An introduction to machine learning for classification and prediction.

Classification and prediction tasks are common in health research. With the increasing availability of vast health data repositories (e.g. electronic medical record databases) and advances in computing power, traditional statistical approaches are being augmented or replaced with machine learning (ML) approaches to classify and predict health outcomes. ML describes the automated process of identifying ("learning") patterns in data to perform tasks. Developing an ML model includes selecting between many ML models (e.g. decision trees, support vector machines, neural networks); model specifications such as hyperparameter tuning; and evaluation of model performance. This process is conducted repeatedly to find the model and corresponding specifications that optimize some measure of model performance. ML models can make more accurate classifications and predictions than their statistical counterparts and confer greater flexibility when modelling unstructured data or interactions between covariates; however, many ML models require larger sample sizes to achieve good classification or predictive performance and have been criticized as "black box" for their poor transparency and interpretability. ML holds potential in family medicine for risk profiling of patients' disease risk and clinical decision support to present additional information at times of uncertainty or high demand. In the future, ML approaches are positioned to become commonplace in family medicine. As such, it is important to understand the objectives that can be addressed using ML approaches and the associated techniques and limitations. This article provides a brief introduction into the use of ML approaches for classification and prediction tasks in family medicine.

Barriers and Considerations in the Design and Implementation of Digital Behavioral Interventions: Qualitative Analysis.

BACKGROUND: Digital behavioral interventions have become increasingly popular for their ability to support patient diagnosis and treatment, chronic disease self-management, behavior change, and adherence to recommended care. However, digital intervention development is impeded by challenges such as limited technical skills, limited access to developers, and cost. The purpose of this study is to elicit in-depth qualitative feedback from intervention developers who have interest in digital behavioral interventions but lack programming skills regarding the barriers they experience and key considerations in the design and implementation of digital interventions. OBJECTIVE: This study aims to understand barriers in the design and implementation of digital behavioral interventions, as well as to identify key considerations for researchers who are developing these interventions. METHODS: We conducted semistructured qualitative interviews with 18 researchers who had experience either designing (but not coding) digital behavioral interventions or running research studies with them. Participants were a convenience sample of users of the Computerized Intervention Authoring System platform, an existing no-code development platform for building digital intervention content, and were recruited through either direct email solicitation or snowball sampling. All interviews were conducted and recorded over videoconference between February and April 2020. Recordings from interviews were transcribed and thematically analyzed by multiple coders. RESULTS: Interviews were completed with 18 participants and lasted between 24 and 65 (mean 46.9, SD 11.3) minutes. Interviewees were predominantly female (17/18, 94%) and represented different job roles, ranging from researcher to project/study staff. Three key barriers in the development of digital behavior interventions were identified during interviews: lack of cross-disciplinary understanding; variability in recipients' technology access, infrastructure, and literacy; and the idea that evidence-based in-person interactions do not translate directly to digital interactions. Interviewees identified several key considerations that interventionists learned to prioritize, which have the potential to overcome these barriers and lead to successful interventions. CONCLUSIONS: Barriers in the development of digital behavioral interventions are often created by a lack of cross-disciplinary understanding, which can lead to difficulties conceptualizing interventions, unrealistic expectations in terms of cost, and confusion about the development process. Moreover, concerns about research study participant characteristics and access to technology, as well as the translation of in-person interventions to digital, are apparent. Appropriate training in how to work with software development teams may help future digital behavior intervention creators overcome these barriers and may lead to new, exciting innovations in this space.

The Perceived Benefits of Digital Interventions for Behavioral Health: Qualitative Interview Study.

BACKGROUND: Digital interventions have gained momentum in terms of behavioral health. However, owing to lacking standard approaches or tools for creating digital behavioral interventions, clinical researchers follow widely varying conceptions of how best to go about digital intervention development. Researchers also face significant cost-, time-, and expertise-related challenges in digital intervention development. Improving the availability of tools and guidance for researchers will require a thorough understanding of the motivations and needs of researchers seeking to create digital interventions. OBJECTIVE: This study aims to understand the perceptions of behavioral researchers toward digital interventions, and inform the use of these interventions, by documenting the reasons why researchers are increasingly focusing their efforts on digital interventions and their perspectives on the perceived benefits that digital approaches can provide for researchers and intervention recipients. METHODS: We conducted semistructured qualitative interviews with 18 researchers who had experience designing digital behavioral interventions or running studies with them. A convenience sample of interviewees was recruited from among users of the Computerized Intervention Authoring System platform, a web-based tool that facilitates the process of creating and deploying digital interventions in behavioral research. Interviews were conducted over teleconference between February and April 2020. Recordings from the interviews were transcribed and thematically analyzed by multiple coders. RESULTS: Interviews were completed with 18 individuals and lasted between 24 and 65 (mean 46.9, SD 11.3) minutes. Interviewees were predominantly female (17/18, 94%) and represented different job roles, ranging from researcher to project or study staff. Four major themes came out of the interviews concerning the benefits of digital interventions for behavioral health: convenience and flexibility for interventionists and recipients, support for implementing evidence-based interventions with fidelity, scaling and improving access to interventions, and getting a foot in the door despite stigma and disenfranchisement. CONCLUSIONS: Interviewees described a number of important potential benefits of digital interventions, particularly with respect to scientific rigor, scalability, and overcoming barriers to reaching more people. There are complex considerations with regard to translating behavior change strategies into digital forms of delivery, and interventionists make individual, sometimes unexpected, choices with minimal evidence of their relative effectiveness. Future research should investigate how behavioral researchers can be supported in making these choices toward usability, ease of access, and approachability of digital interventions. Our study underscores the need for authoring platforms that can facilitate the process of creating and deploying digital interventions to reach their full potential for interventionists and recipients alike.

Spirometry-based reconstruction of real-time cardiac MRI: Motion control and quantification of heart-lung interactions.

PURPOSE: To test the feasibility of cardiac real-time MRI in combination with retrospective gating by MR-compatible spirometry, to improve motion control, and to allow quantification of respiratory-induced changes during free-breathing. METHODS: Cross-sectional real-time MRI (1.5T; 30 frames/s) using steady-state free precession contrast during free-breathing was combined with MR-compatible spirometry in healthy adult volunteers (n = 4). Retrospective binning assigned images to classes that were defined by electrocardiogram and spirometry. Left ventricular eccentricity index as an indicator of septal position and ventricular volumes in different respiratory phases were calculated to assess heart-lung interactions. RESULTS: Real-time MRI with MR-compatible spirometry is feasible and well tolerated. Spirometry-based binning improved motion control significantly. The end-diastolic epicardial eccentricity index increased significantly during inspiration (1.04 ± 0.04 to 1.19 ± 0.05; P < .05). During inspiration, right ventricular end-diastolic volume (79 ± 17 mL/m2 to 98 ± 18 mL/m2 ), stroke volume (41 ± 8 mL/m2 to 59 ± 11 mL/m2 ) and ejection fraction (53 ± 3% to 60 ± 1%) increased significantly, whereas the end-systolic volume remained almost unchanged. Left ventricular end-diastolic volume, left ventricular stroke volume, and left ventricular ejection fraction decreased during inspiration, whereas the left ventricular end-systolic volume increased. The relationship between stroke volume and end-diastolic volume (Frank-Starling relationship) based on changes induced by respiration allowed for a slope estimate of the Frank-Starling curve to be 0.9 to 1.1. CONCLUSION: Real-time MRI during free-breathing combined with MR-compatible spirometry and retrospective binning improves image stabilization, allows quantitative image analysis, and importantly, offers unique opportunities to judge heart-lung interactions.

How can we combat multicenter variability in MR radiomics? Validation of a correction procedure.

OBJECTIVE: Test a practical realignment approach to compensate the technical variability of MR radiomic features. METHODS: T1 phantom images acquired on 2 scanners, FLAIR and contrast-enhanced T1-weighted (CE-T1w) images of 18 brain tumor patients scanned on both 1.5-T and 3-T scanners, and 36 T2-weighted (T2w) images of prostate cancer patients scanned in one of two centers were investigated. The ComBat procedure was used for harmonizing radiomic features. Differences in statistical distributions in feature values between 1.5- and 3-T images were tested before and after harmonization. The prostate studies were used to determine the impact of harmonization to distinguish between Gleason grades (GGs). RESULTS: In the phantom data, 40 out of 42 radiomic feature values were significantly different between the 2 scanners before harmonization and none after. In white matter regions, the statistical distributions of features were significantly different (p < 0.05) between the 1.5- and 3-T images for 37 out of 42 features in both FLAIR and CE-T1w images. After harmonization, no statistically significant differences were observed. In brain tumors, 41 (FLAIR) or 36 (CE-T1w) out of 42 features were significantly different between the 1.5- and 3-T images without harmonization, against 1 (FLAIR) or none (CE-T1w) with harmonization. In prostate studies, 636 radiomic features were significantly different between GGs after harmonization against 461 before. The ability to distinguish between GGs using radiomic features was increased after harmonization. CONCLUSION: ComBat harmonization efficiently removes inter-center technical inconsistencies in radiomic feature values and increases the sensitivity of studies using data from several scanners. KEY POINTS: • Radiomic feature values obtained using different MR scanners or imaging protocols can be harmonized by combining off-the-shelf image standardization and feature realignment procedures. • Harmonized radiomic features enable one to pool data from different scanners and centers without a substantial loss of statistical power caused by intra- and inter-center variability. • The proposed realignment method is applicable to radiomic features from different MR sequences and tumor types and does not rely on any phantom acquisition.

Impact of breath-hold level on positional error aligned by stent/Lipiodol in Hepatobiliary radiotherapy with breath-hold respiratory control.

BACKGROUND: Respiratory motion management with breath hold for patients with hepatobiliary cancers remain a challenge in the precise positioning for radiotherapy. We compared different image-guided alignment markers for estimating positional errors, and investigated the factors associated with positional errors under breath-hold control. METHODS: Spirometric motion management system (SDX) for breath holds was used in 44 patients with hepatobiliary tumor. Among them, 28 patients had a stent or embolized materials (lipiodol) as alignment markers. Cone-beam computed tomography (CBCT) and kV-orthogonal images were compared for accuracy between different alignment references. Breath-hold level (BHL) was practiced, and BHL variation (ΔBHL) was defined as the standard deviation in differences between actual BHLs and baseline BHL. Mean BHL, ΔBHL, and body-related factors were analyzed for the association with positional errors. RESULTS: Using the reference CBCT, the correlations of positional errors were significantly higher in those with stent/lipiodol than when the vertebral bone was used for alignment in three dimensions. Patients with mean BHL > 1.4 L were significantly taller (167.6 cm vs. 161.6 cm, p = 0.03) and heavier (67.1 kg vs. 57.4 kg, p = 0.02), and had different positional error in the craniocaudal direction (- 0.26 cm [caudally] vs. + 0.09 cm [cranially], p = 0.01) than those with mean BHL < 1.4 L. Positional errors were similar for patients with ΔBHL< 0.03 L and > 0.03 L. CONCLUSION: Under rigorous breath-hold respiratory control, BHL correlated with body weight and height. With more accurate alignment reference by stent/lipiodol, actual BHL but not breath-hold variation was associated with craniocaudal positional errors.

Head CT: Image quality improvement with ASIR-V using a reduced radiation dose protocol for children.

OBJECTIVE: To investigate the quality of images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V), using pediatric head CT protocols. METHODS: A phantom was scanned at decreasing 20% mA intervals using our standard pediatric head CT protocols. Each study was then reconstructed at 10% ASIR-V intervals. After the phantom study, we reduced mA by 10% in the protocol for <3-year-old patients and applied 30% ASIR-V and by 30% in the protocol for 3- to 15-year-old patients and applied 40% ASIR-V. RESULTS: Increasing the percentage of ASIR-V resulted in lower noise and higher contrast-to-noise ratio (CNR) and preserved spatial resolution in the phantom study. Compared to a conventional-protocol, reduced-dose protocol with ASIR-V achieved 12.8% to 34.0% of dose reduction and showed images of lower noise (9.22 vs. 10.73, P = 0.043) and higher CNR in different levels (centrum semiovale, 2.14 vs. 1.52, P = 0.003; basal ganglia, 1.46 vs. 1.07, P = 0.001; and cerebellum, 2.18 vs. 1.33, P < 0.001). Qualitative analysis showed higher gray-white matter differentiation and sharpness and preserved overall diagnostic quality in the images with ASIR-V. CONCLUSIONS: Use of ASIR-V allowed a 12.8% to 34.0% dose reduction in each age group with potential to improve image quality. KEY POINTS: • It is possible to reduce radiation dose and improve image quality with ASIR-V. • We improved noise and CNR and decreased radiation dose. • Sharpness improved with ASIR-V. • Total radiation dose was decreased by 12.8% to 34.0%.

Application of diffusion kurtosis imaging to odontogenic lesions: Analysis of the cystic component.

PURPOSE: To assess the feasibility of applying diffusion kurtosis imaging (DKI) to common odontogenic lesions and to compare its diagnostic ability versus that of the apparent diffusion coefficient (ADC) for differentiating keratocystic odontogenic tumors (KCOTs) from odontogenic cysts. MATERIALS AND METHODS: Altogether, 35 odontogenic lesions were studied: 24 odontogenic cysts, six KCOTs, and five ameloblastomas. The diffusion coefficient (D) and excessive kurtosis (K) were obtained from diffusion-weighted images at b-values of 0, 500, 1000, and 1500 s/mm2 on 3T magnetic resonance imaging (MRI). The combination of D and K values showing the maximum density of the probable density function was estimated. The ADC was obtained (0 and 1000 s/mm2 ). Values for odontogenic cysts, KCOTs, and ameloblastomas were compared. Multivariate logistic regression modeling was performed to assess the combination of D and K model versus ADC for differentiating KCOTs from odontogenic cysts. RESULTS: The mean D and ADC were significantly higher for ameloblastomas than for odontogenic cysts or KCOTs (P < 0.05). The mean K was significantly lower for ameloblastomas than for odontogenic cysts or KCOTs (P < 0.05). The mean values of all parameters for odontogenic cysts and KCOTs showed no significant differences (P = 0.369 for ADC, 0.133 for D, and 0.874 for K). The accuracy of the combination of D and K model (76.7%) was superior to that of ADC (66.7%). CONCLUSION: Use of DKI may be feasible for common odontogenic lesions. A combination of DKI parameters can be expected to increase the accuracy of its diagnostic ability compared with ADC. J. Magn. Reson. Imaging 2016;44:1565-1571.

Head CT: Image quality improvement of posterior fossa and radiation dose reduction with ASiR - comparative studies of CT head examinations.

OBJECTIVES: To evaluate head CT protocol developed to improve visibility of the brainstem and cerebellum, lower bone-related artefacts in the posterior fossa and maintain patient radioprotection. METHODS: A paired comparison of head CT performed without Adaptive Statistical Iterative Reconstruction (ASiR) and a clinically indicated follow-up with 40 % ASiR was acquired in one group of 55 patients. Patients were scanned in the axial mode with different scanner settings for the brain and the posterior fossa. Objective image quality analysis was performed with signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Subjective image quality analysis was based on brain structure visibility and evaluation of the artefacts. RESULTS: We achieved 19 % reduction of total DLP and significantly better image quality of posterior fossa structures. SNR for white and grey matter in the cerebellum were 34 % to 36 % higher, respectively, CNR was improved by 142 % and subjective analyses were better for images with ASiR. CONCLUSIONS: When imaging parameters are set independently for the brain and the posterior fossa imaging, ASiR has a great potential to improve CT performance: image quality of the brainstem and cerebellum is improved, and radiation dose for the brain as well as total radiation dose are reduced. KEY POINTS: •With ASiR it is possible to lower radiation dose or improve image quality •Sequentional imaging allows setting scan parameters for brain and posterior-fossa independently •We improved visibility of brainstem structures and decreased radiation dose •Total radiation dose (DLP) was decreased by 19.

Comparison of contemporary methods for estimating prostate tumour volume in pathological specimens.

OBJECTIVE: To evaluate the accuracy of various prostate tumour volume (TV) estimation methods. To determine the most appropriate estimation method for current clinical practice. PATIENTS AND METHODS: Radical prostatectomy (RP) specimens from multiple institutions were analysed by a single uro-pathologist between September 2009 and May 2011. Tumour properties including thickness, width and length were collected and TV was established using computer-assisted image analysis (CAIA). TV estimation methods including; square, cuboidal and ellipsoidal estimations were calculated using previously reported formulae. The estimation methods were compared against the 'gold-standard' and the accuracy of identifying clinically significant tumours of TV ≥0.5 cc was determined. RESULTS: In all, 299 consecutive specimens were analysed by a single uropathologist. The median index TV on CAIA was 1.42 cc. Of the four estimation methods, the ellipsoid methods produced the closest correlation with the gold-standard (r(2) 0.91, P = 0.71). This correlation lost accuracy when larger tumours (TV >4 cc) were excluded from the analysis (r(2) = 0.73, P = 0.003). Sensitivity and specificity for identifying clinically significant tumours was 94% and 92% respectively, when using the ellipsoid estimation. CONCLUSIONS: In current uro-pathology, the ellipsoidal estimation method appears to be the most suitable for estimating TV in prostate cancers. This method is cheap, reproducible and sensitive and can be safely used as a surrogate for CAIA volumes when such technology is not available.

Pedicle Screw Pseudofracture on Computed Tomography Secondary to Metal Artifact Reduction.

Metal artifact reduction (MAR) algorithms are commonly used in computed tomography (CT) scans where metal implants are involved. However, MAR algorithms also have the potential to create new artifacts in reconstructed images. We present a case of a screw pseudofracture due to MAR on CT.

Low-cost and open-source three-dimensional (3D) printing in neurosurgery: A pilot experiment using direct drive modification to produce multi-material neuroanatomical models.

BACKGROUND: 3-dimensional (3D) printing carries a genuine potential for pre-operative planning in neurosurgery. Entry-level 3D printers offer practicality in low resource settings, but are often limited by the range of filament materials as well as the capability of open-source segmentation software. OBJECTIVE: We intended to demonstrate that 3D printing of neuroanatomical structures is possible using an entry-level 3D printer equipped with the direct drive (DD) modification, which supported flexible filaments, with the models segmented using an open-source software. METHODS: A DD system was installed onto the Ender 3 Pro printer. An attempt to print neurosurgical models using a low-cost 3D printer was conducted, where four patient-based neuroanatomical models were printed: skull base-vasculature, skull base-tumour, cervical spine, and ventricular system. The results were discussed and compared to similar endeavours in past literature. RESULTS: Although DD installation was challenging and led to vibration and longer print time, which ultimately warranted an inferior printing speed, DD system enabled the printing with thermoplastic polyurethane (TPU), a versatile elastomer; in addition to producing equal amount of detail to those printed with high-end printers and advanced image segmentation software. Fitting the frame well, changing infill type, and avoiding warping and stringing will improve print quality with the DD system. CONCLUSION: 3D printing with entry-level 3D printers equipped with DD system has been proven to be a reliable way of accurately reproducing patient-specific neuroanatomical constructs. Follow-up studies are necessary to implement 3D printing for neurosurgical planning in low-resource settings.

A systematic review and future research agenda on detection of polycystic ovary syndrome (PCOS) with computer-aided techniques.

Polycystic Ovary Syndrome (PCOS) is among the most prevalent endocrinological abnormalities seen in reproductive female bodies posing serious health hazards. The correctness of interpreting this condition depends heavily on the wide spectrum of associated symptoms and the doctor's expertise, making real-time clinical detection quite challenging. Thus, investigations on computer-aided PCOS detection systems have recently been explored by several researchers worldwide as a potential replacement for manual assessment. This review study's objective is to analyze the relevant research works on computer-assisted methods for automatically identifying PCOS through a systematic literature review (SLR) methodology as well as investigate the research limitations and explore potential future research scopes in this domain. 28 articles have been selected using the PRISMA approach based on a set of inclusion-exclusion criteria for conducting the review. The data synthesis of the selected articles has been conducted using six data exploration themes. As outcomes, the SLR explored the topical association between the studies; their research profiles; objectives; data size, type, and sources; methodologies applied for the detection of PCOS; and lastly the research outcomes along with their evaluation measures and performances. The study also highlights areas for future research directions examining the study gaps to enhance the current efforts for autonomous PCOS identification; such as integrating advanced techniques with the current methods; developing interactive software systems; exploring deep learning and unsupervised machine learning techniques; enhancing datasets and country context; and investigating more unknown factors behind PCOS. Thus, this SLR provides a state-of-the-art paradigm of autonomous PCOS detection which will support significantly efficient clinical assessment, diagnosis and treatment of PCOS.

Remote Analysis of Respiratory Sounds in Patients With COVID-19: Development of Fast Fourier Transform-Based Computer-Assisted Diagnostic Methods.

BACKGROUND: Respiratory sounds have been recognized as a possible indicator of behavior and health. Computer analysis of these sounds can indicate characteristic sound changes caused by COVID-19 and can be used for diagnostics of this illness. OBJECTIVE: The aim of the study is to develop 2 fast, remote computer-assisted diagnostic methods for specific acoustic phenomena associated with COVID-19 based on analysis of respiratory sounds. METHODS: Fast Fourier transform (FFT) was applied for computer analysis of respiratory sound recordings produced by hospital doctors near the mouths of 14 patients with COVID-19 (aged 18-80 years) and 17 healthy volunteers (aged 5-48 years). Recordings for 30 patients and 26 healthy persons (aged 11-67 years, 34, 60%, women), who agreed to be tested at home, were made by the individuals themselves using a mobile telephone; the records were passed for analysis using WhatsApp. For hospitalized patients, the illness was diagnosed using a set of medical methods; for outpatients, polymerase chain reaction (PCR) was used. The sampling rate of the recordings was from 44 to 96 kHz. Unlike usual computer-assisted diagnostic methods for illnesses based on respiratory sound analysis, we proposed to test the high-frequency part of the FFT spectrum (2000-6000 Hz). RESULTS: Comparing the FFT spectra of the respiratory sounds of patients and volunteers, we developed 2 computer-assisted methods of COVID-19 diagnostics and determined numerical healthy-ill criteria. These criteria were independent of gender and age of the tested person. CONCLUSIONS: The 2 proposed computer-assisted diagnostic methods, based on the analysis of the respiratory sound FFT spectra of patients and volunteers, allow one to automatically diagnose specific acoustic phenomena associated with COVID-19 with sufficiently high diagnostic values. These methods can be applied to develop noninvasive screening self-testing kits for COVID-19.

Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?

OBJECTIVE: To compare ultrasound images of the kidney obtained, randomly or in a controlled manner (standardizing the physical aspects of the ultrasound system), by various professionals and with different devices. MATERIALS AND METHODS: We evaluated a total of 919 images of kidneys, obtained by five professionals using two types of ultrasound systems, in 24 patients. The images were categorized into four types, by how they were acquired and processed. We compared the gray-scale median and different gray-scale ranges representative of virtual histological tissues. RESULTS: There were statistically significant differences among the five professionals, regardless of the type of ultrasound system employed, in terms of the gray-scale medians for the images obtained (p < 2.2e-16). Analyzing the four categories of images-a totally random image (without any standardization); a standardized image (with fixed values for gain, time gain control, and dynamic range); a normalized version of the random image; and a normalized version of the standardized image-we determined that the random image, even after normalization, differed quite significantly among the professionals (p = 0.006098). The analysis of the normalized version of the standardized image did not differ significantly among the professionals (p = 0.7319). CONCLUSION: Our findings indicate that a gray-scale analysis of ultrasound images of the kidney performs better when the image acquisition process is standardized and the images undergo a process of normalization.

OBJETIVO: Comparar imagens renais ultrassonográficas obtidas de maneira aleatória e controlada (padronizando fatores físicos do aparelho de ultrassom) por diferentes profissionais e aparelhos. MATERIAIS E MÉTODOS: Foram obtidos quatro tipos de imagens, de acordo com sua aquisição e processamento por cinco profissionais e dois tipos de aparelhos de ultrassonografia, em 24 pacientes, totalizando 919 imagens. Comparamos a mediana de escala de cinza e diferentes intervalos de tons de cinza representantes de tecidos histológicos virtuais. RESULTADOS: As medianas de escala de cinza de imagens renais obtidas por dois tipos de aparelhos foram estatisticamente diferentes (p < 2.2e-16). Analisando os quatro tipos de imagens, partindo de uma totalmente aleatória (sem qualquer padronização), uma padronizada (fixado o ganho, time gain control e dynamic range), e essas duas passando por um processo de normatização, obteve-se que a imagem aleatória é totalmente diversa entre os profissionais (p = 0,006098), mesmo passando pelo processo de normatização. A imagem padronizada, após passar pelo processo de normatização, apresentou resultados equivalentes, não possuindo diferença estatística (p = 0,7319). CONCLUSÃO: Constatou-se que na análise de tons de cinza deve-se usar um mesmo tipo de máquina e uma imagem em que sejam padronizados aspectos físicos, passando por um processo de normatização/padronização.

Ultrafast Computation of Left Ventricular Ejection Fraction by Using Temporal Intensity Variation in Cine Cardiac Magnetic Resonance.

Cardiac magnetic resonance enables comprehensive cardiac evaluation; however, intense time and labor requirements for data acquisition and processing have discouraged many clinicians from using it. We have developed an alternative image-processing algorithm that requires minimal user interaction: an ultrafast algorithm that computes left ventricular ejection fraction (LVEF) by using temporal intensity variation in cine balanced steady-state free precession (bSSFP) short-axis images, with or without contrast medium. We evaluated the algorithm's performance against an expert observer's analysis for segmenting the LV cavity in 65 study participants (LVEF range, 12%-70%). In 12 instances, contrast medium was administered before cine imaging. Bland-Altman analysis revealed quantitative effects of LV basal, midcavity, and apical morphologic variation on the algorithm's accuracy. Total computation time for the LV stack was <2.5 seconds. The algorithm accurately delineated endocardial boundaries in 1,132 of 1,216 slices (93%). When contours in the extreme basal and apical slices were not adequate, they were replaced with manually drawn contours. The Bland-Altman mean differences were <1.2 mL (0.8%) for end-diastolic volume, <5 mL (6%) for end-systolic volume, and <3% for LVEF. Standard deviation of the difference was ≤4.1% of LV volume for all sections except the midcavity in end-systole (8.3% of end-systolic volume). We conclude that temporal intensity variation-based ultrafast LVEF computation is clinically accurate across a range of LV shapes and wall motions and is suitable for postcontrast cine SSFP imaging. Our algorithm enables real-time processing of cine bSSFP images on a commercial scanner console within 3 seconds in an unobtrusive automated process.

Voxel-based superimposition of Cone Beam CT scans for orthodontic and craniofacial follow-up: Overview and clinical implementation.

INTRODUCTION: The increasing use of three-dimensional (3D) imaging in orthodontics has led to the development of 3D superimposition techniques. These techniques use stable anatomic structures as references in order to compare Cone Beam CT (CBCT) scans of the same subject at different time-points. Three methods have been described in the literature: landmark-based, surface-based and voxel-based 3D superimpositions. OBJECTIVE: This article focuses on the voxel-based approach, which is the most described and the only one that can be fully automatized. The aim of this paper is to offer clinicians a practical tutorial on craniofacial voxel-based 3D superimposition. MATERIAL AND METHODS: We provide an updated overview of the available implementation methods, describing their methodology, validations, main steps, advantages and drawbacks. The historical open-source method is the most widespread for research purposes, but takes around three hours to achieve for an experienced operator. Several commercially-available software perform superimpositions in a few minutes. RESULTS: We used two of the available methods to conduct the superimposition process with three representative clinical cases in order to illustrate the different types of results that can be obtained. CONCLUSIONS: Commercially-available software provide user-friendly and fully automatized superimposition methods, allowing clinicians to perform it easily and helping to reduce human error in image analysis. Still, quantitative evaluation of the results remains the main challenge of this technique.

Comparison of automated and manual protocols for magnetic resonance imaging assessment of liver iron concentration.

OBJECTIVE: To compare automated and manual magnetic resonance imaging protocols for estimating liver iron concentrations at 1.5 T. MATERIALS AND METHODS: Magnetic resonance imaging examination of the liver was performed in 53 patients with clinically suspected hepatic iron overload and in 21 control subjects. Liver iron concentrations were then estimated by two examiners who were blinded to the groups. The examiners employed automated T2* and T1 mapping, as well as manual T2* and signal-intensity-ratio method. We analyzed accuracy by using ROC curves. Interobserver and intraobserver agreement were analyzed by calculating two-way intraclass correlation coefficients. RESULTS: The area under the ROC curve (to discriminate between patients and controls) was 0.912 for automated T2* mapping, 0.934 for the signal-intensity-ratio method, 0.908 for manual T2*, and 0.80 for T1 mapping, the last method differing significantly from the other three. The level of interobserver and intraobserver agreement was good (intraclass correlation coefficient, 0.938-0.998; p < 0.05). Correlations involving T1 mapping, although still significant, were lower. CONCLUSION: At 1.5 T, T2* mapping is a rapid tool that shows promise for the diagnosis of liver iron overload, whereas T1 mapping shows less accuracy. The performance of T1 mapping is poorer than is that of T2* methods.

OBJETIVO: Comparar protocolos automatizados e manuais de ressonância magnética para estimar a concentração hepática de ferro em 1,5 T. MATERIAIS E MÉTODOS: Foi realizada ressonância magnética hepática em 53 pacientes com suspeita de sobrecarga de ferro hepática e 21 controles, seguida da estimativa cega da concentração hepática de ferro por dois examinadores usando mapas automáticos T2* e T1, assim como o manual T2* e o método signal-intensity-ratio. O desempenho foi medido usando curvas ROC e a correlação interobservador e intraobservador usando o coeficiente de correlação intraclasse bidirecional. RESULTADOS: O desempenho da curva ROC separando pacientes e controles mostrou áreas sob a curva de 0,912 para o mapa automático T2*, 0,934 para o método signal-intensity-ratio, 0,908 para manual T2* e 0,80 para mapa T1 (este difere significativamente dos outros três métodos). Houve boa correlação interobservador e intraobservador (coeficiente de correlação intraclasse entre 0,938 e 0,998; p < 0,05). Correlações envolvendo o mapa T1, embora ainda significativas, foram menores. CONCLUSÃO: Em 1,5 T, o mapa T2* representa uma nova ferramenta rápida e promissora para avaliar o diagnóstico de sobrecarga de ferro hepática, enquanto o mapa T1 mostrou menor precisão. O desempenho do mapa T1 foi menor que o dos métodos T2*.

A study of the clinical, treatment planning and dosimetric feasibility of dose painting in external beam radiotherapy of prostate cancer.

BACKGROUND AND PURPOSE: Radiotherapy dose painting is a promising technique which enables dose escalation to areas of higher tumour cell density within the prostate which are associated with radioresistance, known as dominant intraprostatic lesions (DILs). The aim of this study was to determine factors affecting the feasibility of radiotherapy dose painting in patients with high and intermediate risk prostate cancer. MATERIALS & METHODS: Twenty patients were recruited into the study for imaging using a 3 T magnetic resonance imaging (MRI) scanner. Identified DILs were outlined and the scan registered with the planning computed tomography (CT) dataset. Intensity-modulated plans were produced and evaluated to determine the effect of the organ-at-risk constraints on the dose that could be delivered to the DILs. Measurements were made to verify that the distribution could be safely delivered. RESULTS: MRI scans were obtained for nineteen patients. Fourteen patients had one to two DILs with ten overlapping the urethra and/or rectum. The target boost of 86 Gy was achieved in seven plans but was limited to 80 Gy for five patients whose boost volume overlapped or abutted the urethra. Dosimetric measurements gave a satisfactory gamma pass rate at 3%/3 mm. CONCLUSIONS: It was feasible to produce dose-painted plans for a boost of 86 Gy for approximately half the patients with DILs. The main limiting factor was the proximity of the urethra to the boost volumes. For a small proportion of patients, rigid registration between CT and MRI images was not adequate for planning purposes.

Quantitative evaluation of brain volume among elderly individuals in São Paulo, Brazil: a population-based study.

OBJECTIVE: To perform a quantitative analysis of the brain volume of elderly individuals in a population-based sample. MATERIALS AND METHODS: This was a radiological assessment and voxel-based quantitative analysis, with surface alignment, of 525 magnetic resonance imaging scans of individuals between 60 and 103 years of age who participated in the Saúde, Bem-estar e Envelhecimento (Health, Well-being, and Aging) study in the city of São Paulo, Brazil. RESULTS: We noted a median rate of reduction in total brain volume of 2.4% per decade after 60 years of age. Gray and white matter both showed volume reductions with age. The total brain volume/intracranial brain volume ratio differed between males and females. CONCLUSION: We have corroborated the findings of studies conducted in the United States and Europe. The total brain volume/intracranial brain volume ratio is higher in men, representing a potential bias for the conventional radiological assessment of atrophy, which is typically based on the evaluation of the cerebrospinal fluid spaces.

OBJETIVO: Analisar, quantitativamente, o volume cerebral de idosos em uma amostra de base populacional em São Paulo. MATERIAIS E MÉTODOS: O estudo é uma avaliação radiológica e análise quantitativa baseada em voxel com alinhamento de superfície de 525 imagens de ressonância magnética de participantes de uma coorte de idosos (SABE - Saúde, Bem-estar e Envelhecimento) em São Paulo, Brasil, com idades de 60 a 103 anos, dos dois sexos. RESULTADOS: Observamos redução média do volume cerebral total de 2,4% por década após os 60 anos de idade. A redução de volume ocorreu na substância cinzenta e na substância branca com a idade. A relação entre volume cerebral intracraniano e volume cerebral total diferiu entre homens e mulheres. CONCLUSÃO: Nós reproduzimos os achados de estudos prévios em populações americanas e europeias. A relação entre volume intracraniano e volume cerebral é maior em homens, o que pode representar fonte de viés na avaliação de atrofia radiológica convencional, já que essa avaliação é usualmente baseada em análise de espaços liquóricos intracranianos.