Georgios C. Manikis

Georgios C. Manikis
Foundation for Research and Technology - Hellas | forth · Computational Medicine Laboratory (CML)

PhD

About

75
Publications
8,386
Reads
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482
Citations
Citations since 2017
50 Research Items
388 Citations
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2017201820192020202120222023020406080100120140
2017201820192020202120222023020406080100120140
2017201820192020202120222023020406080100120140
Introduction
Georgios C. Manikis is a postdoctoral researcher at the Karolinska Institutet and also affiliated with the CBML at FORTH. He holds an MSc in Electronics and Computer Engineering and a PhD on oncological image modelling with the School of Medicine at the University of Crete. He has been working on various EU projects as a research assistant. His research interests lie in the areas of medical image analysis, radiomics, machine and deep learning, and multimodal data integration
Additional affiliations
August 2010 - present
Foundation for Research and Technology - Hellas
Position
  • Technical Staff

Publications

Publications (75)
Article
Full-text available
Radiomics analysis is a powerful tool aiming to provide diagnostic and prognostic patient information directly from images that are decoded into handcrafted features, comprising descriptors of shape, size and textural patterns. Although radiomics is gaining momentum since it holds great promise for accelerating digital diagnostics, it is susceptibl...
Conference Paper
Being diagnosed with breast cancer (BC) can be a traumatic experience for patients who may experience symptoms of depression. In order to facilitate the prevention of such symptoms, it is crucial to understand how and why depressive symptoms emerge and evolve for each individual, from diagnosis through treatment and recovery. In the present work, d...
Chapter
Humans have various features that differentiates one person from another which can be used to identify an individual for security purposes. These biometrics can authenticate or verify a person's identity and can be sorted in two classes, physiological and behavioural. In this article, the authors present their results of experimentation on publicly...
Chapter
There are several novel applications of Deep Learning in Medical Imaging and especially in Ophthalmology in order to provide solutions to unmet clinical needs. The research presented in this paper concerns semantic segmentation of lesions regarding Diabetic Retinopathy. Most of the state-of-the-art papers nowadays use Convolutional Neural Networks,...
Article
Full-text available
The tumor immune microenvironment (TIME) is an important player in breast cancer pathophysiology. Surrogates for antitumor immune response have been explored as predictive biomarkers to immunotherapy, though with several limitations. Immunohistochemistry for programmed death ligand 1 suffers from analytical problems, immune signatures are devoid of...
Article
Full-text available
Pollen identification is an important task for the botanical certification of honey. It is performed via thorough microscopic examination of the pollen present in honey; a process called melissopalynology. However, manual examination of the images is hard, time-consuming and subject to inter- and intra-observer variability. In this study, we invest...
Article
Full-text available
The aim of this study is to investigate the possibility of predicting histological grade in pa- tients with endometrial cancer on the basis of intravoxel incoherent motion (IVIM)-related histogram analysis parameters. This prospective study included 52 women with endometrial cancer (EC) who underwent MR imaging as initial staging in our hospital, a...
Conference Paper
Breast cancer diagnosis has been associated with poor mental health, with significant impairment of quality of life. In order to ensure support for successful adaptation to this illness, it is of paramount importance to identify the most prominent factors affecting well-being that allow for accurate prediction of mental health status across time. H...
Article
Full-text available
Differentiation between transient osteoporosis (TOH) and avascular necrosis (AVN) of the hip is a longstanding challenge in musculoskeletal radiology. The purpose of this study was to utilize MRI-based radiomics and machine learning (ML) for accurate differentiation between the two entities. A total of 109 hips with TOH and 104 hips with AVN were r...
Article
Full-text available
To address the current lack of dynamic susceptibility contrast magnetic resonance imaging (DSC–MRI)-based radiomics to predict isocitrate dehydrogenase (IDH) mutations in gliomas, we present a multicenter study that featured an independent exploratory set for radiomics model development and external validation using two independent cohorts. The max...
Article
Full-text available
Pollen analysis and the classification of several pollen species is an important task in melissopalynology. The development of machine learning or deep learning based classification models depends on available datasets of pollen grains from various plant species from around the globe. In this paper, Cretan Pollen Dataset v1 (CPD-1) is presented, wh...
Article
Full-text available
Diabetic Retinopathy is a retina disease caused by diabetes mellitus and it is the leading cause of blindness globally. Early detection and treatment are necessary in order to delay or avoid vision deterioration and vision loss. To that end, many artificial-intelligence-powered methods have been proposed by the research community for the detection...
Article
Purpose To investigate and histopathologically validate the role of model selection in the design of novel parametric meta-maps towards the discrimination of low from high-grade soft tissue sarcomas (STSs) using multiple Diffusion Weighted Imaging (DWI) models. Methods DWI data of 28 patients were quantified using the mono-exponential, bi-exponent...
Article
Displaying resilience following a diagnosis of breast cancer is crucial for successful adaptation to illness, well-being, and health outcomes. Several theoretical and computational models have been proposed toward understanding the complex process of illness adaptation, involving a large variety of patient sociodemographic, lifestyle, medical, and...
Article
Full-text available
Purpose: The proposed study aims to develop an MRI-based radiomics analysis framework and investigate the feasibility of the calculated quantitative imaging features for differentiating low from high grade soft tissue sarco-mas (STSs). Material and Methods: A total of 22 patients (9 low grade and 13 high grade) who were pathologically diagnosed wit...
Article
Full-text available
Neuropsychiatric systemic lupus erythematosus (NPSLE) is an autoimmune entity 30 comprising of heterogenous syndromes affecting both the peripheral and central nervous system. 31 Research on the pathophysiological substrate of NPSLE manifestations, including functional 32 neuroimaging studies, is extremely limited. The present study examined person...
Article
Full-text available
Background: We investigated a recently proposed multiexponential (Mexp) fitting method applied to T2 relaxometry magnetic resonance imaging (MRI) data of benign and malignant adipocytic tumours and healthy subcutaneous fat. We studied the T2 distributions of the different tissue types and calculated statistical metrics to differentiate benign and...
Article
Full-text available
This study aims to examine a time-extended dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) protocol and report a comparative study with three different pharmacokinetic (PK) models, for accurate determination of subtle blood–brain barrier (BBB) disruption in patients with multiple sclerosis (MS). This time-extended DCE-MRI perfusion p...
Chapter
Full-text available
In the current study, a model-based system for predicting resilience in silico, as part of personalizing precision medicine, to better understand the needs for improved therapeutic protocols of each patient is proposed. The computational environment, which is currently under implementation within the BOUNCE EU project (“Predicting Effective Adaptat...
Article
Fibrous dysplasia (FD) is a mosaic skeletal disorder resulting in fractures, deformity, and functional impairment. Clinical evaluation has been limited by a lack of surrogate endpoints capable of quantitating disease activity. The purpose of this study was to investigate the utility of ¹⁸F‐NaF PET/CT imaging in quantifying disease activity in patie...
Preprint
Full-text available
Background: Subcutaneous fat may have variable signal intensity on T2w images depending on the choice of imaging parameters. However, fatty components within tumors have a different degree of signal dependence on the acquisition scheme. This study examined the use of T2, T2* relaxometry and spin coupling related signal changes (Spin Coupling ratio...
Article
Full-text available
Background: Sorafenib is the currently recommended therapy in patients with advanced hepatocellular carcinoma (HCC). Among the several biomarkers available for the evaluation of the therapeutic response and prognosis, there is perfusion magnetic resonance imaging (p-MRI) that, through measurement of the vascular permeability unit (ktrans), may ret...
Article
Imaging biomarkers (IBs) play a critical role in the clinical management of breast cancer (BRCA) patients throughout the cancer continuum for screening, diagnosis, and therapy assessment, especially in the neoadjuvant setting. However, certain model-based IBs suffer from significant variability due to the complex workflows involved in their computa...
Article
Full-text available
Humans have various features that differentiates one person from another which can be used to identify an individual for security purposes. These biometrics can authenticate or verify a person's identity and can be sorted in two classes, physiological and behavioural. In this article, the authors present their results of experimentation on publicly...
Chapter
The efficiency of a biometric system is identified by the detection error tradeoff (DET) curve, which is a visual characterization of the trade-off between the False Acceptance Rate (FAR) and the False Rejection Rate (FRR). A DET curve is a plot of FAR against FRR for various threshold values, t. FRR refers to the expected probability that two mate...
Article
Purpose Non-invasive characterization of lipomatous tumors can be challenging as several histological types have similar imaging characteristics. In this study we examine the use of a new biomarker based on spin coupling related signal loss between two acquisitions of different echo spacing to differentiate between benign lipomas, well, intermediat...
Article
Purpose T2 relaxation constant has been established as an accurate biomarker from the early days of MRI for tissue or material identification as it expresses physical properties without dependence on the MR protocol used. T2* expresses acceleration of T2 dephasing process by local field inhomogeneities that can be produced by paramagnetic blood pro...
Conference Paper
Full-text available
Accurate determination of disease activity by detection of the acute, inflammatory Multiple Sclerosis (MS) lesions, with blood brain barrier disruption and contrast enhancement is critical for clinicians because it affects diagnosis and treatment. In this work, a new Dynamic Contrast Enhanced (DCE) protocol was investigated in conjunction with diff...
Chapter
Full-text available
Medical imaging is an active and developing area, providing significant anatomical, functional, and molecular information in a wide range of clinical and research studies. Medical imaging techniques like ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) in conjunction with advanced acquis...
Chapter
Full-text available
Magnetic resonance imaging (MRI) is an imaging technique that is based on the interactions of water with external magnetic fields. Magnetic properties of water molecules are analyzed in order to sketch the profile of tissues, and they may be related to a variety of aspects including internal structure, tissue integrity, molecular environment, and o...
Article
Full-text available
Purpose: The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer. Material and methods: Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation thera...
Data
The dataset used in this analysis is available in the file S1_Dataset.zip. The derived DWI parameters from the four examined models and the statistical analysis results are provided in csv format. (ZIP)
Poster
Full-text available
This study aims to elucidate aspects of IVIM fitting procedure that may obscure the true contribution of pseudo-diffusion to a multi-b-value DWI acquisition scheme.
Poster
Full-text available
This study presents a platform for the longitudinal analysis of the DW-MRI data.
Poster
Full-text available
There is an increasing interest on recruiting imaging biomarkers for evaluating treatment effects. The potential ability of an imaging biomarker to act as an indicator of a biological process and for monitoring the response to therapy can be severely influenced by the lack of reproducibility and repeatability.
Article
Full-text available
Purpose: To compare the diagnostic accuracy of normalized Blood Volume (nBV) histogram metrics in differentiating low from high-grade gliomas. Material and Methods: Forty-four patients (22 female, 22 male) with histologically confirmed gliomas were included. Group A comprised 10 patients with low grade gliomas (all grade II) while group B comprised...
Article
Full-text available
Objectives To compare two Gaussian diffusion-weighted MRI (DWI) models including mono-exponential and bi-exponential, with the non-Gaussian kurtosis model in patients with pancreatic ductal adenocarcinoma. Materials and methods After written informed consent, 15 consecutive patients with pancreatic ductal adenocarcinoma underwent free-breathing DW...
Conference Paper
Full-text available
Diffusion Weighted Imaging (DWI) is a noninvasive imaging technique in Magnetic Resonance Imaging (MRI), providing significant anatomical and functional information in a wide range of clinical and research studies based on the random motion of water molecules. DWI, using appropriate models, can be quantified into clinically relevant biomarkers givi...
Article
Introduction Echo spacing in Fast Spin Echo techniques can affect signal intensity mainly of fatty tissue and is presented as effectively prolonged T2 relaxation time (magnetic fat liquefaction). Purpose The aim of this study is to measure signal intensity in multi echo Fast Spin Echo techniques with variable echo spacing in order to examine the f...
Conference Paper
Full-text available
This paper presents a graphical user interface (GUI) for empowering users to read, analyze, visualize and quantify the diffusion weighted magnetic resonance imaging (DWI-MRI) data into diffusion related imaging biomarkers. The process of random motion of water molecules in human tissues called diffusivity is a significant physical process that can...
Conference Paper
Full-text available
Visualizing tumor environment is a critical task for assessing treatment response as well as tailoring therapy to the individual by better understanding the viable, necrotic and hypoxic areas. While a number of imaging modalities can provide complementary information about the tumor composition, there are several constraints regarding radiation, co...
Poster
Full-text available
The aim of the current poster was to apply and compare four diffusion models including mono-exponential and bi-exponential both Gaussian and non-Gaussian, in hepatic metastases and normal liver tissue.
Poster
Full-text available
The aim of the current poster was to compare four diffusion models including mono-exponential and bi-exponential both Gaussian and non-Gaussian in patients with rectal adenocarcinoma.
Conference Paper
Full-text available
Purpose: To compare the diagnostic accuracy of Apparent Diffusion Coefficient (ADC) to normalized Blood Volume (nBV) histogram metrics in differentiating low from high grade gliomas. Patients and Methods: Forty four patients (22 female, 22 male) with histologically confirmed gliomas were included. Group A comprised 10 patients with low grade gliom...
Article
Full-text available
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables the quantification of contrast leakage from the vascular tissue by using pharmacokinetic (PK) models. Such quantitative analysis of DCE-MRI data provides physiological parameters that are able to provide information of tumor pathophysiology and therapeutic outcome. Several assum...
Article
Full-text available
Single-slice magnetization transfer (MT) imaging has shown promising results for evaluating post-radiation fibrosis. The study aim was to evaluate the value of multislice MT imaging to assess tumour response after chemoradiotherapy by comparing magnetization transfer ratios (MTR) with histopathological tumour regression grade (TRG). Thirty patients...
Conference Paper
Improving the initial diagnosis and the assessment of response to treatment in malignant gliomas, while avoiding invasive methods as much as justifiable, is one major aspect actual research is focusing on. Imaging studies are used to calculate tumor volume and define vital, necrotic and cystic areas within a tumor. Though the visual interpretation...
Conference Paper
Full-text available
Nephroblastoma is the most common malignant renal tumor in children. Today about 90 % of the patients can be cured by chemotherapy and surgery. Most of the patients are enrolled in prospective clinical trials. In the SIOP (International Society of Pediatric Oncology) approach all children do receive preoperative chemotherapy to shrink the tumor bef...
Article
Full-text available
Applying diffusive models for simulating the spatiotemporal change of concentration of tumour cells is a modern application of predictive oncology. Diffusive models are used for modelling glioblastoma, the most aggressive type of glioma. This paper presents the results of applying a linear quadratic model for simulating the effects of radiotherapy...