A robust and semi-automatic quantitative measurement of patellofemoral instability based on four dimensional computed tomography.

Patellofemoral instability is a motion related disease, featured as the patella dislocating from the trochlear groove. Four dimensional computed tomography (4DCT) enables full assessment of the patellofemoral movement. Nevertheless, the quantitative measurements of patellofemoral instability are still under research and currently of limited practical use. The aim of this study is to develop a robust and semi-automatic workflow to quantitatively describe the patellofemoral movement in a patient group of eight suffering from patellofemoral instability. The initial results show agreement with manual observations of the tibial tubercle - trochlear groove (TT-TG) distance in routine practice, and the possibility to evaluate both TT-TG distance and patellar centre - trochlear groove (PC-TG) distance dynamically during active flexion-extension-flexion movement of the knee.

Assessment of fasted and fed gastrointestinal contraction frequencies in healthy subjects using continuously tagged MRI.

BACKGROUND: Continuously tagged MRI during free breathing can assess bowel motility at frequencies as low as the slow wave, motility pattern range. This study aimed to evaluate noninvasive gastrointestinal-tagged MRI for small bowel motility assessment and to observe the physiological response to a 300-kcal meal challenge in healthy, overnight-fasted volunteers. METHODS: After overnight fasting, 16 healthy subjects (7 women, mean age 25.5, range 19-37 years) underwent a free breathing, tagged MRI scan to capture small bowel motility. Each subject underwent a (a) baseline motility scan, (b) food challenge, (c) postchallenge scan, and (d) second postchallenge scan (after 20 minutes). Motility was quantified using a frequency analysis technique for measuring the spectral power of the strain, referred to as motility score. Motility score was assessed in 20 frequency intervals between 1 and 20 contractions per minute (cpm), and the data were analyzed with linear mixed-effect models. KEY RESULT: The stimulation protocol demonstrated an immediate, food-induced, motility response in the low-frequency range (2-10 cpm), which is consistent with the stomach and small bowel frequency range (3-12 cpm). CONCLUSIONS AND INFERENCES: This study shows that this MRI tagging technique is able to quantify the fasted-to-fed response to a 300-kcal meal challenge within the specific small bowel motility frequency range in healthy subjects. The food provocation MRI protocol provides a tool to explore the gut's response to a stimulus in specific motility frequency ranges in patients with gastrointestinal dysmotility and functional disorders.

Automated segmentation of trabecular and cortical bone from proton density weighted MRI of the knee.

Patient-specific implant design and pre- and intra-operative planning is becoming increasingly important in the orthopaedic field. For clinical feasibility of these techniques, fast and accurate segmentation of bone structures from MRI is essential. However, manual segmentation is time intensive and subject to inter- and intra-observer variation. The challenge in developing automatic segmentation algorithms for MRI data mainly exists in the inhomogeneity problem and the low contrast among cortical bone and adjacent tissues. In this paper, we proposed a method for automatic segmentation of knee bone structures for MRI data with a 3D local intensity clustering-based level set and a novel approach to determine the cortical boundary utilizing the normal vector of the trabecular surface. Application to clinical imaging data shows that our method is robust to MRI inhomogeneity. In comparing our method to manual segmentation in 18 femurs and tibiae, we found a dice similarity coefficient (DSC) of 0.9611 ± 0.0052 for the femurs and 0.9591 ± 0.0173 for tibiae. The average surface distance error was 0.4649 ± 0.1430 mm for the femurs and 0.4712 ± 0.2113 mm for the tibiae. The results of the automatic technique thus strongly corresponded to the manual segmentation using less than 3% of the time and with virtually no workload. Graphical abstract ᅟ.

Noninvasive automated motion assessment of intestinal motility by continuously tagged MR imaging.

PURPOSE: To evaluate continuously tagged 3 Tesla MRI for monitoring glucagon-induced bowel motility changes in healthy volunteers. MATERIALS AND METHODS: After standardized oral bowel preparation, 10 healthy volunteers underwent a free-breathing, continuously tagged three-dimensional (3D) dynamic fast-field-echo (FFE), at a 3.36 Hz sampling frequency. One milligram of glucagon was administered intravenously during data acquisition. Each dataset was divided into four temporal sets of 2 min (period 1 to 4). Taglines were tracked automatically using a scale spaced based algorithm. Assessment of global spectral resolution was performed for three frequency intervals: 0.008-0.300 Hz (motility), 0.300-0.400 Hz (breathing motion), and 0.400-0.533 Hz (higher order motion). Additional analyses were performed at fine spectral resolution in frequency bands of 0.033 Hz. Glucagon-induced motility changes were investigated by means of a motility index (spectral power normalized to the maximal spectral power per-volunteer), resulting in a range of 0 to 1 (no motion to maximal motion). Statistical comparison was done for period 1 and 4 (Wilcoxon-signed rank test). RESULTS: After glucagon administration, a significant decrease in the motility index was found for the low- (0.008-0.300 Hz) (P < 0.0001) and high-frequency interval (0.400-0.533 Hz) (P < 0.0001). Around breathing motion frequencies, no decrease in motility index was detected. CONCLUSION: Free-breathing, continuously tagged MR imaging is a noninvasive method for automated bowel motility assessment and allows for detection of drug-induced changes.

A novel MRI compatible soft tissue indentor and fibre Bragg grating force sensor.

MRI is an ideal method for non-invasive soft tissue mechanical properties investigation. This requires mechanical excitation of the body's tissues and measurement of the corresponding boundary conditions such as soft tissue deformation inside the MRI environment. However, this is technically difficult since load application and measurement of boundary conditions requires MRI compatible actuators and sensors. This paper describes a novel MRI compatible computer controlled soft tissue indentor and optical Fibre Bragg Grating (FBG) force sensor. The high acquisition rate (100Hz) force sensor was calibrated for forces up to 15N and demonstrated a maximum error of 0.043N. Performance and MRI compatibility of the devices was verified using indentation tests on a silicone gel phantom and the upper arm of a volunteer. The computer controlled indentor provided a highly repeatable tissue deformation. Since the indentor and force sensor are composed of non-ferromagnetic materials, they are MRI compatible and no artefacts or temporal SNR reductions were observed. In a phantom study the mean and standard deviation of the temporal SNR levels without the indentor present were 500.18 and 207.08, respectively. With the indentor present the mean and standard deviation were 501.95 and 200.45, respectively. This computer controlled MRI compatible soft tissue indentation system with an integrated force sensor has a broad range of applications and will be used in the future for the non-invasive analysis of the mechanical properties of skeletal muscle tissue.

A scale space based algorithm for automated segmentation of single shot tagged MRI of shearing deformation.

OBJECT: This study proposes a scale space based algorithm for automated segmentation of single-shot tagged images of modest SNR. Furthermore the algorithm was designed for analysis of discontinuous or shearing types of motion, i.e. segmentation of broken tag patterns. MATERIALS AND METHODS: The proposed algorithm utilises non-linear scale space for automatic segmentation of single-shot tagged images. The algorithm's ability to automatically segment tagged shearing motion was evaluated in a numerical simulation and in vivo. A typical shearing deformation was simulated in a Shepp-Logan phantom allowing for quantitative evaluation of the algorithm's success rate as a function of both SNR and the amount of deformation. For a qualitative in vivo evaluation tagged images showing deformations in the calf muscles and eye movement in a healthy volunteer were acquired. RESULTS: Both the numerical simulation and the in vivo tagged data demonstrated the algorithm's ability for automated segmentation of single-shot tagged MR provided that SNR of the images is above 10 and the amount of deformation does not exceed the tag spacing. The latter constraint can be met by adjusting the tag delay or the tag spacing. CONCLUSION: The scale space based algorithm for automatic segmentation of single-shot tagged MR enables the application of tagged MR to complex (shearing) deformation and the processing of datasets with relatively low SNR.

Validation of continuously tagged MRI for the measurement of dynamic 3D skeletal muscle tissue deformation.

PURPOSE: Typically spatial modulation of the magnetization (SPAMM) tagged magnetic resonance imaging (MRI) requires many repeated motion cycles limiting the applicability to highly repeatable tissue motions only. This paper describes the validation of a novel SPAMM tagged MRI and post-processing framework for the measurement of complex and dynamic 3D soft tissue deformation following just three motion cycles. Techniques are applied to indentation induced deformation measurement of the upper arm and a silicone gel phantom. METHODS: A SPAMM tagged MRI methodology is presented allowing continuous (3.3-3.6 Hz) sampling of 3D dynamic soft tissue deformation using non segmented 3D acquisitions. The 3D deformation is reconstructed by the combination of three mutually orthogonal tagging directions, thus requiring only three repeated motion cycles. In addition a fully automatic post-processing framework is presented employing Gabor scale-space and filter-bank analysis for tag extrema segmentation and triangulated surface fitting aided by Gabor filter bank derived surface normals. Deformation is derived following tracking of tag surface triplet triangle intersections. The dynamic deformation measurements were validated using indentation tests (∼20 mm deep at 12 mm/s) on a silicone gel soft tissue phantom containing contrasting markers which provide a reference measure of deformation. In addition, the techniques were evaluated in vivo for dynamic skeletal muscle tissue deformation measurement during indentation of the biceps region of the upper arm in a volunteer. RESULTS: For the phantom and volunteer tag point location precision were 44 and 92 µm, respectively resulting in individual displacements precisions of 61 and 91 µm, respectively. For both the phantom and volunteer data cumulative displacement measurement accuracy could be evaluated and the difference between initial and final locations showed a mean and standard deviation of 0.44 and 0.59 mm for the phantom and 0.40 and 0.73 mm for the human data. Finally accuracy of (cumulative) displacement was evaluated using marker tracking in the silicone gel phantom. Differences between true and predicted marker locations showed a mean of 0.35 mm and a standard deviation of 0.63 mm. CONCLUSIONS: A novel SPAMM tagged MRI and fully automatic post-processing framework for the measurement of complex 3D dynamic soft tissue deformation following just three repeated motion cycles was presented. The techniques demonstrate dynamic measurement of complex 3D soft tissue deformation at subvoxel accuracy and precision and were validated for 3.3-3.6 Hz sampling of deformation speeds up to 12 mm/s.

Use of continuously MR tagged imaging for automated motion assessment in the abdomen: a feasibility study.

PURPOSE: To investigate the feasibility of measuring motion in the abdomen using a continuously tagged magnetic resonance imaging sequence. MATERIALS AND METHODS: To assess (nonperiodic) motion in the abdomen, a nontriggered, continuously tagged transient field echo (TFE) sequence was implemented that acquires one complete 3D dataset per prepulse after a fixed delay. In postprocessing, a frequency analysis approach was developed for compact reviewing of the data and noise suppression. For proof of principle, a simulation was made and one free-breathing dynamic in vivo scan was acquired in a healthy volunteer. During the dynamic scan the volunteer received glucagon intravenously. RESULTS: The simulation showed that this frequency analysis enables the extraction of motion at low signal-to-noise ratio levels. Motion information was successfully gathered from the in vivo scan. The decline in bowel motion caused by the administration of glucagon could be quantitatively measured using the continuously tagged sequence. CONCLUSION: Continuously tagged imaging in the abdomen for the purpose of automated gathering of motion information is feasible and could aid the study of bowel motion.

Validation of SPAMM tagged MRI based measurement of 3D soft tissue deformation.

PURPOSE: This study presents and validates a novel (non-ECG-triggered) MRI sequence based on spatial modulation of the magnetization (SPAMM) to noninvasively measure 3D (quasistatic) soft tissue deformations using only six acquisitions (three static and three indentations). In the current SPAMM tagged MRI approaches, data are typically constructed from many repeated motion cycles. This has so far restricted its application to the measurement of highly repeatable and periodic movements (e.g., cardiac deformation). In biomechanical applications where soft tissue deformation is artificially induced, often by indentation, significant repeatability constraints exist, and for clinical applications, discomfort and health issues generally preclude a large number of repetitions. METHODS: A novel (non-ECG-triggered) SPAMM tagged MRI sequence is presented, whereby a single 1-1 (first order) SPAMM set is acquired following a 3D transient field echo acquisition. Full 3D deformation measurement is achieved through the combination of only six acquisitions (three static and three motion cycles). The 3D deformation measurements were validated using quasistatic indentation tests and marker tracking in a silicone gel soft tissue phantom. In addition, the technique's ability to measure 3D soft tissue deformation in vivo was evaluated using indentation of the biceps region of the upper arm in a volunteer. RESULTS: Following comparison to marker tracking in the silicone gel phantom, the SPAMM tagged MRI based displacement measurement demonstrated subvoxel accuracy with a mean displacement difference of 72 microm and a standard deviation of 289 microm. In addition, precision of displacement magnitude was evaluated for both the phantom and the volunteer data. The standard deviations of the displacement magnitude with respect to the average displacement magnitude were 75 and 169 microm for the phantom and volunteer data, respectively. CONCLUSIONS: The subvoxel accuracy and precision demonstrated in the phantom in combination with the precision comparison between the phantom and the volunteer data provide confidence in the methods presented for measurement of soft tissue deformation in vivo. To the author's knowledge, since only six acquisitions are required, the presented methodology is the fastest SPAMM tagged MRI method currently available for the noninvasive measurement of quasistatic 3D soft tissue deformation.