Placental differences between uncomplicated and complicated monochorionic diamniotic pregnancies on diffusion and multicompartment Magnetic Resonance Imaging.

INTRODUCTION: Twin-twin transfusion syndrome (TTTS) and selective fetal growth restriction (sFGR) are common complications in monochorionic diamniotic (MCDA) pregnancies. The Diffusion-rElaxation Combined Imaging for Detailed Placental Evaluation (DECIDE) model, a placental-specific model, separates the T2 values of the fetal and maternal blood from the background tissue and estimates the fetal blood oxygen saturation. This study investigates diffusion and relaxation differences in uncomplicated MCDA pregnancies and MCDA pregnancies complicated by TTTS and sFGR in mid-pregnancy. METHODS: This prospective monocentric cohort study included uncomplicated MCDA pregnancies and pregnancies complicated by TTTS and sFGR. We performed MRI with conventional diffusion-weighted imaging (DWI) and combined relaxometry - DWI-intravoxel incoherent motion. DECIDE analysis was used to quantify different parameters within the placenta related to the fetal, placental, and maternal compartments. RESULTS: We included 99 pregnancies, of which 46 were uncomplicated, 12 were complicated by sFGR and 41 by TTTS. Conventional DWI did not find differences between or within cohorts. On DECIDE imaging, fetoplacental oxygen saturation was significantly lower in the smaller member of sFGR (p = 0.07) and in both members of TTTS (p = 0.01 and p = 0.004) compared to the uncomplicated pairs. Additionally, average T2 relaxation time was significantly lower in the smaller twin of the sFGR (p = 0.004) compared to the uncomplicated twins (p = 0.03). CONCLUSION: Multicompartment functional MRI showed significant differences in several MRI parameters between the placenta of uncomplicated MCDA pregnancies and those complicated by sFGR and TTTS in mid-pregnancy.

Application of Automatic Segmentation on Super-Resolution Reconstruction MR Images of the Abnormal Fetal Brain.

BACKGROUND AND PURPOSE: Fetal brain MR imaging is clinically used to characterize fetal brain abnormalities. Recently, algorithms have been proposed to reconstruct high-resolution 3D fetal brain volumes from 2D slices. By means of these reconstructions, convolutional neural networks have been developed for automatic image segmentation to avoid labor-intensive manual annotations, usually trained on data of normal fetal brains. Herein, we tested the performance of an algorithm specifically developed for segmentation of abnormal fetal brains. MATERIALS AND METHODS: This was a single-center retrospective study on MR images of 16 fetuses with severe CNS anomalies (gestation, 21-39 weeks). T2-weighted 2D slices were converted to 3D volumes using a super-resolution reconstruction algorithm. The acquired volumetric data were then processed by a novel convolutional neural network to perform segmentations of white matter and the ventricular system and cerebellum. These were compared with manual segmentation using the Dice coefficient, Hausdorff distance (95th percentile), and volume difference. Using interquartile ranges, we identified outliers of these metrics and further analyzed them in detail. RESULTS: The mean Dice coefficient was 96.2%, 93.7%, and 94.7% for white matter and the ventricular system and cerebellum, respectively. The Hausdorff distance was 1.1, 2.3, and 1.6 mm, respectively. The volume difference was 1.6, 1.4, and 0.3 mL, respectively. Of the 126 measurements, there were 16 outliers among 5 fetuses, discussed on a case-by-case basis. CONCLUSIONS: Our novel segmentation algorithm obtained excellent results on MR images of fetuses with severe brain abnormalities. Analysis of the outliers shows the need to include pathologies underrepresented in the current data set. Quality control to prevent occasional errors is still needed.

Neuroprotection is improved by watertightness of fetal spina bifida repair in the sheep model.

OBJECTIVES: A contributing factor to unsuccessful prenatal spina bifida aperta (SBA) repair via an open approach may be incomplete neurosurgical repair causing persistent in-utero leakage of cerebrospinal fluid (CSF) and exposure of the fetal spinal cord to amniotic fluid. We aimed to investigate the neurostructural and neurofunctional efficacy of watertight prenatal SBA repair in a validated SBA fetal lamb model. METHODS: A well-powered superiority study was conducted in the validated SBA fetal lamb model (n = 7 per group). The outcomes of lambs which underwent watertight or non-watertight multilayer repair through an open approach were compared to those of unrepaired SBA lambs (historical controls) at delivery (term = 145 days). At ∼75 days, fetal lambs underwent standardized induction of lumbar SBA. At ∼100 days, they were assigned to an either watertight or non-watertight layered repair group based on an intraoperative watertightness test using subcutaneous fluorescein injection. At 1-2 days postnatally, as primary outcome, we assessed reversal of hindbrain herniation using magnetic resonance imaging (MRI). Secondary proxies of neuroprotection were: absence of CSF leakage at the repair site; hindlimb motor function based on joint-movement score, locomotor grade and Motor Evoked Potential (MEP); four-score neuroprotection scale, encompassing live birth, complete hindbrain herniation reversal, absence of CSF leakage and joint-movement score ≥ 9/15; and brain and spinal cord histology and immunohistochemistry. As the watertightness test cannot be used clinically due to its invasiveness, we developed a potential surrogate intraoperative three-score skin-repair-quality scale based on visual assessment of the quality of the skin repair (suture inter-run distance ≤ 3 mm, absence of tear and absence of ischemia), with high quality defined by a score ≥ 2/3 and low quality by a score < 2/3, and assessed its relationship with improved outcome. RESULTS: Compared with unrepaired lambs, lambs with watertight repair achieved a high level of neuroprotection (neuroprotection score of 4/4 in 5/7 vs 0/7 lambs) as evidenced by: a significant 100% (vs 14%) reversal of hindbrain herniation on MRI; low CSF leakage (14% vs 100%); better hindlimb motor function, with higher joint-movement score, locomotor grade and MEP area under the curve and peak-to-peak amplitude; higher neuronal density in the hippocampus and corpus callosum; and higher reactive astrogliosis at the SBA lesion epicenter. Conversely, lambs with non-watertight SBA repair did not achieve the same level of neuroprotection (score of 4/4 in 1/7 lambs) compared with unrepaired lambs, with: a non-significant 86% (vs 14%) reversal of hindbrain herniation; high CSF leakage (43% vs 100%); no improvement in motor function; low brain neuron count in both the hippocampus and corpus callosum; and small spinal astroglial cell area at the epicenter. Both watertight layered repair and high (≥ 2/3) intraoperative skin-repair-quality score were associated with improved outcome, but the watertightness test and skin-repair-quality scale could not be used interchangeably due to result discrepancies. CONCLUSIONS: Watertight layered fetal SBA repair is neuroprotective since it improves brain and spinal-cord structure and function in the fetal lamb model. This translational research has important clinical implications. A neurosurgical technique that achieves watertightness should be adopted in all fetal centers to improve neuroprotection. Future clinical studies could assess whether a high skin-repair-quality score (≥ 2/3) correlates with neuroprotection. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Advanced quantitative evaluation of PET systems using the ACR phantom and NiftyPET software.

PURPOSE: A novel phantom-imaging platform, a set of software tools, for automated and high-precision imaging of the American College of Radiology (ACR) positron emission tomography (PET) phantom for PET/magnetic resonance (PET/MR) and PET/computed tomography (PET/CT) systems is proposed. METHODS: The key feature of this platform is the vector graphics design that facilitates the automated measurement of the knife-edge response function and hence image resolution, using composite volume of interest templates in a 0.5 mm resolution grid applied to all inserts of the phantom. Furthermore, the proposed platform enables the generation of an accurate µ $\mu$ -map for PET/MR systems with a robust alignment based on two-stage image registration using specifically designed PET templates. The proposed platform is based on the open-source NiftyPET software package used to generate multiple list-mode data bootstrap realizations and image reconstructions to determine the precision of the two-stage registration and any image-derived statistics. For all the analyses, iterative image reconstruction was employed with and without modeled shift-invariant point spread function and with varying iterations of the ordered subsets expectation maximization (OSEM) algorithm. The impact of the activity outside the field of view (FOV) was assessed using two acquisitions of 30 min each, with and without the activity outside the FOV. RESULTS: The utility of the platform has been demonstrated by providing a standard and an advanced phantom analysis including the estimation of spatial resolution using all cylindrical inserts. In the imaging planes close to the edge of the axial FOV, we observed deterioration in the quantitative accuracy, reduced resolution (FWHM increased by 1-2 mm), reduced contrast, and background uniformity due to the activity outside the FOV. Although it slows convergence, the PSF reconstruction had a positive impact on resolution and contrast recovery, but the degree of improvement depended on the regions. The uncertainty analysis based on bootstrap resampling of raw PET data indicated high precision of the two-stage registration. CONCLUSIONS: We demonstrated that phantom imaging using the proposed methodology with the metric of spatial resolution and multiple bootstrap realizations may be helpful in more accurate evaluation of PET systems as well as in facilitating fine tuning for optimal imaging parameters in PET/MR and PET/CT clinical research studies.

Optimal symptom combinations to aid COVID-19 case identification: Analysis from a community-based, prospective, observational cohort.

OBJECTIVES: Diagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health. METHODS: UK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity. FINDINGS: UK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC. INTERPRETATION: We confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.

Diagnostic value of cutaneous manifestation of SARS-CoV-2 infection.

BACKGROUND: One of the challenging aspects of SARS-CoV-2 infection is its diverse multisystemic disease presentation. OBJECTIVES: To evaluate the diagnostic value of cutaneous manifestations of SARS-CoV-2 infection and investigate their duration and timing in relation to other COVID-19 symptoms. METHODS: We used data from 336 847 UK users of the COVID Symptom Study app to assess the diagnostic value of body rash or an acral rash in SARS-CoV-2 infection, and data from an independent online survey of 11 544 respondents to investigate skin-specific symptoms and collect their photographs. RESULTS: Using data from the app, we show significant association between skin rashes and a positive swab test result (odds ratio 1·67, 95% confidence interval 1·42-1·97). Strikingly, among the respondents of the independent online survey, we found that 17% of SARS-CoV-2-positive cases reported skin rashes as the first presentation, and 21% as the only clinical sign of COVID-19. Together with the British Association of Dermatologists, we have compiled a catalogue of images of the most common skin manifestations of COVID-19 from 400 individuals (https://covidskinsigns.com), which we have made publicly available to assist clinicians in recognition of this early clinical feature of COVID-19. CONCLUSIONS: Skin rashes cluster with other COVID-19 symptoms, are predictive of a positive swab test, and occur in a significant number of cases, either alone or before other classical symptoms. Recognizing rashes is important in identifying new and earlier cases of COVID-19.

Cranial findings detected by second-trimester ultrasound in fetuses with myelomeningocele: a systematic review.

BACKGROUND: Abnormal intracranial findings are often detected at mid-trimester ultrasound (US) in fetuses with myelomeningocele (MMC). It is unclear whether these findings constitute a spectrum of the disease or are an independent finding, which should contraindicate fetal surgery. OBJECTIVE: To ascertain the spectrum and frequency of US-detected cranial findings in fetuses with MMC. SEARCH STRATEGY: MEDLINE, Embase, Web of Science and CENTRAL were searched from January 2000 to June 2020. SELECTION CRITERIA: Study reporting incidence of cranial US findings in consecutive cases of second-trimester fetuses with MMC. DATA COLLECTION AND ANALYSIS: Publication quality was assessed by Newcastle-Ottawa Scale (NOS) and modified NOS. Meta-analysis could not be performed as a result of high clinical diversity and study heterogeneity. MAIN RESULTS: Fourteen cranial US findings were reported in 15 studies. Findings in classic Chiari II malformation (CIIM) spectrum included posterior fossa funnelling (96%), small transcerebellar diameter (82-96%), 'banana' sign (50-100%), beaked tectum (65%) and 'lemon' sign (53-100%). Additional cranial findings were small biparietal diameter (BPD) and head circumference (HC) (<5th centile; 53 and 71%, respectively), ventriculomegaly (45-89%), abnormal pointed shape of the occipital horn (77-78%), thinning of the posterior cerebrum, perinodular heterotopia (11%), abnormal gyration (3%), corpus callosum disorders (60%) and midline interhemispheric cyst (42%). CONCLUSIONS: We identified 14 cranial findings by second-trimester US in fetuses with MMC. The relatively high incidence of these findings and their unclear prognostic significance might not contraindicate fetal surgery in the case of normal fetal genetic testing. Some cranial findings may independently affect postnatal outcome, however. Long-term detailed follow-up is required to investigate this. TWEETABLE ABSTRACT: A high rate of cranial abnormalities found on second-trimester ultrasound in fetuses with myelomeningocele.

Optimal symptom combinations to aid COVID-19 case identification: analysis from a community-based, prospective, observational cohort.

OBJECTIVES: Diagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health. METHODS: UK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity. FINDINGS: UK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC. INTERPRETATION: We confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.

Magnetic resonance imaging measurement of placental perfusion and oxygen saturation in early-onset fetal growth restriction.

OBJECTIVE: We hypothesised that a multi-compartment magnetic resonance imaging (MRI) technique that is sensitive to fetal blood oxygenation would identify changes in placental blood volume and fetal blood oxygenation in pregnancies complicated by early-onset fetal growth restriction (FGR). DESIGN: Case-control study. SETTING: London, UK. POPULATION: Women with uncomplicated pregnancies (estimated fetal weight [EFW] >10th centile for gestational age [GA] and normal maternal and fetal Doppler ultrasound, n = 12) or early-onset FGR (EFW <3rd centile with or without abnormal Doppler ultrasound <32 weeks GA, n = 12) were studied. METHODS: All women underwent MRI examination. Using a multi-compartment MRI technique, we quantified fetal and maternal blood volume and feto-placental blood oxygenation. MAIN OUTCOME MEASURES: Disease severity was stratified according to Doppler pulsatility index and the relationship to the MRI parameters was investigated, including the influence of GA at scan. RESULTS: The FGR group (mean GA 27+5  weeks, range 24+2 to 33+6  weeks) had a significantly lower EFW compared with the control group (mean GA 29+1  weeks; -705 g, 95% CI -353 to -1057 g). MRI-derived feto-placental oxygen saturation was higher in controls compared with FGR (75 ± 9.6% versus 56 ± 16.2%, P = 0.02, 95% CI 7.8-30.3%). Feto-placental oxygen saturation estimation correlated strongly with GA at scan in controls (r = -0.83). CONCLUSION: Using a novel multimodal MRI protocol we demonstrated reduced feto-placental blood oxygen saturation in pregnancies complicated by early-onset FGR. The degree of abnormality correlated with disease severity defined by ultrasound Doppler findings. Gestational age-dependent changes in oxygen saturation were also present in normal pregnancies. TWEETABLE ABSTRACT: MRI reveals differences in feto-placental oxygen saturation between normal and FGR pregnancy that is associated with disease severity.

Comparison of manual and semi-automatic registration in augmented reality image-guided liver surgery: a clinical feasibility study.

BACKGROUND: The laparoscopic approach to liver resection may reduce morbidity and hospital stay. However, uptake has been slow due to concerns about patient safety and oncological radicality. Image guidance systems may improve patient safety by enabling 3D visualisation of critical intra- and extrahepatic structures. Current systems suffer from non-intuitive visualisation and a complicated setup process. A novel image guidance system (SmartLiver), offering augmented reality visualisation and semi-automatic registration has been developed to address these issues. A clinical feasibility study evaluated the performance and usability of SmartLiver with either manual or semi-automatic registration. METHODS: Intraoperative image guidance data were recorded and analysed in patients undergoing laparoscopic liver resection or cancer staging. Stereoscopic surface reconstruction and iterative closest point matching facilitated semi-automatic registration. The primary endpoint was defined as successful registration as determined by the operating surgeon. Secondary endpoints were system usability as assessed by a surgeon questionnaire and comparison of manual vs. semi-automatic registration accuracy. Since SmartLiver is still in development no attempt was made to evaluate its impact on perioperative outcomes. RESULTS: The primary endpoint was achieved in 16 out of 18 patients. Initially semi-automatic registration failed because the IGS could not distinguish the liver surface from surrounding structures. Implementation of a deep learning algorithm enabled the IGS to overcome this issue and facilitate semi-automatic registration. Mean registration accuracy was 10.9 ± 4.2 mm (manual) vs. 13.9 ± 4.4 mm (semi-automatic) (Mean difference - 3 mm; p = 0.158). Surgeon feedback was positive about IGS handling and improved intraoperative orientation but also highlighted the need for a simpler setup process and better integration with laparoscopic ultrasound. CONCLUSION: The technical feasibility of using SmartLiver intraoperatively has been demonstrated. With further improvements semi-automatic registration may enhance user friendliness and workflow of SmartLiver. Manual and semi-automatic registration accuracy were comparable but evaluation on a larger patient cohort is required to confirm these findings.

Micro-CT and histological investigation of the spatial pattern of feto-placental vascular density.

INTRODUCTION: There are considerable variations in villous morphology within a normal placenta. However, whether there is a reproducible spatial pattern of variation in villous vascular density is not known. Micro-CT provides three-dimensional volume imaging with spatial resolution down to the micrometre scale. In this study, we applied Micro-CT and histological analysis to investigate the degree of heterogeneity of vascularisation within the placenta. METHOD: Ten term placentas were collected at elective caesarean section, perfused with contrast agent and imaged whole with Micro-CT. Eight full depth tissue blocks were then taken from each placenta and imaged. Sections were taken for histological analysis. Data was analysed to investigate vascular fill, and vascular density in relation to location from cord insertion to placental edge at each scale. RESULTS: Whole placental imaging revealed no spatially consistent difference in villous vessel density within the main placental tissue, although there was a great degree of heterogeneity. Both block imaging and histological analysis found a large degree of heterogeneity of vascular density within placentas, but no strong correlation between villous vascular density and block location (rs = 0.066, p = 0.7 block imaging, rs = 0.06, p = 0.6 histological analysis). DISCUSSION: This work presents a novel method for imaging the human placenta vascular tree using multiscale Micro-CT imaging. It demonstrates that there is a large degree of variation in vascular density throughout normal term human placentas. The three-dimensional data created by this technique could be used, with more advanced computer analysis, to further investigate the structure of the vascular tree.

Artificial intelligence for the real-time classification of intrapapillary capillary loop patterns in the endoscopic diagnosis of early oesophageal squamous cell carcinoma: A proof-of-concept study.

Background: Intrapapillary capillary loops (IPCLs) represent an endoscopically visible feature of early squamous cell neoplasia (ESCN) which correlate with invasion depth - an important factor in the success of curative endoscopic therapy. IPCLs visualised on magnification endoscopy with Narrow Band Imaging (ME-NBI) can be used to train convolutional neural networks (CNNs) to detect the presence and classify staging of ESCN lesions. Methods: A total of 7046 sequential high-definition ME-NBI images from 17 patients (10 ESCN, 7 normal) were used to train a CNN. IPCL patterns were classified by three expert endoscopists according to the Japanese Endoscopic Society classification. Normal IPCLs were defined as type A, abnormal as B1-3. Matched histology was obtained for all imaged areas. Results: This CNN differentiates abnormal from normal IPCL patterns with 93.7% accuracy (86.2% to 98.3%) and sensitivity and specificity for classifying abnormal IPCL patterns of 89.3% (78.1% to 100%) and 98% (92% to 99.7%), respectively. Our CNN operates in real time with diagnostic prediction times between 26.17 ms and 37.48 ms. Conclusion: Our novel and proof-of-concept application of computer-aided endoscopic diagnosis shows that a CNN can accurately classify IPCL patterns as normal or abnormal. This system could be used as an in vivo, real-time clinical decision support tool for endoscopists assessing and directing local therapy of ESCN.

Interactive virtual 3D models of renal cancer patient anatomies alter partial nephrectomy surgical planning decisions and increase surgeon confidence compared to volume-rendered images.

PURPOSE: To determine whether the interactive visualisation of patient-specific virtual 3D models of the renal anatomy influences the pre-operative decision-making process of urological surgeons for complex renal cancer operations. METHODS: Five historic renal cancer patient pre-operative computed tomography (CT) datasets were retrospectively selected based on RENAL nephrectomy score and variety of anatomy. Interactive virtual 3D models were generated for each dataset using image segmentation software and were made available for online visualisation and manipulation. Consultant urologists were invited to participate in the survey which consisted of CT and volume-rendered images (VRI) for the control arm, and CT with segmentation overlay and the virtual 3D model for the intervention arm. A questionnaire regarding anatomical structures, surgical approach, and confidence was administered. RESULTS: Twenty-five participants were recruited (54% response rate), with 19/25 having > 5 years of renal surgery experience. The median anatomical clarity score increased from 3 for the control to 5 for the intervention arm. A change in planned surgical approach was reported in 19% of cases. Virtual 3D models increased surgeon confidence in the surgical decisions in 4/5 patient datasets. There was a statistically significant improvement in surgeon opinion of the potential utility for decision-making purposes of virtual 3D models as compared to VRI at the multidisciplinary team meeting, theatre planning, and intra-operative stages. CONCLUSION: The use of pre-operative interactive virtual 3D models for surgery planning influences surgical decision-making. Further studies are needed to investigate if the use of these models changes renal cancer surgery outcomes.

Somatosensory function and pain in extremely preterm young adults from the UK EPICure cohort: sex-dependent differences and impact of neonatal surgery.

BACKGROUND: Surgery or multiple procedural interventions in extremely preterm neonates influence neurodevelopmental outcome and may be associated with long-term changes in somatosensory function or pain response. METHODS: This observational study recruited extremely preterm (EP, <26 weeks' gestation; n=102, 60% female) and term-born controls (TC; n=48) aged 18-20 yr from the UK EPICure cohort. Thirty EP but no TC participants had neonatal surgery. Evaluation included: quantitative sensory testing (thenar eminence, chest wall); clinical pain history; questionnaires (intelligence quotient; pain catastrophising; anxiety); and structural brain imaging. RESULTS: Reduced thermal threshold sensitivity in EP vs TC participants persisted at age 18-20 yr. Sex-dependent effects varied with stimulus intensity and were enhanced by neonatal surgery, with reduced threshold sensitivity in EP surgery males but increased sensitivity to prolonged noxious cold in EP surgery females (P<0.01). Sex-dependent differences in thermal sensitivity correlated with smaller amygdala volume (P<0.05) but not current intelligence quotient. While generalised decreased sensitivity encompassed mechanical and thermal modalities in EP surgery males, a mixed pattern of sensory loss and sensory gain persisted adjacent to neonatal scars in males and females. More EP participants reported moderate-severe recurrent pain (22/101 vs 4/48; χ2=0.04) and increased pain intensity correlated with higher anxiety and pain catastrophising. CONCLUSIONS: After preterm birth and neonatal surgery, different patterns of generalised and local scar-related alterations in somatosensory function persist into early adulthood. Sex-dependent changes in generalised sensitivity may reflect central modulation by affective circuits. Early life experience and sex/gender should be considered when evaluating somatosensory function, pain experience, or future chronic pain risk.

Structural cortical network reorganization associated with early conversion to multiple sclerosis.

Brain structural covariance networks (SCNs) based on pairwise statistical associations of cortical thickness data across brain areas reflect underlying physical and functional connections between them. SCNs capture the complexity of human brain cortex structure and are disrupted in neurodegenerative conditions. However, the longitudinal assessment of SCN dynamics has not yet been explored, despite its potential to unveil mechanisms underlying neurodegeneration. Here, we evaluated the changes of SCNs over 12 months in patients with a first inflammatory-demyelinating attack of the Central Nervous System and assessed their clinical relevance by comparing SCN dynamics of patients with and without conversion to multiple sclerosis (MS) over one year. All subjects underwent clinical and brain MRI assessments over one year. Brain cortical thicknesses for each subject and time point were used to obtain group-level between-area correlation matrices from which nodal connectivity metrics were obtained. Robust bootstrap-based statistical approaches (allowing sampling with replacement) assessed the significance of longitudinal changes. Patients who converted to MS exhibited significantly greater network connectivity at baseline than non-converters (p = 0.02) and a subsequent connectivity loss over time (p = 0.001-0.02), not observed in non-converters' network. These findings suggest SCN analysis is sensitive to brain tissue changes in early MS, reflecting clinically relevant aspects of the condition. However, this is preliminary work, indicated by the low sample sizes, and its results and conclusions should be treated with caution and confirmed with larger cohorts.

3-D Pose Estimation of Articulated Instruments in Robotic Minimally Invasive Surgery.

Estimating the 3-D pose of instruments is an important part of robotic minimally invasive surgery for automation of basic procedures as well as providing safety features, such as virtual fixtures. Image-based methods of 3-D pose estimation provide a non-invasive low cost solution compared with methods that incorporate external tracking systems. In this paper, we extend our recent work in estimating rigid 3-D pose with silhouette and optical flow-based features to incorporate the articulated degrees-of-freedom (DOFs) of robotic instruments within a gradient-based optimization framework. Validation of the technique is provided with a calibrated ex-vivo study from the da Vinci Research Kit (DVRK) robotic system, where we perform quantitative analysis on the errors each DOF of our tracker. Additionally, we perform several detailed comparisons with recently published techniques that combine visual methods with kinematic data acquired from the joint encoders. Our experiments demonstrate that our method is competitively accurate while relying solely on image data.

Bullseye's representation of cerebral white matter hyperintensities.

BACKGROUND AND PURPOSE: Visual rating scales have limited capacities to depict the regional distribution of cerebral white matter hyperintensities (WMH). We present a regional-zonal volumetric analysis alongside a visualization tool to compare and deconstruct visual rating scales. MATERIALS AND METHODS: 3D T1-weighted, T2-weighted spin-echo and FLAIR images were acquired on a 3T system, from 82 elderly participants in a population-based study. Images were automatically segmented for WMH. Lobar boundaries and distance to ventricular surface were used to define white matter regions. Regional-zonal WMH loads were displayed using bullseye plots. Four raters assessed all images applying three scales. Correlations between visual scales and regional WMH as well as inter and intra-rater variability were assessed. A multinomial ordinal regression model was used to predict scores based on regional volumes and global WMH burdens. RESULTS: On average, the bullseye plot depicted a right-left symmetry in the distribution and concentration of damage in the periventricular zone, especially in frontal regions. WMH loads correlated well with the average visual rating scores (e.g. Kendall's tau [Volume, Scheltens]=0.59 CI=[0.53 0.62]). Local correlations allowed comparison of loading patterns between scales and between raters. Regional measurements had more predictive power than global WMH burden (e.g. frontal caps prediction with local features: ICC=0.67 CI=[0.53 0.77], global volume=0.50 CI=[0.32 0.65], intra-rater=0.44 CI=[0.23 0.60]). CONCLUSION: Regional-zonal representation of WMH burden highlights similarities and differences between visual rating scales and raters. The bullseye infographic tool provides a simple visual representation of regional lesion load that can be used for rater calibration and training.

The Bionic Clicker Mark I & II.

In this manuscript, we present two 'Bionic Clicker' systems, the first designed to demonstrate electromyography (EMG) based control systems for educational purposes and the second for research purposes. EMG based control systems pick up electrical signals generated by muscle activation and use these as inputs for controllers. EMG controllers are widely used in prosthetics to control limbs. The Mark I (MK I) clicker allows the wearer to change the slide of a presentation by raising their index finger. It is built around a microcontroller and a bio-signals shield. It generated a lot of interest from both the public and research community. The Mark II (MK II) device presented here was designed to be a cheaper, sleeker, and more customizable system that can be easily modified and directly transmit EMG data. It is built using a wireless capable microcontroller and a muscle sensor.

Evaluation of a multi-atlas CT synthesis approach for MRI-only radiotherapy treatment planning.

BACKGROUND AND PURPOSE: Computed tomography (CT) imaging is the current gold standard for radiotherapy treatment planning (RTP). The establishment of a magnetic resonance imaging (MRI) only RTP workflow requires the generation of a synthetic CT (sCT) for dose calculation. This study evaluates the feasibility of using a multi-atlas sCT synthesis approach (sCTa) for head and neck and prostate patients. MATERIAL AND METHODS: The multi-atlas method was based on pairs of non-rigidly aligned MR and CT images. The sCTa was obtained by registering the MRI atlases to the patient's MRI and by fusing the mapped atlases according to morphological similarity to the patient. For comparison, a bulk density assignment approach (sCTbda) was also evaluated. The sCTbda was obtained by assigning density values to MRI tissue classes (air, bone and soft-tissue). After evaluating the synthesis accuracy of the sCTs (mean absolute error), sCT-based delineations were geometrically compared to the CT-based delineations. Clinical plans were re-calculated on both sCTs and a dose-volume histogram and a gamma analysis was performed using the CT dose as ground truth. RESULTS: Results showed that both sCTs were suitable to perform clinical dose calculations with mean dose differences less than 1% for both the planning target volume and the organs at risk. However, only the sCTa provided an accurate and automatic delineation of bone. CONCLUSIONS: Combining MR delineations with our multi-atlas CT synthesis method could enable MRI-only treatment planning and thus improve the dosimetric and geometric accuracy of the treatment, and reduce the number of imaging procedures.

Rapid processing of PET list-mode data for efficient uncertainty estimation and data analysis.

In this technical note we propose a rapid and scalable software solution for the processing of PET list-mode data, which allows the efficient integration of list mode data processing into the workflow of image reconstruction and analysis. All processing is performed on the graphics processing unit (GPU), making use of streamed and concurrent kernel execution together with data transfers between disk and CPU memory as well as CPU and GPU memory. This approach leads to fast generation of multiple bootstrap realisations, and when combined with fast image reconstruction and analysis, it enables assessment of uncertainties of any image statistic and of any component of the image generation process (e.g. random correction, image processing) within reasonable time frames (e.g. within five minutes per realisation). This is of particular value when handling complex chains of image generation and processing. The software outputs the following: (1) estimate of expected random event data for noise reduction; (2) dynamic prompt and random sinograms of span-1 and span-11 and (3) variance estimates based on multiple bootstrap realisations of (1) and (2) assuming reasonable count levels for acceptable accuracy. In addition, the software produces statistics and visualisations for immediate quality control and crude motion detection, such as: (1) count rate curves; (2) centre of mass plots of the radiodistribution for motion detection; (3) video of dynamic projection views for fast visual list-mode skimming and inspection; (4) full normalisation factor sinograms. To demonstrate the software, we present an example of the above processing for fast uncertainty estimation of regional SUVR (standard uptake value ratio) calculation for a single PET scan of (18)F-florbetapir using the Siemens Biograph mMR scanner.