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Increasingly, dynamic magnetic resonance imaging (MRI) has potential as a noninvasive and accessible tool for diagnosing and monitoring gastrointestinal motility in healthy and diseased bowel. However, current MRI methods of measuring bowel motility have limitations: requiring bowel preparation or long acquisition times; providing mainly surrogate measures of motion; and estimating bowel-wall movement in just two dimensions. In this proof-of-concept study we apply a method that provides a quantitative measure of motion within the bowel, in both two and three dimensions, using existing, vendor-implemented MRI pulse sequences with minimal bowel preparation. This method uses a minimised cost function to fit linear vectors in the spatial and temporal domains. It is sensitised to the spatial scale of the bowel and aims to address issues relating to the low signal-to-noise in high-temporal resolution dynamic MRI scans, previously compensated for by performing thick-slice (10-mm) two-dimensional (2D) coronal scans. We applied both 2D and three-dimensional (3D) scanning protocols in two healthy volunteers. For 2D scanning, analysis yielded bi-modal velocity peaks, with a mean antegrade motion of 5.5 mm/s and an additional peak at similar to 9 mm/s corresponding to longitudinal peristalsis, as supported by intraoperative data from the literature. Furthermore, 3D scans indicated a mean forward motion of 4.7 mm/s, and degrees of antegrade and retrograde motion were also established. These measures show promise for the noninvasive assessment of bowel motility, and have the potential to be tuned to particular regions of interest and behaviours within the bowel.

Background: Since 2008 primary care physicians (GPs) in our region have been allowed open access to knee MRI scans. There are questions about whether this changes referral practice and if it is an effective use of resources. Purpose: To describe the change in demographics of patients referred for knee MRI following implementation of a new referral pathway. Study Type: Retrospective observational study. Population: All primary care referrals between 2008 and 2015 for knee MRI from a population of 900,000. Field Strength/Sequence: Not applicable. Assessment: Demographic profile and number of knee MRI referrals and subsequent arthroscopies. Statistical Tests: Comparisons between urban and rural populations used the t-test. Test for normality used Shapiro–Wilks. Comparison between abnormal MRI proportions used a chi-squared test. Results: There were 23,928 knee MRI referrals (10,695 from GPs) between 2000 and 2015. MRI knee referrals rose from 210 in 2008 to 2379 in 2015. The average age of the patient decreased from 46.8 (SD = 14.9) in 2008 to 41.3 (SD = 14.7) in 2015. Conversion to arthroscopy declined from 15.4% to 10.2%, but there was no significant change in abnormal scan proportion. Conversion rates showed no significant difference between rural (9.6%) and urban populations (10.5%). Referral rates were significantly higher in low socioeconomic status areas (47.3% vs. 34.6%). The median referral rate per 1000 patients was 13.8 (interquartile range = 8.4). Referral rates varied widely between practices. Data Conclusion: Despite a large rise in knee MRI referrals from primary care, there has been no substantial change in the age profile, suggesting that there has been no increase in inappropriate referral of elderly patients in whom MRI is unlikely to influence management. A modest decrease in the conversion rate to arthroscopy may be reasonably offset against a decrease in secondary care referrals. Socioeconomic status of the target population must be considered when planning primary care knee MRI services. Level of Evidence: 4. Technical Efficacy Stage: 6. J. Magn. Reson. Imaging 2019.

OBJECTIVE: Magnetic resonance imaging (MRI) texture analysis is a method of analyzing subchondral bone alterations in osteoarthritis (OA). The objective of this study was to evaluate the association between MR texture analysis and ground-truth subchondral bone histomorphometry at the tibial plateau. DESIGN: The local research ethics committee approved the study. All subjects provided written, informed consent. This was a cross-sectional study carried out at our institution between February and August 2014. Ten participants aged 57-84 with knee OA scheduled for total knee arthroplasty (TKA) underwent pre-operative MRI of the symptomatic knee at 3T using a high spatial-resolution coronal T1 weighted sequence. Tibial plateau explants obtained at the time of TKA underwent histological preparation to allow calculation of bone volume fraction (BV.TV), trabecular thickness (Tb.Th), trabecular separation (Tb.Sp) and trabecular number (Tb.N). Texture analysis was performed on the tibial subchondral bone of MRI images matched to the histological sections. Regression models were created to assess the association of texture analysis features with BV.TV, Tb.Th, Tb.Sp and Tb.N. RESULTS: MRI texture features were significantly associated with BV.TV (R2 = 0.76), Tb.Th (R2 = 0.47), Tb.Sp (R2 = 0.75) and Tb.N (R2 = 0.60, all P < 0.001). Simple gray-value histogram based texture features demonstrated the highest standardized regression coefficients for each model. CONCLUSION: MRI texture analysis features were significantly associated with ground-truth subchondral bone histomorphometry at the tibial plateau.

Purpose To measure the test–retest reliability of rapid (

To determine the feasibility of MRI texture analysis as a method of quantifying subchondral bone architecture in knee osteoarthritis (OA). Asymptomatic subjects aged 20–30 (group 1, n = 10), symptomatic patients aged 40–50 (group 2, n = 10) and patients scheduled for knee replacement aged 55–85 (group 3, n = 10) underwent high spatial resolution T1-weighted coronal 3T knee MRI. Regions of interest were created in the medial (MT) and lateral (LT) tibial subchondral bone from which 20 texture parameters were calculated. T2 mapping of the tibial cartilage was performed in groups 1 and 2. Mean parameter values were compared between groups using ANOVA. Linear discriminant analysis (LDA) was used to evaluate the ability of texture analysis to classify subjects correctly. Significant differences in 18/20 and 12/20 subchondral bone texture parameters were demonstrated between groups at the MT and LT respectively. There was no significant difference in mean MT or LT cartilage T2 values between group 1 and group 2. LDA demonstrated subject classification accuracy of 97 % (95 % CI 91–100 %). MRI texture analysis of tibial subchondral bone may allow detection of alteration in subchondral bone architecture in OA. This has potential applications in understanding OA pathogenesis and assessing response to treatment. • Improved techniques to monitor OA disease progression and treatment response are desirable • Subchondral bone (SB) may play significant role in the development of OA • MRI texture analysis is a method of quantifying changes in SB architecture • Pilot study showed that this technique is feasible and reliable • Significant differences in SB texture were demonstrated between individuals with/without OA

BACKGROUND: The aim of this study was to compare two different methods of quantitative assessment of tibial subchondral bone in osteoarthritis (OA): statistical texture analysis (sTA) and trabecular microarchitecture analysis (tMA). METHODS: Asymptomatic controls aged 20-30 (n = 10), patients aged 40-50 with chronic knee pain but without established OA (n = 10) and patients aged 55-85 with advanced OA scheduled for knee replacement (n = 10) underwent knee MR imaging at 3 Tesla with a three-dimensional gradient echo sequence to allow sTA and tMA. tMA and sTA features were calculated using region of interest creation in the medial (MT) and lateral (LT) tibial subchondral bone. Features were compared between groups using one-way analysis of variance. The two most discriminating tMA and sTA features were used to construct exploratory discriminant functions to assess the ability of the two methods to classify participants. RESULTS: No tMA features were significantly different between groups at either MT or LT. 17/20 and 11/20 sTA features were significantly different between groups at the MT/LT, respectively (P

PURPOSE: To define the range of quantitative pharmacokinetic parameters in normal-healing bone with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). DCE-MRI is an established technique for characterizing abnormal tissue microvasculature within solid tumors, but has also shown promise for assessing bone and bone marrow. MATERIALS AND METHODS: In this study ethical approval for eight patients was obtained. Inclusion criteria were an extra-articular distal radial fracture in patients aged 20-50 years which had united by 6 weeks in plaster cast. This was assessed by an experienced orthopedic surgeon. DCE-MRI was performed at 1.5T 6 weeks after initial injury. The transfer constant (K(trans) ), transfer rate (Kep ), and initial area under the curve (IAUC) values for the fracture site and adjacent marrow were obtained for each patient. RESULTS: The mean T1 , K(trans) , Kep , and IAUC at the fracture site were 1713 (standard deviation [SD] 645), 0.09 (SD 0.07), 0.17 (SD 0.17) and 4.9 (SD 4.4). The relative standard deviation (RSD) for the fracture site ranged from 0.38 to 0.97 and for the adjacent marrow ranged from 0.95-3.88. Within each patient the range of RSDs was 0.04-0.42 for T1 , 0.26-0.91 for K(trans) , 0.14-1.06 for Kep , and 0.35-0.96 for the IAUC. CONCLUSION: Pharmacokinetic measures of perfusion can be obtained from healing fractures using DCE-MRI with "excellent" intraclass correlation coefficients for inter- and intrarater reliability. The use of these perfusion parameters is limited by wide patient-to-patient variation and slice-to-slice variation within patients. J. Magn. Reson. Imaging 2015.

To measure the test-retest reproducibility of an automated system for quantifying whole body and compartmental muscle volumes using wide bore 3 T MRI.Thirty volunteers stratified by body mass index underwent whole body 3 T MRI, two-point Dixon sequences, on two separate occasions. Water-fat separation was performed, with automated segmentation of whole body, torso, upper and lower leg volumes, and manually segmented lower leg muscle volumes.Mean automated total body muscle volume was 19·32 L (SD9·1) and 19·28 L (SD9·12) for first and second acquisitions (Intraclass correlation coefficient (ICC) = 1·0, 95% level of agreement -0·32-0·2 L). ICC for all automated test-retest muscle volumes were almost perfect (0·99-1·0) with 95% levels of agreement 1.8-6.6% of mean volume. Automated muscle volume measurements correlate closely with manual quantification (right lower leg: manual 1·68 L (2SD0·6) compared to automated 1·64 L (2SD 0·6), left lower leg: manual 1·69 L (2SD 0·64) compared to automated 1·63 L (SD0·61), correlation coefficients for automated and manual segmentation were 0·94-0·96).Fully automated whole body and compartmental muscle volume quantification can be achieved rapidly on a 3 T wide bore system with very low margins of error, excellent test-retest reliability and excellent correlation to manual segmentation in the lower leg.Sarcopaenia is an important reversible complication of a number of diseases. Manual quantification of muscle volume is time-consuming and expensive. Muscles can be imaged using in and out of phase MRI. Automated atlas-based segmentation can identify muscle groups. Automated muscle volume segmentation is reproducible and can replace manual measurements.

To measure the test-retest reliability of rapid (15 min) whole body and visceral fat volume quantification in normal and obese subjects on a widebore 3T MR system and compare it with conventional manual segmentation.Thirty participants (body mass index [BMI] 20.1-48.6 kg/mThe mean TAT was 31.74 L with a coefficient of variation (CV) of 0.79% and a coefficient of repeatability (CR) of 0.49 L. The ASAT was 7.92 L with a CV of 2.98% and a CR of 0.46 L. There was no significant difference in the semiautomated and manually segmented VAT (P = 0.73) but there were differences in the reliability of the two techniques. The mean semiautomated VAT was 2.56 L, CV 1.8%, and CR 0.09 L compared to the mean manually segmented VAT of 3.12 L, where the CV was 6.3% and the CR was 0.39 L.Rapid semiautomated whole body and compartmental fat volume quantification can be derived from a widebore 3T system, for a range of body sizes including obese patients, with "almost perfect" test-retest reliability. J. Magn. Reson. Imaging 2016;44:1464-1473.

Aim To compare magnetic resonance imaging (MRI)-derived breast density measurements using automatic segmentation algorithms with radiologist estimations using the Breast Imaging Reporting and Data Systems (BI-RADS) density classification. Materials and methods Forty women undergoing mammography and dynamic breast MRI as part of their clinical management were recruited. Fat–water separated MRI images derived from a two-point Dixon technique, phase-sensitive reconstruction, and atlas-based segmentation were obtained before and after intravenous contrast medium administration. Breast density was assessed using software from Advanced MR Analytics (AMRA), Linkoping, Sweden, with results compared to the widely used four-quartile quantitative BI-RADS scale. Results The proportion of glandular tissue in the breast on MRI was derived from the AMRA sequence. The mean unenhanced breast density was 0.31±0.22 (mean±SD; left) and 0.29±0.21 (right). Mean breast density on post-contrast images was 0.32±0.19 (left) and 0.32±0.2 (right). There was “almost perfect” correlation between pre- and post-contrast breast density quantification: Spearman's correlation rho=0.98 (95% confidence intervals [CI]: 0.97–0.99; left) and rho=0.99 (95% CI: 0.98–0.99; right). The 95% limits of agreement were −0.11–0.08 (left) and −0.08–0.03 (right). Interobserver reliability for BI-RADS was “substantial”: weighted Kappa k=0.8 (95% CI: 0.74–0.87). The Spearman correlation coefficient between BI-RADS and MRI breast density was rho=0.73 (95% CI: 0.60–0.82; left) and rho=0.75 (95% CI: 0.63–0.83; right) which was also “substantial”. Conclusion The AMRA sequence provides a fully automated, reproducible, objective assessment of fibroglandular breast tissue proportion that correlates well with mammographic assessment of breast density with the added advantage of avoidance of ionising radiation.

The aim of this study was to compare two different methods of quantitative assessment of tibial subchondral bone in osteoarthritis (OA): statistical texture analysis (sTA) and trabecular microarchitecture analysis (tMA).Asymptomatic controls aged 20-30 (n = 10), patients aged 40-50 with chronic knee pain but without established OA (n = 10) and patients aged 55-85 with advanced OA scheduled for knee replacement (n = 10) underwent knee MR imaging at 3 Tesla with a three-dimensional gradient echo sequence to allow sTA and tMA. tMA and sTA features were calculated using region of interest creation in the medial (MT) and lateral (LT) tibial subchondral bone. Features were compared between groups using one-way analysis of variance. The two most discriminating tMA and sTA features were used to construct exploratory discriminant functions to assess the ability of the two methods to classify participants.No tMA features were significantly different between groups at either MT or LT. 17/20 and 11/20 sTA features were significantly different between groups at the MT/LT, respectively (P 0.001). Discriminant functions created using tMA features classified 12/30 participants correctly (40% accuracy; 95% confidence interval [CI], 22-58%) based on MT data and 9/30 correctly (30%,; 95% CI, 14-46) based on LT data. Discriminant functions using sTA features classified 16/30 participants correctly (53%; 95% CI, 35-71) based on MT data and 14/30 correctly (47%; 95% CI, 29-65) based on LT data.sTA features showed more significant differences between the three study groups and improved classification accuracy compared with tMA features.

To define the range of quantitative pharmacokinetic parameters in normal-healing bone with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). DCE-MRI is an established technique for characterizing abnormal tissue microvasculature within solid tumors, but has also shown promise for assessing bone and bone marrow.In this study ethical approval for eight patients was obtained. Inclusion criteria were an extra-articular distal radial fracture in patients aged 20-50 years which had united by 6 weeks in plaster cast. This was assessed by an experienced orthopedic surgeon. DCE-MRI was performed at 1.5T 6 weeks after initial injury. The transfer constant (K(trans) ), transfer rate (Kep ), and initial area under the curve (IAUC) values for the fracture site and adjacent marrow were obtained for each patient.The mean T1 , K(trans) , Kep , and IAUC at the fracture site were 1713 (standard deviation [SD] 645), 0.09 (SD 0.07), 0.17 (SD 0.17) and 4.9 (SD 4.4). The relative standard deviation (RSD) for the fracture site ranged from 0.38 to 0.97 and for the adjacent marrow ranged from 0.95-3.88. Within each patient the range of RSDs was 0.04-0.42 for T1 , 0.26-0.91 for K(trans) , 0.14-1.06 for Kep , and 0.35-0.96 for the IAUC.Pharmacokinetic measures of perfusion can be obtained from healing fractures using DCE-MRI with "excellent" intraclass correlation coefficients for inter- and intrarater reliability. The use of these perfusion parameters is limited by wide patient-to-patient variation and slice-to-slice variation within patients.

Telemedicine is the delivery of medicine at a distance using communications and information technologies. Teleradiology is the most established and mature field in Telemedicine, focusing on digital storage and transmission of medical images. In ultrasound, teleradiology application entails the transmission of still images and video sequences across an organizational Local Area Network (LAN) to a Picture Archiving and Communication System (PACS). This subsequently is distributed to remote locations via a private inter-organizational Wide Area Network (WAN) or a public network, such as the Internet.

Background Small bowel peristalsis is a complex of many individual motion elements. Although each element of peristalsis can be measured there is no current global measure of peristalsis. Purpose To examine the feasibility of automated computerized assessment of global small bowel motility using simple computational methods. Material and Methods Coronal dynamic MR images were obtained from five healthy volunteers who had fasted for 9 h and drunk 1.5 L of water. Images were taken using single breath-hold and ECG triggering. Acquisitions were repeated at 10 and 20 min after an intramuscular injection of hyoscine butylbromide. Parametric maps were generated representing the mean change in signal amplitude (MSA) per voxel for each dynamic acquisition. Two observers independently assessed thresholding for optimal segmentation of small bowel from other sources of signal. Total voxel activity (TVA) for each study was calculated as a sum of MSA per slice and whole examination and TVA profiles were generated. Results Independent observations suggest that the automated segmentation method described usefully segments small bowel activity from other signal. Small bowel movement represented as TVA varied three-fold in the five volunteers and was inhibited by anti-muscarinic injection. Conclusion It is possible to develop a new measure, based on automated segmentation of mean signal amplitude changes, of small bowel peristalsis using dynamic MR.

Background The mechanics of small bowel motility are extremely complex. Routine clinical access to small bowel has been restricted to radiological enteric contrast studies which have not contributed significantly to the understanding of small bowel physiology. Small bowel mechanics are understood within a framework of individual visible or measurable elements such as peristaltic wave formation, intra-luminal pressure gradients and transit times. There are no global measures of small bowel function that can be readily obtained in vivo in humans. Magnetic resonance imaging (MRI) is playing an increasingly important role in radiological diagnosis of small bowel disease and dynamic MRI offers the possibility of capturing small bowel movement in three-dimensional cinematic datasets. The metrics that are used to describe small bowel mechanics, typically anatomical measures in isolated segments, are not suited to analysing these large dynamic datasets. The proposal in this paper is to leave behind all previously described anatomical metrics and to describe anew the mechanics of small bowel movement in mathematical terms derived from changes in pixel intensity within dynamic MRI datasets so that global small bowel activity might be summarised in a single novel metric. Hypothesis The hypothesis of this paper is that global small bowel activity can be quantified by a new dynamic MR based metric. Evaluation A proposed strategy for evaluation includes a progression through feasibility, optimisation, reliability and validation studies. Thereafter normal volunteers would be required in order to define normal ranges for the new metric. These ranges would describe small bowel activity during fasting or after ingestion of fluids and standard meals. Mathematical modelling of the data could follow a two stage approach. The first stage could be to study segmentation or extraction techniques by which the small bowel activity could be isolated from MRI signal generated by the rest of the abdomen. The second stage would be to apply a number of data mining techniques that would identify significant features within the datasets. Conclusion If this approach proves to be a useful model for studying small bowel physiology in humans, it would afford significant new avenues of research and treatment particularly in areas such as enteric drug delivery, the ageing gut, and nutrition.

The aim of this study was to test the feasibility of a software application that would allow the anonymization and cataloguing of whole DICOM datasets in order to build searchable radiology museums within PACS. The application was developed on a dedicated networked PC, using C# and HL7 coding. Whole DICOM datasets were pushed from PACS to a networked PC on which the application, Museum Builder, was developed. Museum Builder works by replacing the patient specific data (the forename, surname and hospital number) within each header of each DICOM file with terms from anatomical and surgical sieve menus. The date of birth is anonymized to 1 January of the same year. Whole DICOM datasets comprising hundreds of images can be anonymized and catalogued in a single episode. Museum Builder primes PACS with an HL7 script to receive a "new" patient. DICOM datasets are then pushed back to PACS where they are added to the database as "new" cases. The museum cases can then be searched for, on PACS, by any combination of terms that correspond to appropriate anatomical units, surgical sieve headings or radiological specialty. New radiology reports containing clinical histories, radiological descriptions, differential diagnoses and discussion can be added through the report window. Our institution has developed and used this tool to generate a PACS based radiology museum containing not only full DICOM datasets, but also relevant histological and clinical photographs. In conclusion, this technique offers a mechanism for generating anonymized catalogued radiology museums in PACS. Museum Builder represents a working prototype that demonstrates some of the archiving functions that are expected by teaching institutions from PACS.