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Background Multiple sclerosis (MS) is the most common cause of non-traumatic neurological disability affecting young adults during their best working years. Previous studies have shown that approximately two-thirds of patients with MS (PwMS) are unable to retain employment in the long term, and many retire soon after the diagnosis. However, it is not known, how the rate of retirement has changed over the decades, especially after the introduction of disease modifying therapies (DMTs). The year 1995 was selected as a division point because DMTs have been increasingly available ever since. Objective To evaluate the change in retirement rate due to MS and to present risk factors for early retirement. Methods A retrospective survey of all PwMS treated at the Department of Neurology, Kanta-Hame Central Hospital, Finland between 1978 and 2015, was conducted. The population was divided into two groups: those diagnosed before year 1995 and those diagnosed thereafter. A Kaplan-Meier analysis was performed to evaluate the time from diagnosis to beginning of a pension in both groups. Crude incidence rates, incidence rate differences as well as age and multivariable adjusted Cox proportional hazard regression analysis were calculated for all pension predictors collected. Results A total of 484 PwMS were identified, 140 of whom were diagnosed before the year 1995 and 344 after. Actual retirement rates were 88 (63%) before the year the year 1995 and 111 (32%) after, respectively. The hazard for disability pension diminished in PwMS diagnosed after the year 1995 compared to those diagnosed before, HR 0.41 (95% confidence interval 0.31-0.55). The median time from diagnosis to retirement was 8.3 years in the group diagnosed before year 1995 and 11.1 years in the group diagnosed later. Male sex and age were statistically significant risk factors in relapsing-remitting MS, HR for male sex 1.8 (95% confidence interval 1.18-2.75) and for age 1.1 (95% confidence interval 1.07-1.12). Only age was a risk factor in progressive MS with HR 1.09 (95% confidence interval 1.07-1.11). In subgroup of relapsing-remitting MS, not using disease modifying therapies was a statistically significant risk factor, HR 1.89 (95% confidence interval 1.19-3.01). Conclusion The rate of retirement due to MS in Finland has decreased significantly since 1995 and the median time from diagnosis to retirement has become longer. Not using disease modifying therapies for relapsing remitting MS was identified as one risk factor for losing ability to work prematurely.

Objectives: To evaluate the prognostic significance of tumor volume in computed tomographic (CT) images of non-Hodgkin lymphoma patients. To compare CT volumes with those measured by magnetic resonance imaging (MRI). Methods: Twenty-five patients with B cell-type non-Hodgkin lymphoma (16 men, 9 women, age range, 48-77 years) were imaged with CT at 5 time points. The volumes and volume reductions were associated with clinical characteristics and treatment outcome. The CT-derived tumor volumes were correlated with MRI volumes derived earlier for the same patients. Results: Good agreement was found between 1-dimensional (1D), 2D, and 3D analyses. The CT-derived median tumor volumes were 306 cm 3 , 174 cm 3 , 75 cm 3 , 28 cm 3 , and 15 cm 3 at the 5 time points. These volumes were found to associate, for example, with mortality and tumor malignancy. The CT-based tumor volumes showed good correlation with MRI. Conclusions: Tumor volume quantification is a powerful tool that associates with clinical characteristics and treatment outcome.

Purpose Physical activity is a key to independent functional ability among older adults but few interventions have been conducted in assisted‑living residences. A pedometer has been stated to be ‘a good-enough’ measuring device for the assessment of walking activity in older populations. Research has, however, focused more on community dwelling older adults than on those residing in assisted-living facilities. The aim of this pilot study was to assess the feasibility of a pedometer‑based walking program in an assisted-living facility, and to explore the challenges and obstacles for the implementation of such a program. Materials and methods A pilot intervention study was done with 8 residents between 68 and 89 years of age residing in one assisted‑living facility in Finland. The participants were given pedometers and were asked to walk as usual for a period of one week in order to measure the baseline number of steps. Then, personal goals were assessed based on these baseline figures. Motivational materials and meetings with the participants and attendant nurses were also provided. Participants were encouraged to increase their daily number of steps from their baseline levels by 5% weekly for a period of 6 weeks. Post intervention, seven of the participants and their nurses (n=13) filled in questionnaires concerning the use and usability of the pedometer. Results At baseline, the median number of steps taken by the participants was 800 per day, the daily average being 1369. Post intervention the median was 884 and daily average 1458 steps, demonstrating an increase but no statistically significant changes in the number of steps. Most of the nurses (9/13) believed the pedometer actually encouraged the residents to walk more, but because of technical difficulties, fewer nurses (5/13) found the pedometer to be useful in practice in terms of encouragement for more activity. The participants and nurses found the pedometer easy to use but reported problems with it falling off, underestimating step counts, and inaccuracy. Conclusion Motivating sedentary older adults living in an assisted‑living facility to walk more by employing a pedometer-based walking program is possible but challenging. Integrating the program into daily routines and systematic communication between the research team and the staff of the participating site are needed in order to support the adoption and sustained usage of the new technology. The accuracy and reliability of the pedometer need improvement in terms of use by people with shuffling and low-impact gaits. Better clips to prevent dislodging as well as easier to read numbers are also recommended. Overall, the findings from this study suggest that there is a need for improved pedometer technology to be used with older adults residing in assisted-living residences.

In primary progressive multiple sclerosis (PPMS) abnormalities in brain magnetic resonance imaging (MRI) differ from abnormalities in other subtypes of multiple sclerosis (MS). It was investigated whether the extent of brain and spinal cord MRI abnormalities is reflected in the neurological disability in PPMS. Focal and diffuse changes and atrophy in central nervous system (CNS) in patients with PPMS (n = 28) and healthy controls (n = 20) were assessed by semi-automatic MRI segmentation and volumetric analysis. The measurements were related to neurological disability as expressed by the expanded disability status scale (EDSS), the regional functional scoring system (RFSS), the arm index and the ambulation index. Plaques in T1- and/or T2-weighted images were seen in all brains, while spinal plaques were detected in 23 of 28 patients (82%). The total volumes of brain and spinal cord were significantly smaller in patients than in controls (P = 0.001 and 0.000, respectively). The volumes of T1 or T2 lesions in the brain correlated to the ambulation index (r = 0.51, P = 0.005 and r = 0.53, P = 0.004, respectively). No correlations were detected between MRI measurements and total EDSS score, but relative brain atrophy correlated inversely with the total RFSS scores, poor arm index and higher cerebral disturbances (r = -0.53, P = 0.004; r = -0.53, P = 0.004; and r = -0.52, P = 0.005, respectively). Although the number of spinal T2 lesions correlated with sensory disturbances (r = 0.60, P = 0.001), no correlations were found between EDSS subscores and spinal cord atrophy. These findings show that marked atrophy of brain and spinal cord detected by volumetric quantitation correlates with neurological disability. This observation indicates the importance of neurodegenerative events in PPMS.

In recent years increasing evidence has been provided on frequent simultaneous coexistence of inflammatory diseases and allergies in upper and lower airways. To achieve a good standard of measurement of upper airways, an objective method should be used. A total of 48 nasal cavities with nasal stuffiness associated with chronic sinusitis were measured with acoustic rhinometry (AR) and High-resolution computer tomography volumetry (HRCTV). Comparison of volumes and minimum cross-sectional areas measured with these methods was performed. The volumes measured from the nostril with both methods were the anterior (0–10 mm), middle (11–40 mm) and posterior (41–70 mm) volumes. The AR cross-sectional area curve was analysed based on two minimal notches corresponding to local minimal areas. A series of 1-mm coronal CT images without intervening gaps were made and analysed based on two minimal voxel values, which were later converted to cross-sectional areas corresponding to local, minimum cross-sectional areas (MCA). Furthermore, the distances of these 2 MCAs from the nostril were also measured. Strong statistically significant (P

Objective. To estimate fetal volume and weight in diabetic and normal pregnancy using high-resolution magnetic resonance imaging. Methods. T1-weighted magnetic resonance imaging was combined with semiautomatic segmentation technique. The accuracy of fetal volume estimations thus obtained was compared with conventional ultrasound-based weight estimations in ten pregnant women with insulin-dependent diabetes mellitus and ten women with normal pregnancy. Examinations were made within 48 hours before delivery. Results. Ultrasound-based estimations of fetal weight showed a correlation rate of r =0.77 with the actual birth weights in the whole material, while volume determinations based on magnetic resonance imaging showed a significantly better correlation rate of r =0.95. Diabetic women did not differ from the normal pregnancy group with regard to birth weight or the accuracy of weight estimations. Conclusions. High-resolution magnetic resonance imaging combined with semiautomatic segmentation software was fo...

The applications of a new segmentation software, Anatomatic, in the evaluation of volumetric measurements of brain infarctions and the new Medimag 3D software in the evaluation of 3D image representation of infarctions are described. These programs are applied to magnetic resonance imaging. The aim of this study is to evaluate the use of these software packages in making accurate volumetric measurements in 40 patients with right cerebral infarctions, in determining the correlations between the quantitated lesions and neurological/neuropsychological dysfunctions and in creating realistic 3D views of the infarctions. Using Anatomatic, reproducible infarction volumes were achieved with ease and within a reasonably fast time. Medimag helped achieve realistic 3D representations of the infarctions. When compared, the semiautomatic segmentation proved to be much faster and yielded higher infarction volumes than the manual segmentation technique. Significantly positive correlations between the infarction volumes and neurological dysfunctions and neuropsychological deficit (neglect) helped to explain the effect of volumes on the clinical status of the patients.

The objectives of the present study was to correlate the segmented magnetic resonance imaging (MRI) volumes of intracranial cerebrospinal fluid (CSF) spaces (expressing the extent of brain atrophy) and cerebral plaques with the neurological disability in secondary progressive multiple sclerosis (MS). Earlier studies have mainly correlated MS plaques and neurological disability measured by expanded disability status scale (EDSS). The data on the association between brain atrophy and EDSS or regional functional scoring scale (RFSS) are very limited. We measured the volumes of intracranial CSF spaces in 28 patients with secondary progressive MS using MRI, and semiautomatic segmentation software. The volumes of T1-weighted hypointense and T2-weighted hyperintense MS plaques were also measured. In multiple regression analysis, increasing volumes of total (P=0.006) and relative (P=0.005) intracranial CSF spaces were significantly associated with worsening neurological disability as expressed by EDSS. No associations were found between these intracranial CSF space volumes and total RFSS scores. The mean volume of T2-weighted plaques showed a tendency to associate with total RFSS score (r=0.40, P=0.03), but no correlations were detected between T1- or T2-weighted plaque volumes and EDSS. The application of a new segmentation technique in quantifying intracranial cerebrospinal fluid spaces allowed an exact and sensitive way of assessing brain atrophy. The associations between brain atrophy and neurological disability expressed by EDSS suggests that the effect of MS therapies should be evaluated by measurement of brain atrophy.

The electroencephalogram (EEG) visualization software was developed containing two-dimensional (2D) and three-dimensional (3D) brain mapping modules. The input to the program is standard clinical individual patient data recorded using digital EEG and magnetic resonance imaging (MRI). The software utilizes several techniques, such as heuristic triangulation, ray casting, Gouraud shading, and image fusion to form multimodal 3D images. The program has been applied to the 3D visualization of various EEG signals, "cortical" EEG signals, and potential fields generated by a computer model. The developed program appears to operate efficiently and intuitively in PC/Windows environment.

Semiautomatic segmentation methods using High Resolution Computed Tomography (HRCT) or Magnetic Resonance Imaging give accurate and reproducible volumetric measurements in various intracranial diseases. In this prospective study, for the first time in literature, with the help of a new semiautomatic segmentation technique and coronal HRCT, we correlated the volumes and cross-sectional areas of the nasal cavity with those obtained by clinical acoustic rhinometry in 14 patients with chronic sinusitis. The measurements obtained by both techniques showed statistically significant correlations between volumes in the anterior and middle parts, but statistically poor correlations between the volumes in the posterior part of the nasal cavity. Coronal HRCT and our new microcomputer applicable semiautomatic segmentation software proved compatible with daily clinical practice. Based on the promising results of our study, we recommend the use of this technique in the validation studies of acoustic rhinometry and in complicated cases as a complementary examination in the evaluation of nasal cavity.

This study focuses on three-dimensional (3D) presentations of medical images such as magnetic resonance (MR) images and computed tomography (CT) images. Also multimodal presentations of medical images and signals, including different visualization techniques are considered. A C++ class library together with graphical user interfaces was developed for presenting the results. The implemented software operates in PC/Windows environment. It was tested with various medical images including raw MR and CT data and segmented images, and was applied in a hospital environment. The software operates relatively fast and the quality of resulting pictures is adequate for all tested medical applications. Further applications of 3D presentations in clinical medicine are considered.

A large number of computerized conductivity models of the human thorax have been created to study bioelectric phenomena in human beings. Devised models have varied greatly in the level of anatomical detail incorporated thus restricting the accuracy and validity of conducted simulations. This paper introduces a highly detailed anatomically accurate three-dimensional computer model of the conductive anatomy of the human thorax for calculating electric fields generated by equivalent bioelectric sources and different externally applied sources. The anatomy of the devised model is based on high resolution colour cryosection images of the US National Library of Medicine's Visible Human Man data set and is comprised of more anatomical detail than prior computer models. The model is based on the finite difference method and is readily applicable for the analysis of a wide range of biomedical field problems, such as electrocardiography, impedance cardiography, tissue stimulations, and especially, in development of measurement systems.

This paper describes a segmentation method primarily developed for reconstructing resistive head models for electroencephalographic modelling purposes. The method was implemented by combining several image processing techniques, such as amplitude segmentation, region growing, and image fusion. Also a graphical user interface was developed to enable semiautomatic approach to the segmentation process. This method was developed especially for segmentation of the brain and skull from T1-weighted magnetic resonance images, but can also be applied in any segmentation procedure. The entire project was implemented successfully in a PC-based computer running the Unix/NeXTstep ™ operating system.

Objective: The aim of this study was to determine the volume of non―Hodgkin lymphomas (NHLs) using semiautomatic segmentation and to correlate these results with clinical findings, treatment, and prognosis in patients with B-cell―type NHL. Methods: For this study, 29 patients with NHL underwent magnetic resonance imaging at 5 time points after onset of disease. Volumetric analysis of the tumors was accomplished with semiautomatic segmentation by the Anatomatic software. Results: The median tumor volumes from the first to the fifth examination were 468, 256, 90, 38, and 33 cm 3 . Good correlation with 1-dimensional and 2-dimensional measures, used as standard methods in response categorization, was found. Surprisingly, volume reductions in excess of 239 cm 3 after only 1 week of chemotherapy decreased the survival probability. Conclusions: Volume measurements seem to be highly informative for prognosis in the very early stages of treatment for patients with NHL.

The need for quantitative image analysis, especially for MR images, is increasing because of the promising results in diagnosis and follow up of various clinical treatments. This document describes briefly a new software project targeted to computer aided diagnosis. The research focus has been in image segmentation, texture analysis, and volumetric analysis. The developed software enables boundary based segmentation algorithms, and provides interfaces for further analysis of the data. The software is based on two previously started software projects of our research group: Anatomatic+ and Segmentator. The new software has an intuitive user interface and is fast enough for use in medical scientific and practical work.

The popularity of digital imaging devices and PACS installations has increased during the last years. Still, images are analyzed and diagnosed using conventional techniques. Our research group begun to study the requirements for digital image diagnostic methods to be applied together with PACS systems. The research was focused on various image analysis procedures (e.g., segmentation, volumetry, 3D visualization, image fusion, anatomic atlas, etc.) that could be useful in medical diagnosis. We have developed Image Analysis software (www.medimag.net) to enable several image-processing applications in medical diagnosis, such as volumetry, multimodal visualization, and 3D visualizations. We have also developed a commercial scalable image archive system (ActaServer, supports DICOM) based on component technology (www.acta.fi), and several telemedicine applications. All the software and systems operate in NT environment and are in clinical use in several hospitals. The analysis software have been applied in clinical work and utilized in numerous patient cases (500 patients). This method has been used in the diagnosis, therapy and follow-up in various diseases of the central nervous system (CNS), respiratory system (RS) and human reproductive system (HRS). In many of these diseases e.g. Systemic Lupus Erythematosus (CNS), nasal airways diseases (RS) and ovarian tumors (HRS), these methods have been used for the first time in clinical work. According to our results, digital diagnosis improves diagnostic capabilities, and together with PACS installations it will become standard tool during the next decade by enabling more accurate diagnosis and patient follow-up.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The application of a new segmentation software, Anatomatic in the evaluation of volumetric measurements of ovarian tumours and the new Medimag three-dimensional (3D) software in the evaluation of 3D image representation of ovarian tumours with 1.5 T magnetic resonance imaging (MRI) is described. Our goal was to compare MRI based volumetry with operative findings at laparotomy for six consecutive patients with suspected ovarian tumours. Volumetric analysis and three dimensional image reconstructions of the tumours were obtained. At laparotomy, the tumour sizes were measured in situ, and the volumes were calculated. Using Anatomatic, reproducible tumour volumes were achieved with ease and within a reasonably fast time in patients with ovarian tumours without ascites. Medimag helped achieve realistic 3D representations of the tumours. For the four solitary tumours segmentation based volumetry and laparotomy findings agreed in three cases. In one patient with an oval shaped tumour, the segmented volume was double as compared to that estimated at laparotomy. Of the two patients with multiple tumours, both patients had significant ascites, and volumetry misinterpreted the fluid as tumour cyst fluid and markedly overestimated the tumour size. In conclusion, the MRI based segmentation volumetry and 3D image reconstructions are rapid, and reproducible methods of measuring ovarian tumours in patients without significant ascites.

The paper describes the application of new semi-automatic segmentation software to the task of detection of anatomical structures and lesion and their three-dimensional (3D) visualisation in 23 patients with secondary progressive multiple sclerosis (MS). The purpose is to study the correlation between magnetic resonance imaging (MRI) parameters (volumes of plaques and cerebrospinal fluid spaces) and clinical deficits (neurological deficits in the form of EDSS and RFSS scores, and neuropsychological deficits). The software operates in PC/Windows and PC/NeXTstep environments and utilises graphical user interfaces. Quantitative accuracy is measured by performing segmentation of fluid-filled syringes (relative error of 1.5%), and reproducibility is measured by intra- and inter-observer studies (3% and 7% variability, respectively). The mean volumes of MS plaques show significant correlations with the total RFSS scores (p = 0.04). Relative intracranial cerebrospinal fluid (CSF) space volumes show statistically significant correlation with EDSS scores (p = 0.01). The mean volume of MS plaques shows a significant correlation with the overall neuropsychological deficits (p = 0.03). 3D visualisation helps to understand the relationship of lesions to the surrounding brain structures. The use of semiautomatic segmentation techniques is recommended in the clinical diagnosis of MS patients.

After the introduction of digital imagin devices in medicine computerized tissue recognition and classification have become important in research and clinical applications. Segmented data can be applied among numerous research fields including volumetric analysis of particular tissues and structures, construction of anatomical modes, 3D visualization, and multimodal visualization, hence making segmentation essential in modern image analysis. In this research project several PC based software were developed in order to segment medical images, to visualize raw and segmented images in 3D, and to produce EEG brain maps in which MR images and EEG signals were integrated. The software package was tested and validated in numerous clinical research projects in hospital environment.

The objective of this study was to determine nasal cavity volumes and cross-sectional profiles from segmented coronal high-resolution computed tomography (HRCT) images. Pathological mucosal changes and congenital sinonasal variants were quantitated and three-dimensional (3D) images for determining sinonasal airway diseases evaluated by using the new semiautomatic segmentation software, Anatomatic. Anterior to posterior cross-sectional profiles of the sinonasal airway were obtained from acoustic rhinometry and segmented coronal HRCT images and compared in five patients having complaints of nasal obstruction and chronic sinusitis. Results showed that accurate volumes of air spaces in the nasal cavity and paranasal sinuses were obtained. When compared, the cross-sectional profiles of the nasal cavities obtained from acoustic rhinometry and the segmentation technique were similar in the anterior portion, but differed in the posterior portion. The results obtained by coronal HRCT and segmentation were more reliable than those produced with acoustic rhinometry. 3D images acquired from segmented images were found to help make a good pre-operative assessment of the whole sinonasal compartment. Segmentation and volumetric analysis using the Anatomatic technique also proved to be well suited to the evaluation of the nasal cavity and paranasal sinus geometry in patients with sinonasal diseases.

Quantitative magnetic resonance (MR) imaging of the brain is useful in multiple sclerosis (MS) in order to obtain reliable indices of disease progression. The goal of this project was to estimate the total volume of gliotic and non gliotic plaques in chronic progressive multiple sclerosis with the help of a semiautomatic segmentation method developed at the Ragnar Granit Institute. Youth developed program running on a PC based computer provides de displays of the segmented data, in addition to the volumetric analyses. The volumetric accuracy of the program was demonstrated by segmenting MR images of fluid filed syringes. An anatomical atlas is to be incorporated in the segmentation system to estimate the distribution of MS plaques in various neural pathways of the brain. A total package including MS plaque volume estimation, estimation of brain atrophy and ventricular enlargement, distribution of MS plaques in different neural segments of the brain has ben planned for the near future. Our study confirmed that total lesion volumes in chronic MS disease show a poor correlation to EDSS scores but show a positive correlation to neuropsychological scores. Therefore accurate total volume measurements of MS plaques using the developed semiautomatic segmentation technique helped us to evaluate the degree of neuropsychological impairment.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Background To show magnetic resonance imaging (MRI) texture appearance change in non-Hodgkin lymphoma (NHL) during treatment with response controlled by quantitative volume analysis. Methods A total of 19 patients having NHL with an evaluable lymphoma lesion were scanned at three imaging timepoints with 1.5T device during clinical treatment evaluation. Texture characteristics of images were analyzed and classified with MaZda application and statistical tests. Results NHL tissue MRI texture imaged before treatment and under chemotherapy was classified within several subgroups, showing best discrimination with 96% correct classification in non-linear discriminant analysis of T2-weighted images. Texture parameters of MRI data were successfully tested with statistical tests to assess the impact of the separability of the parameters in evaluating chemotherapy response in lymphoma tissue. Conclusion Texture characteristics of MRI data were classified successfully; this proved texture analysis to be potential quantitative means of representing lymphoma tissue changes during chemotherapy response monitoring.