembles dynamic clinical environments with gradual population shifts. We propose ODEx, a holist...

Most continual learning methods are validated in settings where task boundaries are clearly defined and task identity information is available during training and testing. We explore how such methods perform in a task-agnostic setting that more closely resembles dynamic clinical environments with gradual population shifts. We propose ODEx, a holist...

Rationale and objectives: To investigate the impact of a prototypical deep learning-based super-resolution reconstruction algorithm tailored to partial Fourier acquisitions on acquisition time and image quality for abdominal T1-weighted volume-interpolated breath-hold examination (VIBESR) at 3 Tesla. The standard T1-weighted images were used as th...

Background: The aim of this study was to assess the technical feasibility and the impact on image quality and acquisition time of a deep learning-accelerated fat-saturated T2-weighted turbo spin echo sequence in musculoskeletal imaging of the extremities. Methods: Twenty-three patients who underwent MRI of the extremities were prospectively incl...

Purpose The purpose of this study was to evaluate the impact of a deep learning-based super-resolution technique on T1-weighted gradient-echo acquisitions (volumetric interpolated breath-hold examination; VIBE) on the assessment of pancreatic MRI at 1.5 T compared to standard VIBE imaging (VIBESTD). Materials and methods This retrospective single-...

Background: This study investigated whether a machine-learning-based combination of radiomics and clinical parameters was superior to the use of clinical parameters alone in predicting therapy response after three months, and overall survival after six and twelve months, in stage-IV malignant melanoma patients undergoing immunotherapy with PD-1 ch...