The Use of Natural Language Processing Elements for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Enterally Fed Patients with Head and Neck or Upper Gastrointestinal Tract Cancers.

BACKGROUND: Psycho-oncology care has emerged as a significant concern in contemporary oncology practice, given its profound impact on patient psychological well-being. Patients undergoing treatment for head-neck or upper gastrointestinal tract cancers often experience complex emotional and psychological challenges, necessitating specialized support and intervention. Traditional approaches to psycho-oncological care may be limited in their ability to comprehensively assess and address patients' needs. Therefore, exploring innovative methodologies, such as leveraging natural language processing (NLP) elements, is crucial to enhancing the effectiveness of psycho-oncological interventions. METHODS: In this study, we developed a method utilizing natural language processing (NLP) elements to augment psycho-oncological care for patients with head-neck or upper gastrointestinal tract cancers. The method aimed to facilitate vocabulary, sentiment, and intensity analysis of five basic emotions (happiness, sadness, anger, disgust, and fear), as well as to explore potential areas of difficulty such as body image, pain, and self-esteem. We conducted research involving 50 patients across three treatment stages. RESULTS: Our method facilitated the identification of characteristic features at each treatment stage, aiding in the tailoring of appropriate therapies to individual patient needs. The results offer insights valuable to psychologists and psychiatrists for expedited diagnosis and intervention, potentially influencing therapy outcomes. Additionally, the data may inform treatment decisions by addressing patient-specific concerns. Furthermore, our method holds promise for optimizing the allocation of psychological care resources, particularly at the initial stages of patient contact. LIMITATIONS: The main problem in the research was the fairly wide age range of participants, which explains the potential diversity of vocabulary. CONCLUSION: In conclusion, our study demonstrates the potential utility of integrating natural language processing (NLP) elements into psycho-oncological care for patients with head-neck or upper gastrointestinal tract cancers. The developed method offers a novel approach to comprehensively assessing patients' emotional states and areas of difficulty, thereby facilitating tailored interventions and treatment planning. These findings underscore the importance of continued research and innovation in psycho-oncology to enhance patient care and outcomes.

The Use of Natural Language Processing for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Patients with Cancers.

BACKGROUND: Head and neck cancers (H&NCs) constitute a significant part of all cancer cases. H&NC patients experience unintentional weight loss, poor nutritional status, or speech disorders. Medical interventions affect appearance and interfere with patients' self-perception of their bodies. Psychological consultations are not affordable due to limited time. METHODS: We used NLP to analyze the basic emotion intensity, sentiment about one's body, characteristic vocabulary, and potential areas of difficulty in free notes. The emotion intensity research uses the extended NAWL dictionary developed using word embedding. The sentiment analysis used a hybrid approach: a sentiment dictionary and a deep recursive network. The part-of-speech tagging and domain rules defined by a psycho-oncologist determine the distinct language traits. Potential areas of difficulty were analyzed using the dictionaries method with word polarity to define a given area and the presentation of a note using bag-of-words. Here, we applied the LSA method using SVD to reduce dimensionality. A total of 50 cancer patients requiring enteral nutrition participated in the study. RESULTS: The results confirmed the complexity of emotions in patients with H&NC in relation to their body image. A negative attitude towards body image was detected in most of the patients. The method presented in the study appeared to be effective in assessing body image perception disturbances, but it cannot be used as the sole indicator of body image perception issues. LIMITATIONS: The main problem in the research was the fairly wide age range of participants, which explains the potential diversity of vocabulary. CONCLUSIONS: The combination of the attributes of a patient's condition, possible to determine using the method for a specific patient, can indicate the direction of support for the patient, relatives, direct medical personnel, and psycho-oncologists.

Modeling of Respiratory Motion to Support the Minimally Invasive Destruction of Liver Tumors.

OBJECTIVE: Respiratory movements are a significant factor that may hinder the use of image navigation systems during minimally invasive procedures used to destroy focal lesions in the liver. This article aims to present a method of estimating the displacement of the target point due to respiratory movements during the procedure, working in real time. METHOD: The real-time method using skin markers and non-rigid registration algorithms has been implemented and tested for various classes of transformation. The method was validated using clinical data from 21 patients diagnosed with liver tumors. For each patient, each marker was treated as a target and the remaining markers as target position predictors, resulting in 162 configurations and 1095 respiratory cycles analyzed. In addition, the possibility of estimating the respiratory phase signal directly from intraoperative US images and the possibility of synchronization with the 4D CT respiratory sequence are also presented, based on ten patients. RESULTS: The median value of the target registration error (TRE) was 3.47 for the non-rigid registration method using the combination of rigid transformation and elastic body spline curves, and an adaptation of the assessing quality using image registration circuits (AQUIRC) method. The average maximum distance was 3.4 (minimum: 1.6, maximum 6.8) mm. CONCLUSIONS: The proposed method obtained promising real-time TRE values. It also allowed for the estimation of the TRE at a given geometric margin level to determine the estimated target position. Directions for further quantitative research and the practical possibility of combining both methods are also presented.

Measuring Respiratory Motion for Supporting the Minimally Invasive Destruction of Liver Tumors.

OBJECTIVE: Destroying liver tumors is a challenge for contemporary interventional radiology. The aim of this work is to compare different techniques used for the measurement of respiratory motion, as this is the main hurdle to the effective implementation of this therapy. METHODS: Laparoscopic stereoscopic reconstruction of point displacements on the surface of the liver, observation of breathing using external markers placed on the surface of the abdominal cavity, and methods for registration of the surface of the abdominal cavity during breathing were implemented and evaluated. RESULTS: The following accuracies were obtained: above 4 mm and 0.5 mm, and below 8 mm for laparoscopic, skin markers, and skin surface registration methods, respectively. CONCLUSIONS: The clinical techniques and accompanying imaging modalities employed to destroy liver tumors, as well as the advantages and limitations of the proposed methods, are presented. Further directions for their development are also indicated.

Computer aided math learning as a tool to assess and increase motivation in learning math by visually impaired students.

PURPOSE: Effective teaching and learning mathematics is important to achieve good results during an academic and professional career. This is especially difficult for visually impaired students because of difficulties in managing structural information included in maths formulae. METHODS: The extended multimedia alternative method, including the problem of decomposition and knowledge vector, were presented and compared to the classical teaching method. A qualitative method to evaluate motivation during the process of teaching and learning maths for impaired students, which includes eleven detailed motivators, has been developed. RESULTS: The alternative teaching method offers statistically significant improvements in four of the eleven proposed assessment categories: success in progress - adjusting the difficulties of learning, presentation of the material, approval: group/individual and alternative presentation of mathematic materials. The experiments carried out allowed the authors to increase the knowledge about the limitations and challenges occurring in the process of maths education among visually impaired students and their motivation. CONCLUSIONS: Based on the experiments and research results, it can be concluded that applying the proposed method of decomposition together with evaluation procedure based on the vector of knowledge in the process of teaching and learning of mathematics by visually impaired may increase their motivation positively.Implications for RehabilitationThe key aspects of the alternative method of presenting math formulae are included in the bellow points:• It increases the availability of materials containing structured information (mathematical formulae) for the blind.• It limits the importance of communication barriers in math education: the possibility of self-study, reducing costs - by reducing the number of individual tutorials.• It contributes to the development of universal rules for the structural presentation of information• It increases the independence of the student from the teacher.

Target registration error reduction for percutaneous abdominal intervention.

A real-time methodology that finds spatio-temporal correspondence between the positions of the target point in the pre-treatment 3DCT image and during the procedure was proposed. It based on minimizing the target registration error in III tier registration circuits. Particle Swarm Optimization and Differential Evaluation were used to find optimal values of Elastic Body Spline parameters in the generation of abdominal deformation field. Different transformation classes have been tested: rigid, affine, Thin Plate Spline, Elastic Body Spline. The lowest TRE was obtained for the swarm optimization algorithm - differential evolution for the rigid and affine version: 3.47 and 3.73 mm, respectively.

Age- and gender-dependent variability in the geometry of middle cerebral artery bifurcations.

The goal of this study was to analyze trends in the geometric parameters of blood vessels with age in a randomly selected group of 200 computed tomography angiography studies of radiologically healthy individuals using dedicated statistical techniques. A quantitative description of cerebral vascular geometry with numerical parameters (bifurcation angle, branching angle, co-planarity index, average curvature, and average torsion) was proposed. The changes and variability in geometry were analyzed according to age. The bifurcation angle, branching angle, and average curvature increased with age, whereas the co-planarity index and average torsion decreased with age. For equal-diameter branches, women comparing to men presented lower bifurcation angles in the 4th decade of life, and lower values for the co-planarity index in the 3rd and 4th decades of life. In non-equal-diameter branches, the opposite relationship was observed for bifurcation angle in the 4th decade of life comparing both groups. All analyzed parameters showed clearly visible trends with patient age. Deviations in specific decades of life were detected; these deviations could be linked to the development of aneurysms in specific age groups.

Computer-aided therapeutic diagnosis for anorexia.

BACKGROUND: Anorexia nervosa is a clinical disorder syndrome of the wide spectrum without a fully recognized etiology. The necessary issue in the clinical diagnostic process is to detect the causes of this disease (e.g., my body image, food, family, peers), which the therapist gradually comes to by verifying assumptions using proper methods and tools for diagnostic process. When a person is diagnosed with anorexia, a clinician (a doctor, a therapist or a psychologist) proposes a therapeutic diagnosis and considers the kind of treatment that should be applied. This process is also continued during therapeutic diagnosis. In both cases, it is recommended to apply computer-aided tools designed for testing and confirming the assumptions made by a psychologist. The paper aims to present the computer-aided therapeutic diagnosis method for anorexia. The proposed method consists of 4 stages: free statements of a patient about his/her body image, the general sentiment analysis of statement based on Recurrent Neural Network, assessment of the intensity of five basic emotions: happiness, anger, sadness, fear and disgust (using the Nencki Affective Word List and conversion of words to their basic form), and the assessment of particular areas of difficulties-the sentiment analysis based on the dictionary approach was applied. RESULTS: The sentiment analysis of a document achieved 72% and 51% of effectiveness, respectively, for RNN and dictionary-based methods. The intensity of sadness (emotion) occurring within the dictionary method is differentiated between control and research group at the level of 10%. CONCLUSION: The quick access to the sentiment analysis of a statement on the image of patient's body, emotions experienced by the patient and particular areas of difficulties of people prone to the anorexia nervosa disorders, may help to establish the diagnosis in a very short time and start an immediate therapy. The proposed automatic method helps to avoid patient's aversions towards the therapy, which may include avoiding patient-therapist communication, talking about less essential topics, coming late for the sessions. These circumstances can guarantee promising prognosis for recovering.

Segmentation of abdominal organs in computed tomography using a generalized statistical shape model.

Segmentation of anatomical structures in computed tomography images remains an important stage in computer-aided diagnostics and therapy. Due to the complexity of anatomical structures in the abdominal cavity, the occurrence of anatomical variants and pathological changes of organs in computed tomography images, segmentation is still treated as a current research problem. The paper presents the segmentation method based on the generalized statistical shape model. The method was tested in the application to segmentation based on 40 cases of computed tomography with contrast: 20 cases were included in training set and 20 in the testing set. For each case, expert outlines were made for the following organs: spleen, kidney, liver, pancreas, and duodenum. The following average results of the DICE coefficient were obtained: 0.96, 093, 0.88, 0.86, 0.81. The obtained results on the developed method can be treated as a step towards a universal method of segmentation in normalized scaled images, because the method does not require the selection of new parameter values when applied to the segmentation of a diverse group of parenchymal anatomical organs.

Supporting diagnostics and therapy planning for percutaneous ablation of liver and abdominal tumors and pre-clinical evaluation.

Percutaneous ablation methods are used to treat primary and metastatic liver tumors. Image guided navigation support minimally invasive interventions of rigid anatomical structures. When working with the displacement and deformation of soft tissues during surgery, as in the abdomen, imaging navigation systems are in the preliminary implementation stage. In this study a multi-stage approach has been developed to support percutaneous liver tumors ablation. It includes CT image acquisition protocol with the amplitude of respiratory motion that yields images subjected to a semi-automatic method able to deliver personalized abdominal model. Then, US probe and ablation needle calibration, as well as patient position adjustment method during the procedure for the preoperative anatomy model, have been combined. Finally, an advanced module for fusion of the preoperative CT with intraoperative US images was designed. These modules have been tested on a phantom and in the clinical environment. The final average Spatial calibration error was 1,7 mm, the average error of matching the position of the markers was about 2 mm during the entire breathing cycle, and average markers fusion error 495 mm. The obtained results indicate the possibility of using the developed method of navigation in clinical practice.

Anisotropic non-rigid Iterative Closest Point Algorithm for respiratory motion abdominal surface matching.

Surface registration is a one of the crucial and actual problems of computer aided surgery. This paper presents the modification of the non-rigid Iterative Closest Point Algorithm which takes into account an anisotropic noise model and landmarks as guided correspondence at the transformation step in every iteration. The presented approach was validated on human abdominal briefing surface data from a time-of-flight camera. We took the median of the resulting measures and the outcome is presented: the median of means of surfaces distance was at the same level for both variants of the ICP algorithm and is comparable with the isotropic variant, the median of mean landmark position errors decreased by 0.93 units (over 20% improvement) and the median of percentage of single correspondences in target point cloud increased by 11.96%. The results showed that the introduction of the anisotropic model of noise for the ToF camera allows for the improvement the percentage of target cloud points which had only one correspondent over 10% impartment and additional weighting of markers also improves the measure of the quality of finding real correspondents over 20% improvement. In the examined dataset, where the average initial distance between the clouds of points in the inspiratory and expiration is equal to approx. 7.5 mm, a more than 10% improvement in the quality of the correspondence improves the accuracy of matching the surface within 1 mm which is a significant value in application of minimally invasive image guided interventions.

Selection of the respiratory phase in minimally invasive interventions for target registration error minimization.

BACKGROUND: In minimally invasive surgery, the main challenge is precisely locating the target during the intervention. For abdominal intervention, one of most important factors causing target motion is breathing. The aim of the study is to efficiently predict target localization during the respiratory in breathing cycle. METHOD: Analysis of target registration error (TRE) for the registration circuits method was used to find the breathing phase corresponding to the preoperative Computed Tomography spatial configuration. Then, Elastic Body Spline (EBS) for modeling deformation field and Particle Swarm Optimization method were used to find the desired values of EBS parameters: ∝ and stiffness were used. RESULTS: The proposed methodology was verified during experiments conducted on 21 patients diagnosed with liver tumors. This ability of TRE reduction has been achieved for the respiratory phases founded in registration chain analysis. CONCLUSIONS: The proposed method presents the usability of spatio-temporal analysis of collected real breathing data in order to estimate the position of a target during the respiratory cycle. This method has been developed to perform operations in real-time on a standard workstation.

Factors influencing the process of learning mathematics among visually impaired and blind people.

Effective instruction and comprehension of mathematics are important for achieving academic and professional success but are especially difficult for visually impaired individuals because of the inherent difficulty in managing structural information included in math formulae. An evaluation of an alternative for computer-aided math instruction and comprehension among visually impaired students was developed, and the evaluation included seven detailed categories of factors: behavioral, emotional, cognitive, social, distracting, motivational, and modeling factors. Then, the proposed method was used to compare the alternative teaching method, including problem decomposition and vector knowledge, to the classical teaching method with a teacher. The assessment of the impact of the developed approach on improving the process of teaching mathematics in a group of blind and visually impaired students was carried out by the completion of a questionnaire prepared by a psychologist. The alternative teaching method achieved significantly better results in six of the seven proposed assessment categories. These experiments extend the knowledge base on the limitations and challenges associated with teaching and learning mathematics among blind people.

Semi-automatic measurements and description of the geometry of vascular tree based on Bézier spline curves: application to cerebral arteries.

BACKGROUND: The geometry of the vessels is easy to assess in novel 3D studies. It has significant influence on flow patterns and this way the evolution of vascular pathologies such as aneurysms and atherosclerosis. It is essential to develop robust system for vascular anatomy measurement and digital description allowing for assessment of big numbers of vessels. METHODS: A semiautomatic, robust, integrated method for vascular anatomy measurements and mathematical description are presented. Bezier splines of 6th degree and continuity of C3 was proposed and distribution of control points was dependent on local radius. Due to main interest of our institution, the system was primarily used for the assessment of the geometry of the intracranial arteries, especially the first Medial Cerebral Artery division. RESULTS: 1359 synthetic figures were generated: 381 torus and 978 spirals. Experimental verification of the proposed methodology was conducted on 400 Middle Cerebral Artery divisions. CONCLUSIONS: In difference to other described solution all proposed methodology steps were integrated allows analysis of variability of geometrical parameters among big number of Medial Cerebral Artery bifurcations using single application. This allows for determination of significant trends in the parameters variability with age and in contrary almost no differences between men and women.

Automatic liver segmentation in computed tomography using general-purpose shape modeling methods.

BACKGROUND: Liver segmentation in computed tomography is required in many clinical applications. The segmentation methods used can be classified according to a number of criteria. One important criterion for method selection is the shape representation of the segmented organ. The aim of the work is automatic liver segmentation using general purpose shape modeling methods. METHODS: As part of the research, methods based on shape information at various levels of advancement were used. The single atlas based segmentation method was used as the simplest shape-based method. This method is derived from a single atlas using the deformable free-form deformation of the control point curves. Subsequently, the classic and modified Active Shape Model (ASM) was used, using medium body shape models. As the most advanced and main method generalized statistical shape models, Gaussian Process Morphable Models was used, which are based on multi-dimensional Gaussian distributions of the shape deformation field. RESULTS: Mutual information and sum os square distance were used as similarity measures. The poorest results were obtained for the single atlas method. For the ASM method in 10 analyzed cases for seven test images, the Dice coefficient was above 55[Formula: see text], of which for three of them the coefficient was over 70[Formula: see text], which placed the method in second place. The best results were obtained for the method of generalized statistical distribution of the deformation field. The DICE coefficient for this method was 88.5[Formula: see text] CONCLUSIONS: This value of 88.5 [Formula: see text] Dice coefficient can be explained by the use of general-purpose shape modeling methods with a large variance of the shape of the modeled object-the liver and limitations on the size of our training data set, which was limited to 10 cases. The obtained results in presented fully automatic method are comparable with dedicated methods for liver segmentation. In addition, the deforamtion features of the model can be modeled mathematically by using various kernel functions, which allows to segment the liver on a comparable level using a smaller learning set.

Computer aided sentiment analysis of anorexia nervosa patients' vocabulary.

BACKGROUND: Diagnosing and treating anorexia nervosa is an important challenge for modern psychiatry. Taking into account a connection between the mental state of a person and the characteristics of their language, this paper presents developed and tested method for analyzing the written statements of patients with anorexia nervosa and healthy individuals, including the identification of keywords. METHODS: Due to the short nature of the texts, which is related to the difficulty of expressing oneself about one's body when suffering from anorexia, the bag of words approach was used for documents' information representation. The document is represented as a vector, where its various elements indicate the number of individual words. Then, a rule-based model was created, where as a collection of rules, dictionary files were used corresponding to three groups of positive, negative and neutral sounds for each subcategory. Next in the analyzed texts were searched and counted keywords. Based on the keywords found, each of the documents was categorized into one of the groups in every subcategory. RESULTS: It is possible to indicate a set of characteristics sentiment for every person. Additionally, the results of specific patient could be analyzed in six specific subcategories: self-esteem, acceptance of the assessment of the environment, emotions, autoimmune, functioning of the body and body image. CONCLUSIONS: The described analysis indicates the existence of a relationship between the mental state of the author's textual health and the vocabulary he or she uses. It is possible to indicate a set of characteristic sentiment terms specific to a given group of people. Their presence is related to the author's mental state and their body image. It could help focus on specific topics during therapy.

Target registration error minimization for minimally invasive interventions involving deformable organs.

Precise positioning of the target point during minimally invasive procedures is a major challenge associated with the use of image-based navigation systems. No significant dependence between fiducial registration error (FRE) and target registration error (TRE) was found. However, this investigation demonstrated the utility of using thin plate splines (TPS) and marker observation to monitor FRE during respiration to estimate target position based on the deformation field for minimally invasive procedures in deformable regions. The proposed methodology was verified via experiments involving 21 patients diagnosed with liver tumors. This method has been developed for real-time use while performing operations.

Tutoring math platform accessible for visually impaired people.

BACKGROUND: There are many problems with teaching and assessing impaired students in higher education, especially in technical science, where the knowledge is represented mostly by structural information like: math formulae, charts, graphs, etc. Developing e-learning platform for distance education solves this problem only partially due to the lack of accessibility for the blind. METHOD: The proposed method is based on the decomposition of the typical mathematical exercise into a sequence of elementary sub-exercises. This allows for interactive resolving of math exercises and assessment of the correctness of exercise solutions at every stage. The presented methods were prepared and evaluated by visually impaired people and students. RESULTS: The article presents the accessible interactive tutoring platform for math teaching and assessment, and experience in exploring it. The results of conducted research confirm good understanding of math formulae described according to elaborated rules. Regardless of the level of complexity of the math formulae the level of math formulae understanding is higher for alternative structural description. CONCLUSIONS: The proposed solution enables alternative descriptions of math formulae. Based on the research results, the tool for computer-aided interactive learning of mathematics adapted to the needs of the blind has been designed, implemented and deployed as a platform for on-site and online and distance learning. The designed solution can be very helpful in overcoming many barriers that occur while teaching impaired students.

Target Registration Error minimization involving deformable organs using elastic body splines and Particle Swarm Optimization approach.

In minimally invasive surgery one of the main challenges is the precise location of the target during the intervention. The aim of the study is to present usability of elastic body splines (EBS) to minimize TRE error. The method to find the desired EBS parameters values is presented with usage of Particle Swarm optimization approach. This ability of TRE minimization has been achieved for the respiratory phases corresponding to minimum FRE for abdominal (especially liver) surgery. The proposed methodology was verified during experiments conducted on 21 patients diagnosed with liver tumors. This method has been developed to perform operations in real-time on a standard workstation.

Surface area estimation for application of wound care.

Estimation of surface for application of wound care is one of the important prognostic factors for wound healing. The objective of this study is to measure a surface area estimation for application of wound care. Non-invasive, 3D surface reconstruction methodology using two monocular cameras was implemented and verified. The measurement environment was setup on 10 patients with different kind of wounds. Phantom measurements, with known dimensions, show accuracy of implemented method below 11 percent The patient's measurements has the same accuracy. The implemented method use state of art algorithms and the cheap equipment and can be treated as an auxiliary, more objective method to quantify the wound healing process.