Anterior horn atrophy in the cervical spinal cord: A new biomarker in progressive multiple sclerosis.

BACKGROUND: Spinal cord (SC) gray and white matter pathology plays a central role in multiple sclerosis (MS). OBJECTIVE: We aimed to investigate the extent, pattern, and clinical relevance of SC gray and white matter atrophy in vivo. METHODS: 39 relapsing-remitting patients (RRMS), 40 progressive MS patients (PMS), and 24 healthy controls (HC) were imaged at 3T using the averaged magnetization inversion recovery acquisitions sequence. Total and lesional cervical gray and white matter, and posterior (SCPH) and anterior horn (SCAH) areas were automatically quantified. Clinical assessment included the expanded disability status scale, timed 25-foot walk test, nine-hole peg test, and the 12-item MS walking scale. RESULTS: PMS patients had significantly reduced cervical SCAH - but not SCPH - areas compared with HC and RRMS (both p < 0.001). In RRMS and PMS, the cervical SCAH areas increased significantly less in the region of cervical SC enlargement compared with HC (all p < 0.001). This reduction was more pronounced in PMS compared with RRMS (both p < 0.001). In PMS, a lower cervical SCAH area was the most important magnetic resonance imaging (MRI)-variable for higher disability scores. CONCLUSION: MS patients show clinically relevant cervical SCAH atrophy, which is more pronounced in PMS and at the level of cervical SC enlargement.

Classification of multiple sclerosis based on patterns of CNS regional atrophy covariance.

There is evidence that multiple sclerosis (MS) pathology leads to distinct patterns of volume loss over time (VLOT) in different central nervous system (CNS) structures. We aimed to use such patterns to identify patient subgroups. MS patients of all classical disease phenotypes underwent annual clinical, blood, and MRI examinations over 6 years. Spinal, striatal, pallidal, thalamic, cortical, white matter, and T2-weighted lesion volumes as well as serum neurofilament light chain (sNfL) were quantified. CNS VLOT patterns were identified using principal component analysis and patients were classified using hierarchical cluster analysis. 225 MS patients were classified into four distinct Groups A, B, C, and D including 14, 59, 141, and 11 patients, respectively). These groups did not differ in baseline demographics, disease duration, disease phenotype distribution, and lesion-load expansion. Interestingly, Group A showed pronounced spinothalamic VLOT, Group B marked pallidal VLOT, Group C small between-structure VLOT differences, and Group D myelocortical volume increase and pronounced white matter VLOT. Neurologic deficits were more severe and progressed faster in Group A that also had higher mean sNfL levels than all other groups. Group B experienced more frequent relapses than Group C. In conclusion, there are distinct patterns of VLOT across the CNS in MS patients, which do not overlap with clinical MS subtypes and are independent of disease duration and lesion-load but are partially associated to sNfL levels, relapse rates, and clinical worsening. Our findings support the need for a more biologic classification of MS subtypes including volumetric and body-fluid markers.

Accurate, rapid and reliable, fully automated MRI brainstem segmentation for application in multiple sclerosis and neurodegenerative diseases.

Neurodegenerative disorders, such as Alzheimer's disease (AD) and progressive forms of multiple sclerosis (MS), can affect the brainstem and are associated with atrophy that can be visualized by MRI. Anatomically accurate, large-scale assessments of brainstem atrophy are challenging due to lack of automated, accurate segmentation methods. We present a novel method for brainstem volumetry using a fully-automated segmentation approach based on multi-dimensional gated recurrent units (MD-GRU), a deep learning based semantic segmentation approach employing a convolutional adaptation of gated recurrent units. The neural network was trained on 67 3D-high resolution T1-weighted MRI scans from MS patients and healthy controls (HC) and refined using segmentations of 20 independent MS patients' scans. Reproducibility was assessed in MR test-retest experiments in 33 HC. Accuracy and robustness were examined by Dice scores comparing MD-GRU to FreeSurfer and manual brainstem segmentations in independent MS and AD datasets. The mean %-change/SD between test-retest brainstem volumes were 0.45%/0.005 (MD-GRU), 0.95%/0.009 (FreeSurfer), 0.86%/0.007 (manually edited segmentations). Comparing MD-GRU to manually edited segmentations the mean Dice scores/SD were: 0.97/0.005 (brainstem), 0.95/0.013 (mesencephalon), 0.98/0.006 (pons), 0.95/0.015 (medulla oblongata). Compared to the manual gold standard, MD-GRU brainstem segmentations were more accurate than FreeSurfer segmentations (p < .001). In the multi-centric acquired AD data, the mean Dice score/SD for the MD-GRU-manual segmentation comparison was 0.97/0.006. The fully automated brainstem segmentation method MD-GRU provides accurate, highly reproducible, and robust segmentations in HC and patients with MS and AD in 200 s/scan on an Nvidia GeForce GTX 1080 GPU and shows potential for application in large and longitudinal datasets.

Preferential spinal cord volume loss in primary progressive multiple sclerosis.

BACKGROUND: Little is known on longer term changes of spinal cord volume (SCV) in primary progressive multiple sclerosis (PPMS). OBJECTIVE: Longitudinal evaluation of SCV loss in PPMS and its correlation to clinical outcomes, compared to relapse-onset multiple sclerosis (MS) subtypes. METHODS: A total of 60 MS age-, sex- and disease duration-matched patients (12 PPMS, each 24 relapsing-remitting (RRMS) and secondary progressive MS (SPMS)) were analysed annually over 6 years of follow-up. The upper cervical SCV was measured on 3D T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) images using a semi-automatic software (CORDIAL), along with the total brain volume (TBV), brain T2 lesion volume (T2LV) and Expanded Disability Status Scale (EDSS). RESULTS: PPMS showed faster SCV loss over time than RRMS ( p < 0.01) and by trend ( p = 0.066) compared with SPMS. In contrast to relapse-onset MS, in PPMS SCV loss progressed independent of TBV and T2LV changes. Moreover, in PPMS, SCV was the only magnetic resonance imaging (MRI) measurement associated with EDSS increase over time ( p < 0.01), as opposed to RRMS and SPMS. CONCLUSION: SCV loss is a strong predictor of clinical outcomes in PPMS and has shown to be faster and independent of brain MRI metrics compared to relapse-onset MS.

Reliable and fast volumetry of the lumbar spinal cord using cord image analyser (Cordial).

OBJECTIVE: To validate the precision and accuracy of the semi-automated cord image analyser (Cordial) for lumbar spinal cord (SC) volumetry in 3D T1w MRI data of healthy controls (HC). MATERIALS AND METHODS: 40 3D T1w images of 10 HC (w/m: 6/4; age range: 18-41 years) were acquired at one 3T-scanner in two MRI sessions (time interval 14.9±6.1 days). Each subject was scanned twice per session, allowing determination of test-retest reliability both in back-to-back (intra-session) and scan-rescan images (inter-session). Cordial was applied for lumbar cord segmentation twice per image by two raters, allowing for assessment of intra- and inter-rater reliability, and compared to a manual gold standard. RESULTS: While manually segmented volumes were larger (mean: 2028±245 mm3 vs. Cordial: 1636±300 mm3, p<0.001), accuracy assessments between manually and semi-automatically segmented images showed a mean Dice-coefficient of 0.88±0.05. Calculation of within-subject coefficients of variation (COV) demonstrated high intra-session (1.22-1.86%), inter-session (1.26-1.84%), as well as intra-rater (1.73-1.83%) reproducibility. No significant difference was shown between intra- and inter-session reproducibility or between intra-rater reliabilities. Although inter-rater reproducibility (COV: 2.87%) was slightly lower compared to all other reproducibility measures, between rater consistency was very strong (intraclass correlation coefficient: 0.974). CONCLUSION: While under-estimating the lumbar SCV, Cordial still provides excellent inter- and intra-session reproducibility showing high potential for application in longitudinal trials. KEY POINTS: • Lumbar spinal cord segmentation using the semi-automated cord image analyser (Cordial) is feasible. • Lumbar spinal cord is 40-mm cord segment 60 mm above conus medullaris. • Cordial provides excellent inter- and intra-session reproducibility in lumbar spinal cord region. • Cordial shows high potential for application in longitudinal trials.

Longitudinal assessment of cervical spinal cord compartments in multiple sclerosis.

BACKGROUND: Although cervical spinal cord (cSC) area is an established biomarker in MS, there is currently a lack of longitudinal assessments of cSC gray and white matter areas. OBJECTIVE: We conducted an explorative analysis of longitudinal changes of cSC gray and white matter areas in MS patients. METHODS: 65 MS patients (33 relapsing-remitting; 20 secondary progressive and 12 primary progressive) and 20 healthy controls (HC) received clinical and upper cSC MRI assessments over 1.10±0.28 years. cSC compartments were quantified on MRI using the novel averaged magnetization inversion recovery acquisitions sequence (in-plane resolution=0.67 × 0.67mm2), and in-house developed post-processing methods. Patients were stratified regarding clinical progression. RESULTS: Patients with clinical progression showed faster reduction of cSC areas over time at the level of cSC enlargement (approximate vertebral level C4-C5) compared to stable patients (p<0.05). In addition, when compared to the rostral-cSC (approximate vertebral level C2-C3), a preferential reduction of cSC and white matter areas over time at the level of cSC enlargement (p<0.05 and p<0.01, respectively) was demonstrated only in patients with clinical progression, but not in stable MS patients and HC. Compared to HC, MS patients showed comparable changes over time in all cSC compartments. CONCLUSIONS: MS patients with clinical disease progression demonstrate subtle signs of a more pronounced tissue loss at the level of cSC enlargement. Future studies should consider larger sample sizes and more extended observation periods.

Improving Accuracy of Brainstem MRI Volumetry: Effects of Age and Sex, and Normalization Strategies.

Background: Brainstem-mediated functions are impaired in neurodegenerative diseases and aging. Atrophy can be visualized by MRI. This study investigates extrinsic sources of brainstem volume variability, intrinsic sources of anatomical variability, and the influence of age and sex on the brainstem volumes in healthy subjects. We aimed to develop efficient normalization strategies to reduce the effects of intrinsic anatomic variability on brainstem volumetry. Methods: Brainstem segmentation was performed from MPRAGE data using our deep-learning-based brainstem segmentation algorithm MD-GRU. The extrinsic variability of brainstem volume assessments across scanners and protocols was investigated in two groups comprising 11 (median age 33.3 years, 7 women) and 22 healthy subjects (median age 27.6 years, 50% women) scanned twice and compared using Dice scores. Intrinsic anatomical inter-individual variability and age and sex effects on brainstem volumes were assessed in segmentations of 110 healthy subjects (median age 30.9 years, range 18-72 years, 53.6% women) acquired on 1.5T (45%) and 3T (55%) scanners. The association between brainstem volumes and predefined anatomical covariates was studied using Pearson correlations. Anatomical variables with associations of |r| > 0.30 as well as the variables age and sex were used to construct normalization models using backward selection. The effect of the resulting normalization models was assessed by % relative standard deviation reduction and by comparing the inter-individual variability of the normalized brainstem volumes to the non-normalized values using paired t- tests with Bonferroni correction. Results: The extrinsic variability of brainstem volumetry across different field strengths and imaging protocols was low (Dice scores > 0.94). Mean inter-individual variability/SD of total brainstem volumes was 9.8%/7.36. A normalization based on either total intracranial volume (TICV), TICV and age, or v-scale significantly reduced the inter-individual variability of total brainstem volumes compared to non-normalized volumes and similarly reduced the relative standard deviation by about 35%. Conclusion: The extrinsic variability of the novel brainstem segmentation method MD-GRU across different scanners and imaging protocols is very low. Anatomic inter-individual variability of brainstem volumes is substantial. This study presents efficient normalization models for variability reduction in brainstem volumetry in healthy subjects.

Sentinel lymph node fingerprinting.

BACKGROUND: When locating the sentinel lymph node (SLN), surgeons use state-of-the-art imaging devices, such as a 1D gamma probe or less widely spread a 2D gamma camera. These devices project the 3D subspace onto a 1D respectively 2D space, hence loosing accuracy and the depth of the SLN which is very important, especially in the head and neck area with many critical structures in close vicinity. Recent methods which use a multi-pinhole collimator and a single gamma detector image try to gain a depth estimation of the SLN. The low intensity of the sources together with the computational cost of the optimization process make the reconstruction in real-time, however, very challenging. RESULTS: In this paper, we use an optimal design approach to improve the classical pinhole design, resulting in a non-symmetric distribution of the pinholes of the collimator. This new design shows a great improvement of the accuracy when reconstructing the position and depth of the radioactive tracer. Then, we introduce our Sentinel lymph node fingerprinting (SLNF) algorithm, inspired by MR-fingerprinting, for fast and accurate reconstruction of the tracer distribution in 3D space using a single gamma detector image. As a further advantage, the method requires no pre-processing, i.e. filtering of the detector image. The method is very stable in its performance even for low exposure times. In our ex vivo experiments, we successfully located multiple Technetium 99m (Tc-99m) sources with an exposure time of only one second and still, with a very small L 2-error. CONCLUSION: These promising results under short exposure time are very encouraging for SLN biopsy. Although, this device has not been tested on patients yet, we believe: that this approach will give the surgeon accurate 3D positions of the SLN and hence, can potentially reduce the trauma for the patient.

Augmenting camera images with gamma detector data : A novel approach to support sentinel lymph node biopsy.

BACKGROUND: Squamous cell carcinoma in the head and neck region is one of the most widespread cancers with high morbidity. Classic treatment comprises the complete removal of the lymphatics together with the cancerous tissue. Recent studies have shown that such interventions are only required in 30% of the patients. Sentinel lymph node biopsy is an alternative method to stage the malignancy in a less invasive manner and to avoid overtreatment. In this paper, we present a novel approach that enables a future augmented reality device which improves the biopsy procedure by visual means. METHODS: We propose a co-calibration scheme for axis-aligned miniature cameras with pinholes of a gamma ray collimating and sensing device and show results gained by experiments, based on a calibration target visible for both modalities. RESULTS: Visual inspection and quantitative evaluation of the augmentation of optical camera images with gamma information are congruent with known gamma source landmarks. CONCLUSIONS: Combining a multi-pinhole collimator with axis-aligned miniature cameras to augment optical images using gamma detector data is promising. As such, our approach might be applicable for breast cancer and melanoma staging as well, which are also based on sentinel lymph node biopsy.

Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge.

Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are often still obtained from manual segmentations on brain MR images, which is a laborious procedure. The automatic WMH segmentation methods exist, but a standardized comparison of the performance of such methods is lacking. We organized a scientific challenge, in which developers could evaluate their methods on a standardized multi-center/-scanner image dataset, giving an objective comparison: the WMH Segmentation Challenge. Sixty T1 + FLAIR images from three MR scanners were released with the manual WMH segmentations for training. A test set of 110 images from five MR scanners was used for evaluation. The segmentation methods had to be containerized and submitted to the challenge organizers. Five evaluation metrics were used to rank the methods: 1) Dice similarity coefficient; 2) modified Hausdorff distance (95th percentile); 3) absolute log-transformed volume difference; 4) sensitivity for detecting individual lesions; and 5) F1-score for individual lesions. In addition, the methods were ranked on their inter-scanner robustness; 20 participants submitted their methods for evaluation. This paper provides a detailed analysis of the results. In brief, there is a cluster of four methods that rank significantly better than the other methods, with one clear winner. The inter-scanner robustness ranking shows that not all the methods generalize to unseen scanners. The challenge remains open for future submissions and provides a public platform for method evaluation.

Spinal cord volume loss: A marker of disease progression in multiple sclerosis.

OBJECTIVE: Cross-sectional studies have shown that spinal cord volume (SCV) loss is related to disease severity in multiple sclerosis (MS). However, long-term data are lacking. Our aim was to evaluate SCV loss as a biomarker of disease progression in comparison to other MRI measurements in a large cohort of patients with relapse-onset MS with 6-year follow-up. METHODS: The upper cervical SCV, the total brain volume, and the brain T2 lesion volume were measured annually in 231 patients with MS (180 relapsing-remitting [RRMS] and 51 secondary progressive [SPMS]) over 6 years on 3-dimensional, T1-weighted, magnetization-prepared rapid-acquisition gradient echo images. Expanded Disability Status Scale (EDSS) score and relapses were recorded at every follow-up. RESULTS: Patients with SPMS had lower baseline SCV (p < 0.01) but no accelerated SCV loss compared to those with RRMS. Clinical relapses were found to predict SCV loss over time (p < 0.05) in RRMS. Furthermore, SCV loss, but not total brain volume and T2 lesion volume, was a strong predictor of EDSS score worsening over time (p < 0.05). The mean annual rate of SCV loss was the strongest MRI predictor for the mean annual EDSS score change of both RRMS and SPMS separately, while correlating stronger in SPMS. Every 1% increase of the annual SCV loss rate was associated with an extra 28% risk increase of disease progression in the following year in both groups. CONCLUSION: SCV loss over time relates to the number of clinical relapses in RRMS, but overall does not differ between RRMS and SPMS. SCV proved to be a strong predictor of physical disability and disease progression, indicating that SCV may be a suitable marker for monitoring disease activity and severity.

Simultaneous intrinsic and extrinsic calibration of a laser deflecting tilting mirror in the projective voltage space.

PURPOSE  : During the past five decades, laser technology emerged and is nowadays part of a great number of scientific and industrial applications. In the medical field, the integration of laser technology is on the rise and has already been widely adopted in contemporary medical applications. However, it is new to use a laser to cut bone and perform general osteotomy surgical tasks with it. In this paper, we describe a method to calibrate a laser deflecting tilting mirror and integrate it into a sophisticated laser osteotome, involving next generation robots and optical tracking. METHODS  : A mathematical model was derived, which describes a controllable deflection mirror by the general projective transformation. This makes the application of well-known camera calibration methods possible. In particular, the direct linear transformation algorithm is applied to calibrate and integrate a laser deflecting tilting mirror into the affine transformation chain of a surgical system. RESULTS  : Experiments were performed on synthetic generated calibration input, and the calibration was tested with real data. The determined target registration errors in a working distance of 150 mm for both simulated input and real data agree at the declared noise level of the applied optical 3D tracking system: The evaluation of the synthetic input showed an error of 0.4 mm, and the error with the real data was 0.3 mm.

With Gaze Tracking Toward Noninvasive Eye Cancer Treatment.

We present a new gaze tracking-based navigation scheme for proton beam radiation of intraocular tumors and we show the technical integration into the treatment facility. Currently, to treat a patient with such a tumor, a medical physicist positions the patient and the affected eye ball such that the radiation beam targets the tumor. This iterative eye positioning mechanism requires multiple X-rays, and radio-opaque clips previously sutured on the target eyeball. We investigate a possibility to replace this procedure with a noninvasive approach using a 3-D model-based gaze tracker. Previous work does not cover a comparably extensive integration of a gaze tracking device into a state-of-the-art proton beam facility without using additional hardware, such as a stereo optical tracking system. The integration is difficult because of limited available physical space, but only this enables to quantify the overall accuracy. We built a compact gaze tracker and integrated it into the proton beam radiation facility of the Paul Scherrer Institute in Villigen, Switzerland. Our results show that we can accurately estimate a healthy volunteer's point of gaze, which is the basis for the determination of the desired initial eye position. The proposed method is the first crucial step in order to make the proton therapy of the eye completely noninvasive.

Reliable volumetry of the cervical spinal cord in MS patient follow-up data with cord image analyzer (Cordial).

Spinal cord (SC) atrophy is an important contributor to the development of disability in many neurological disorders including multiple sclerosis (MS). To assess the spinal cord atrophy in clinical trials and clinical practice, largely automated methods are needed due to the sheer amount of data. Moreover, using these methods in longitudinal trials requires them to deliver highly reliable measurements, enabling comparisons of multiple data sets of the same subject over time. We present a method for SC volumetry using 3D MRI data providing volume measurements for SC sections of fixed length and location. The segmentation combines a continuous max flow approach with SC surface reconstruction that locates the SC boundary based on image voxel intensities. Two cutting planes perpendicular to the SC centerline are determined based on predefined distances to an anatomical landmark, and the cervical SC volume (CSCV) is then calculated in-between these boundaries. The development of the method focused on its application in MRI follow-up studies; the method provides a high scan-rescan reliability, which was tested on healthy subject data. Scan-rescan reliability coefficients of variation (COV) were below 1 %, intra- and interrater COV were even lower (0.1-0.2 %). To show the applicability in longitudinal trials, 3-year follow-up data of 48 patients with a progressive course of MS were assessed. In this cohort, CSCV loss was the only significant predictor of disability progression (p = 0.02). We are, therefore, confident that our method provides a reliable tool for SC volumetry in longitudinal clinical trials.

Augmented reality assisted laparoscopic partial nephrectomy.

Computer assisted navigation is a widely adopted technique in neurosurgery and orthopedics. However, it is rarely used for surgeries on abdominal organs. In this paper, we propose a novel, noninvasive method based on electromagnetic tracking to determine the pose of the kidney. As a clinical use case, we show a complete surgical navigation system for augmented reality assisted laparoscopic partial nephrectomy. Experiments were performed ex vivo on pig kidneys and the evaluation showed an excellent augmented reality alignment error of 2.1 mm ± 1.2 mm.