Atrial fibrillation: a retrospective chart review of complications, morbidity and mortality at 30 days

Introduction

Atrial fibrillation (AF) increasingly burdens medical health systems. Electrical cardioversion (ECV) forms an important rhythm control treatment for AF. Complications associated with this procedure include stroke and other arrhythmias.

Currently, institutional sedation protocols state that patients have to be admitted if 24-hour supervision by family or friends cannot be provided. This implies increased costs, both financially and by occupying a hospital bed. We anticipate that this strategy of admitting patients will become a problem in the future due to the rapid increase of AF patient due to aging of the population.

Purpose

Our aim is to analyse the incidence, type and timing of complications, to determine whether additional supervision is justified.

Methods

This was a retrospective single-centre study, in a large tertiary care hospital in the Netherlands. The study was approved by the Ethical Commission, registered with the Netherlands Trial Register (NL9433). Patients were contacted, those who did not object to the reuse of care data were included. Data was extracted from the electronic patient file, entered into a research database, and analysed. This study includes all eligible elective ECV's performed under general anaesthesia, in 2019. We analysed at the number of documented complications within 2 hours (T1), between 2 and 24 hours (T2) and within 30 days of the ECV (T3).

Results

In total, 370 patients were approached, 7 patients refused consent and 363 unique patients with 564 ECV procedures were included. The majority were male (66%), mean age 65±12 years, BMI 28±6 kg/m2, 49% smoker (current or past), 19% had previously undergone a form of AF ablation, 115 (32%) patients underwent ≥2 ECV's (range 2–11), and 6 patients were admitted due to a social indication.

In T1, 22 complications in 16 ECV's were documented, mostly unrelated to anaesthesia: asystole (3, >5 seconds asystole during/after procedure), hypotension (8), extreme bradycardia (8), chest-wall burn pain (1), and arrhythmias other than AF that developed after ECV (2). Nine complications in 7 ECVs (bradycardia, asystole and arrhythmias) were considered severe enough for admission, 5 patients were diagnosed with SSS/brady-tachy syndrome and were implanted with a pacemaker later.

In T2, 11 complications were documented: bradycardia (1), skin pain (3), muscle pain (2), fatigue (4), fainting and palpitations (1). The latter patient developed bradycardia and recurrent AF, and was readmitted.In T3, 15 complications were documented of which 5 were severe (CVA, angina, heart failure, arrhythmias).

Conclusion

Based on this retrospective analysis of all eligible ECV's in a large tertiary hospital, performed in 2019, complications in T2 (1,8%) needed no further treatment. We therefore conclude that it seems safe to discharge patients to their homes without extra supervision after sedation ECV

Funding Acknowledgement

Type of funding sources: None.

Challenging T > MIC Using Meropenem vs. Escherichia coli and Pseudomonas aeruginosa

Objective: For meropenem 40%T > MIC is associated with optimal killing of P. aeruginosa and E. coli. However, it is unknown how the distribution of %T > MIC through a treatment day impacts the antimicrobial effect in vitro. Therefore, we investigated the in vitro antibiotic activity of meropenem, precisely if 40%T > MIC is achieved in one single long period (single dose), 2 × 20% periods (dosing-bid), or 3 × 13.3% (dosing t.i.d.) thereby keeping the overall period of T > MIC constant.

Material/Methods: Time kill curves (TKC) with P. aeruginosa-ATCC-27853 and E. coli-ATCC-25922 and five clinical isolates each were implemented over 24 h in CAMHB with concentrations from 0.25×MIC-32×MIC. Periods over and under MIC were simulated by centrifugation steps (discarding supernatant and refilling with fresh CAMHB). Double and triple dosing involved further addition and removal of antibiotic. Complementary growth controls (GC) with and without centrifugation steps were done and the emergence of phenotypical resistance was evaluated (repeated MIC-testing after antibiotic administration).

Results: No impact of centrifugation on bacterial growth was seen. TKC with P. aeruginosa showed the best killing in the triple dosage, followed by the double and single dose. In multiple regimens at least a concentration of 4×MIC was needed to achieve a recommended 2-3 log10 killing. Likewise, a reduction of E. coli was best within the three short periods. Contrary to the TKCs with P. aeruginosa we could observe that after the inoculum reached a certain CFU/mL (≥10^8), no further addition of antibiotic could achieve bacterial killing (identified as the inoculum effect). For P. aeruginosa isolates resistance appeared within all regimens, the most pronounced was found in the 40%T > MIC experiments indicating that a single long period might accelerate the emergence of resistance. Contrary, for E. coli no emergence of resistance was found.

Conclusion/Outlook: We could show that not solely the %T > MIC is decisive for an efficient bacterial eradication in vitro, but also the distribution of the selected %T > MIC. Thus, dividing the 40%T > MIC in three short periods requested lowers antibiotic concentrations to achieve efficient bacterial killing and reduces the emergence of resistance in P. aeruginosa isolates. The distribution of the %T > MIC did impact the bacterial eradication of susceptible pathogens in vitro and might play an even bigger role in infections with intermediate or resistant pathogens.

Synthesis of 68Ga-radiopharmaceuticals using both generator-derived and cyclotron-produced 68Ga as exemplified by [68Ga]Ga-PSMA-11 for prostate cancer PET imaging

[⁶⁸Ga]Ga-PSMA-11, a urea-based peptidomimetic, is a diagnostic radiopharmaceutical for positron emission tomography (PET) imaging that targets the prostate-specific membrane antigen (PSMA). The recent Food and Drug Administration approval of [⁶⁸Ga]Ga-PSMA-11 for PET imaging of patients with prostate cancer, expected follow-up approval of companion radiotherapeutics (e.g., [¹⁷⁷Lu]Lu-PSMA-617, [²²⁵Ac]Ac-PSMA-617) and large prostate cancer patient volumes requiring access are poised to create an unprecedented demand for [⁶⁸Ga]Ga-PSMA-11 in nuclear medicine clinics around the world. Meeting this global demand is going to require a variety of synthesis methods compatible with ⁶⁸Ga eluted from a generator or produced on a cyclotron. To address this urgent need in the PET radiochemistry community, herein we report detailed protocols for the synthesis of [⁶⁸Ga]Ga-PSMA-11, (also known as HBED-CC, Glu-urea-Lys(Ahx)-HBED-CC and PSMA-HBED-CC) using both generator-eluted and cyclotron-produced ⁶⁸Ga and contrast the pros and cons of each method. The radiosyntheses are automated and have been validated for human use at two sites (University of Michigan (UM), United States; Royal Prince Alfred Hospital (RPA), Australia) and used to produce [⁶⁸Ga]Ga-PSMA-11 for patient use in good activity yields (single generator, 0.52 GBq (14 mCi); dual generators, 1.04-1.57 GBq (28-42 mCi); cyclotron method (single target), 1.47-1.89 GBq (40-51 mCi); cyclotron method (dual target), 3.63 GBq (98 mCi)) and high radiochemical purity (99%) (UM, n = 645; RPA, n > 600). Both methods are appropriate for clinical production but, in the long term, the method employing cyclotron-produced ⁶⁸Ga is the most promising for meeting high patient volumes. Quality control testing (visual inspection, pH, radiochemical purity and identity, radionuclidic purity and identity, sterile filter integrity, bacterial endotoxin content, sterility, stability) confirmed doses are suitable for clinical use, and there is no difference in clinical prostate cancer PET imaging using [⁶⁸Ga]Ga-PSMA-11 prepared using the two production methods.

Cyclotron-based production of 68Ga, [68Ga]GaCl3, and [68Ga]Ga-PSMA-11 from a liquid target

PURPOSE

To optimize the direct production of 68Ga on a cyclotron, via the 68Zn(p,n)68Ga reaction using a liquid cyclotron target. We Investigated the yield of cyclotron-produced 68Ga, extraction of [68Ga]GaCl3 and subsequent [68Ga]Ga-PSMA-11 labeling using an automated synthesis module.

METHODS

Irradiations of a 1.0 M solution of [68Zn]Zn(NO3)2 in dilute (0.2-0.3 M) HNO3 were conducted using GE PETtrace cyclotrons and GE 68Ga liquid targets. The proton beam energy was degraded to a nominal 14.3 MeV to minimize the co-production of 67Ga through the 68Zn(p,2n)67Ga reaction without unduly compromising 68Ga yields. We also evaluated the effects of varying beam times (50-75 min) and beam currents (27-40 μA). Crude 68Ga production was measured. The extraction of [68Ga]GaCl3 was performed using a 2 column solid phase method on the GE FASTlab Developer platform. Extracted [68Ga]GaCl3 was used to label [68Ga]Ga-PSMA-11 that was intended for clinical use.

RESULTS

The decay corrected yield of 68Ga at EOB was typically > 3.7 GBq (100 mCi) for a 60 min beam, with irradiations of [68Zn]Zn(NO3)2 at 0.3 M HNO3. Target/chemistry performance was more consistent when compared with 0.2 M HNO3. Radionuclidic purity of 68Ga was typically > 99.8% at EOB and met the requirements specified in the European Pharmacopoeia (< 2% combined 66/67Ga) for a practical clinical product shelf-life. The activity yield of [68Ga]GaCl3 was typically > 50% (~ 1.85 GBq, 50 mCi); yields improved as processes were optimized. Labeling yields for [68Ga]Ga-PSMA-11 were near quantitative (~ 1.67 GBq, 45 mCi) at EOS. Cyclotron produced [68Ga]Ga-PSMA-11 underwent full quality control, stability and sterility testing, and was implemented for human use at the University of Michigan as an Investigational New Drug through the US FDA and also at the Royal Prince Alfred Hospital (RPA).

CONCLUSION

Direct cyclotron irradiation of a liquid target provides clinically relevant quantities of [68Ga]Ga-PSMA-11 and is a viable alternative to traditional 68Ge/68Ga generators.

Side lying during nebulisation can significantly improve apical deposition in healthy adults and adults with mild cystic fibrosis lung disease: a randomised crossover trial

Background

In people with and without Cystic Fibrosis (CF), does side lying during nebulisation change: the proportion of the dose loaded in the nebuliser that is deposited in the lungs; the uniformity of deposition throughout the lungs; or the apical drug density as a percentage of the drug density in the remaining lung? Do these effects differ depending on the degree of lung disease present?

Methods

A randomised crossover trial with concealed allocation, intention-to-treat analysis and blinded assessors, involving 39 adults: 13 healthy, 13 with mild CF lung disease (FEV₁ > 80%pred), and 13 with more advanced CF lung disease (FEV₁ < 80%pred). In random order, 4 mL of nebulised radioaerosol was inhaled in upright sitting and in alternate right and left side lying at 2-min intervals, for 20 min.

Results

Compared to sitting upright, lung deposition and the uniformity of deposition were not significantly altered by side lying in any of the three groups. In sitting, the density of the deposition was significantly less in the apical regions than in the rest of the lung in all participants. Side lying significantly improved apical deposition in healthy adults (MD, 13%; 95% CI, 7 to 19), and in minimal CF lung disease (MD, 4%; 95% CI, 1 to 7) but not in advanced disease (MD, 4%; 95% CI, − 2 to 9).

Conclusion

Alternating between right and left side lying during nebulisation significantly improves apical deposition in healthy adults and in adults with mild CF lung disease, without substantial detriment to overall deposition.

Trial registration

ACTRN12611000674932 (Healthy), ACTRN12611000672954 (CF)

Retrospectively registered 4/7/2011.

Electronic supplementary material

The online version of this article (10.1186/s12890-019-0886-7) contains supplementary material, which is available to authorized users.

Effects of exercise and airway clearance (positive expiratory pressure) on mucus clearance in cystic fibrosis: a randomised crossover trial

Exercise improves mucus clearance in people without lung disease and those with chronic bronchitis. No study has investigated exercise alone for mucus clearance in cystic fibrosis (CF). The aim of this study was to compare the effects of treadmill exercise to resting breathing and airway clearance with positive expiratory pressure (PEP) therapy on mucus clearance in adults with CF.This 3-day randomised, controlled, crossover trial included 14 adults with mild to severe CF lung disease (forced expiratory volume in 1 s % predicted 31-113%). Interventions were 20 min of resting breathing (control), treadmill exercise at 60% of the participant's peak oxygen consumption or PEP therapy (including huffing and coughing). Mucus clearance was measured using the radioaerosol technique and gamma camera imaging.Treadmill exercise improved whole lung mucus clearance compared to resting breathing (mean difference 3%, 95% CI 2-4); however, exercise alone was less effective than PEP therapy (mean difference -7%, 95% CI -6- -8). When comparing treadmill exercise to PEP therapy, there were no significant differences in mucus clearance from the intermediate and peripheral lung regions, but significantly less clearance from the central lung region (likely reflecting the huffing and coughing that was only in PEP therapy).It is recommended that huffing and coughing are included to maximise mucus clearance with exercise.

A topo-graph model for indistinct target boundary definition from anatomical images

BACKGROUND AND OBJECTIVE

It can be challenging to delineate the target object in anatomical imaging when the object boundaries are difficult to discern due to the low contrast or overlapping intensity distributions from adjacent tissues.

METHODS

We propose a topo-graph model to address this issue. The first step is to extract a topographic representation that reflects multiple levels of topographic information in an input image. We then define two types of node connections - nesting branches (NBs) and geodesic edges (GEs). NBs connect nodes corresponding to initial topographic regions and GEs link the nodes at a detailed level. The weights for NBs are defined to measure the similarity of regional appearance, and weights for GEs are defined with geodesic and local constraints. NBs contribute to the separation of topographic regions and the GEs assist the delineation of uncertain boundaries. Final segmentation is achieved by calculating the relevance of the unlabeled nodes to the labels by the optimization of a graph-based energy function. We test our model on 47 low contrast CT studies of patients with non-small cell lung cancer (NSCLC), 10 contrast-enhanced CT liver cases and 50 breast and abdominal ultrasound images. The validation criteria are the Dice's similarity coefficient and the Hausdorff distance.

RESULTS

Student's t-test show that our model outperformed the graph models with pixel-only, pixel and regional, neighboring and radial connections (p-values <0.05).

CONCLUSIONS

Our findings show that the topographic representation and topo-graph model provides improved delineation and separation of objects from adjacent tissues compared to the tested models.

Preclinical in vivo and in vitro comparison of the translocator protein PET ligands [18F]PBR102 and [18F]PBR111

PURPOSE

To determine the metabolic profiles of the translocator protein ligands PBR102 and PBR111 in rat and human microsomes and compare their in vivo binding and metabolite uptake in the brain of non-human primates (Papio hamadryas) using PET-CT.

METHODS

In vitro metabolic profiles of PBR102 and PBR111 in rat and human liver microsomes were assessed by liquid chromatography-tandem mass spectrometry. [¹⁸F]PBR102 and [¹⁸F]PBR111 were prepared by nucleophilic substitution of their corresponding p-toluenesulfonyl precursors with [¹⁸F]fluoride. List mode PET-CT brain imaging with arterial blood sampling was performed in non-human primates. Blood plasma measurements and metabolite analysis, using solid-phase extraction, provided the metabolite profile and metabolite-corrected input functions for kinetic model fitting. Blocking and displacement PET-CT scans, using PK11195, were performed.

RESULTS

Microsomal analyses identified the O-de-alkylated, hydroxylated and N-de-ethyl derivatives of PBR102 and PBR111 as the main metabolites. The O-de-alkylated compounds were the major metabolites in both species; human liver microsomes were less active than those from rat. Metabolic profiles in vivo in non-human primates and previously published rat experiments were consistent with the microsomal results. PET-CT studies showed that K₁ was similar for baseline and blocking studies for both radiotracers; V_T was reduced during the blocking study, suggesting low non-specific binding and lack of appreciable metabolite uptake in the brain.

CONCLUSIONS

[¹⁸F]PBR102 and [¹⁸F]PBR111 have distinct metabolic profiles in rat and non-human primates. Radiometabolites contributed to non-specific binding and confounded in vivo brain analysis of [¹⁸F]PBR102 in rodents; the impact in primates was less pronounced. Both [¹⁸F]PBR102 and [¹⁸F]PBR111 are suitable for PET imaging of TSPO in vivo. In vitro metabolite studies can be used to predict in vivo radioligand metabolism and can assist in the design and development of better radioligands.

A combinatorial Bayesian and Dirichlet model for prostate MR image segmentation using probabilistic image features

Blurred boundaries and heterogeneous intensities make accurate prostate MR image segmentation problematic. To improve prostate MR image segmentation we suggest an approach that includes: (a) an image patch division method to partition the prostate into homogeneous segments for feature extraction; (b) an image feature formulation and classification method, using the relevance vector machine, to provide probabilistic prior knowledge for graph energy construction; (c) a graph energy formulation scheme with Bayesian priors and Dirichlet graph energy and (d) a non-iterative graph energy minimization scheme, based on matrix differentiation, to perform the probabilistic pixel membership optimization. The segmentation output was obtained by assigning pixels with foreground and background labels based on derived membership probabilities. We evaluated our approach on the PROMISE-12 dataset with 50 prostate MR image volumes. Our approach achieved a mean dice similarity coefficient (DSC) of 0.90  ±  0.02, which surpassed the five best prior-based methods in the PROMISE-12 segmentation challenge.

Topology polymorphism graph for lung tumor segmentation in PET-CT images

Accurate lung tumor segmentation is problematic when the tumor boundary or edge, which reflects the advancing edge of the tumor, is difficult to discern on chest CT or PET. We propose a 'topo-poly' graph model to improve identification of the tumor extent. Our model incorporates an intensity graph and a topology graph. The intensity graph provides the joint PET-CT foreground similarity to differentiate the tumor from surrounding tissues. The topology graph is defined on the basis of contour tree to reflect the inclusion and exclusion relationship of regions. By taking into account different topology relations, the edges in our model exhibit topological polymorphism. These polymorphic edges in turn affect the energy cost when crossing different topology regions under a random walk framework, and hence contribute to appropriate tumor delineation. We validated our method on 40 patients with non-small cell lung cancer where the tumors were manually delineated by a clinical expert. The studies were separated into an 'isolated' group (n = 20) where the lung tumor was located in the lung parenchyma and away from associated structures / tissues in the thorax and a 'complex' group (n = 20) where the tumor abutted / involved a variety of adjacent structures and had heterogeneous FDG uptake. The methods were validated using Dice's similarity coefficient (DSC) to measure the spatial volume overlap and Hausdorff distance (HD) to compare shape similarity calculated as the maximum surface distance between the segmentation results and the manual delineations. Our method achieved an average DSC of 0.881 ± 0.046 and HD of 5.311 ± 3.022 mm for the isolated cases and DSC of 0.870 ± 0.038 and HD of 9.370 ± 3.169 mm for the complex cases. Student's t-test showed that our model outperformed the other methods (p-values <0.05).

The relationship between neuropsychological functioning and FDG-PET hypometabolism in intractable mesial temporal lobe epilepsy

We examined the relationship between baseline neuropsychological functioning and 18-fluorodeoxyglucose positron emission tomography (FDG-PET) in intractable mesial temporal lobe epilepsy (MTLE). We hypothesized relationships between dominant temporal lobe hypometabolism and verbal memory and between nondominant temporal lobe hypometabolism and nonverbal memory in line with the lateralized material-specific model of memory deficits in MTLE. We also hypothesized an association between performance on frontal lobe neuropsychological tests and prefrontal hypometabolism. Thirty-two patients who had undergone temporal lobectomy for treatment of MTLE and who completed both presurgical FDG-PET and comprehensive neuropsychological investigations with widely used standardized measures were included. Age-adjusted composite measures were calculated for verbal memory, nonverbal memory, relative material-specific memory, IQ, executive function, attention/working memory, and psychomotor speed. Fluorodeoxyglucose positron emission tomography was analyzed with statistical parametric mapping (SPM) to identify hypometabolism relative to healthy controls. Pearson's correlation was used to determine the relationship between regions of hypometabolism and neuropsychological functioning. Dominant temporal lobe hypometabolism was associated with relatively inferior verbal memory, while nondominant temporal lobe hypometabolism was associated with inferior nonverbal memory. No relationship was found between performance on any frontal lobe measures and prefrontal hypometabolism. Statistical parametric mapping-quantified lateralized temporal lobe hypometabolism correlates with material-specific episodic memory impairment in MTLE. In contrast, prefrontal hypometabolism is not associated with performance on frontal lobe measures. We suggest that this is because frontal lobe neuropsychology tests may not be good measures of isolated frontal lobe functioning.

Metabolic changes in occipital lobe epilepsy with automatisms

PURPOSE

Some studies suggest that the pattern of glucose hypometabolism relates not only to the ictal-onset zone but also reflects seizure propagation. We investigated metabolic changes in patients with occipital lobe epilepsy (OLE) that may reflect propagation of ictal discharge during seizures with automatisms.

METHODS

Fifteen patients who had undergone epilepsy surgery for intractable OLE and had undergone interictal Fluorine-18-fluorodeoxyglucose positron-emission tomography ((18)F-FDG-PET) between 1994 and 2004 were divided into two groups (with and without automatisms during seizure). Significant regions of hypometabolism were identified by comparing (18)F-FDG-PET results from each group with 16 healthy controls by using statistical parametric mapping.

KEY FINDINGS

Significant hypometabolism was confined largely to the epileptogenic occipital lobe in the patient group without automatisms. In patients with automatisms, glucose hypometabolism extended from the epileptogenic occipital lobe into the ipsilateral temporal lobe.

SIGNIFICANCE

We identified a distinctive hypometabolic pattern that was specific for OLE patients with automatisms during a seizure. This finding supports the postulate that seizure propagation is a cause of glucose hypometabolism beyond the region of seizure onset.

Is "really conscious" sedation with solely an opioid an alternative to every day used sedation regimes for colonoscopies in a teaching hospital? Midazolam/fentanyl, propofol/alfentanil, or alfentanil only for colonoscopy: a randomized trial

BACKGROUND

We investigated the satisfaction of patients and endoscopists and concurrently safety aspects of an "alfentanil only" and two clinically routinely used sedation regimes in patients undergoing colonoscopy in a teaching hospital.

METHODS

One hundred and eighty patients were prospectively randomized in three groups: M (midazolam/fentanyl), A (alfentanil), and P (propofol/alfentanil); M and A were administered by an endoscopy nurse, P by an anesthesia nurse. Interventions, heart rate, saturation, electrocardiogram, noninvasive blood pressure, and expiratory CO₂ were monitored using video assistance. After endoscopy, patients and gastroenterologists completed questionnaires about satisfaction.

RESULTS

A high level of satisfaction was found in all groups, with patients in group P being more satisfied with their sedation experience (median 1.75, p < 0.001). Gastroenterologist satisfaction varied not significantly between the three alternatives. Patients in group A felt less drowsy, could communicate more rapidly than patients in both other groups, and met discharge criteria immediately after the end of the procedure. Respiratory events associated with sedation were observed in 43% patients in group M, 47% in group P, but only 13% in group A (p < 0.001).

CONCLUSIONS

These results suggest that alfentanil could be an alternative for sedation in colonoscopy even in the setting of a teaching hospital. It results in satisfied patients easily taking up information, and recovering rapidly. Although one might expect to observe more respiratory depression with an "opioid only" sedation technique without involvement of anesthesia partners, respiratory events were less frequent than when other methods were used.

Multi-Channel neurodegenerative pattern analysis and its application in Alzheimer's disease characterization

Neuroimaging has played an important role in non-invasive diagnosis and differentiation of neurodegenerative disorders, such as Alzheimer's disease and Mild Cognitive Impairment. Various features have been extracted from the neuroimaging data to characterize the disorders, and these features can be roughly divided into global and local features. Recent studies show a tendency of using local features in disease characterization, since they are capable of identifying the subtle disease-specific patterns associated with the effects of the disease on human brain. However, problems arise if the neuroimaging database involved multiple disorders or progressive disorders, as disorders of different types or at different progressive stages might exhibit different degenerative patterns. It is difficult for the researchers to reach consensus on what brain regions could effectively distinguish multiple disorders or multiple progression stages. In this study we proposed a Multi-Channel pattern analysis approach to identify the most discriminative local brain metabolism features for neurodegenerative disorder characterization. We compared our method to global methods and other pattern analysis methods based on clinical expertise or statistics tests. The preliminary results suggested that the proposed Multi-Channel pattern analysis method outperformed other approaches in Alzheimer's disease characterization, and meanwhile provided important insights into the underlying pathology of Alzheimer's disease and Mild Cognitive Impairment.

The cognitive profile of occipital lobe epilepsy and the selective association of left temporal lobe hypometabolism with verbal memory impairment

We investigated the cognitive profile of structural occipital lobe epilepsy (OLE) and whether verbal memory impairment is selectively associated with left temporal lobe hypometabolism on [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET). Nine patients with OLE, ages 8-29 years, completed presurgical neuropsychological assessment. Composite measures were calculated for intelligence quotient (IQ), speed, attention, verbal memory, nonverbal memory, and executive functioning. In addition, the Wisconsin Card Sorting Test (WCST) was used as a specific measure of frontal lobe functioning. Presurgical FDG-PET was analyzed with statistical parametric mapping in 8 patients relative to 16 healthy volunteers. Mild impairments were evident for IQ, speed, attention, and executive functioning. Four patients demonstrated moderate or severe verbal memory impairment. Temporal lobe hypometabolism was found in seven of eight patients. Poorer verbal memory was associated with left temporal lobe hypometabolism (p = 0.002), which was stronger (p = 0.03 and p = 0.005, respectively) than the association of left temporal lobe hypometabolism with executive functioning or with performance on the WCST. OLE is associated with widespread cognitive comorbidity, suggesting cortical dysfunction beyond the occipital lobe. Verbal memory impairment is selectively associated with left temporal lobe hypometabolism in OLE, supporting a link between neuropsychological dysfunction and remote hypometabolism in focal epilepsy.

A new energy framework with distribution descriptors for image segmentation

Segmentation of the target object(s) from images that have multiple complicated regions, mixture intensity distributions or are corrupted by noise poses a challenge for the level set models. In addition, the conventional piecewise smooth level set models normally require prior knowledge about the number of image segments. To address these problems, we propose a novel segmentation energy function with two distribution descriptors to model the background and the target. The single background descriptor models the heterogeneous background with multiple regions. Then, the target descriptor takes into account the intensity distribution and incorporates local spatial constraint. Our descriptors, which have more complete distribution information, construct the unique energy function to differentiate the target from the background and are more tolerant of image noise. We compare our approach to three other level set models: 1) the Chan-Vese; 2) the multiphase level set; and 3) the geodesic level set. This comparison using 260 synthetic images with varying levels and types of image noise and medical images with more complicated backgrounds showed that our method outperforms these models for accuracy and immunity to noise. On an additional set of 300 synthetic images, our model is also less sensitive to the contour initialization as well as to different types and levels of noise.

Robust model for segmenting images with/without intensity inhomogeneities

Intensity inhomogeneities and different types/levels of image noise are the two major obstacles to accurate image segmentation by region-based level set models. To provide a more general solution to these challenges, we propose a novel segmentation model that considers global and local image statistics to eliminate the influence of image noise and to compensate for intensity inhomogeneities. In our model, the global energy derived from a Gaussian model estimates the intensity distribution of the target object and background; the local energy derived from the mutual influences of neighboring pixels can eliminate the impact of image noise and intensity inhomogeneities. The robustness of our method is validated on segmenting synthetic images with/without intensity inhomogeneities, and with different types/levels of noise, including Gaussian noise, speckle noise, and salt and pepper noise, as well as images from different medical imaging modalities. Quantitative experimental comparisons demonstrate that our method is more robust and more accurate in segmenting the images with intensity inhomogeneities than the local binary fitting technique and its more recent systematic model. Our technique also outperformed the region-based Chan–Vese model when dealing with images without intensity inhomogeneities and produce better segmentation results than the graph-based algorithms including graph-cuts and random walker when segmenting noisy images.

Lung tumor segmentation in PET images using graph cuts

The aim of segmentation of tumor regions in positron emission tomography (PET) is to provide more accurate measurements of tumor size and extension into adjacent structures, than is possible with visual assessment alone and hence improve patient management decisions. We propose a segmentation energy function for the graph cuts technique to improve lung tumor segmentation with PET. Our segmentation energy is based on an analysis of the tumor voxels in PET images combined with a standardized uptake value (SUV) cost function and a monotonic downhill SUV feature. The monotonic downhill feature avoids segmentation leakage into surrounding tissues with similar or higher PET tracer uptake than the tumor and the SUV cost function improves the boundary definition and also addresses situations where the lung tumor is heterogeneous. We evaluated the method in 42 clinical PET volumes from patients with non-small cell lung cancer (NSCLC). Our method improves segmentation and performs better than region growing approaches, the watershed technique, fuzzy-c-means, region-based active contour and tumor customized downhill.

Joint probabilistic model of shape and intensity for multiple abdominal organ segmentation from volumetric CT images

We propose a novel joint probabilistic model that correlates a new probabilistic shape model with the corresponding global intensity distribution to segment multiple abdominal organs simultaneously. Our probabilistic shape model estimates the probability of an individual voxel belonging to the estimated shape of the object. The probability density of the estimated shape is derived from a combination of the shape variations of target class and the observed shape information. To better capture the shape variations, we used probabilistic principle component analysis optimized by expectation maximization to capture the shape variations and reduce computational complexity. The maximum a posteriori estimation was optimized by the iterated conditional mode-expectation maximization. We used 72 training datasets including low- and high-contrast CT images to construct the shape models for the liver, spleen and both kidneys. We evaluated our algorithm on 40 test datasets that were grouped into normal (34 normal cases) and pathologic (6 datasets) classes. The testing datasets were from different databases and manual segmentation was performed by different clinicians. We measured the volumetric overlap percentage error, relative volume difference, average square symmetric surface distance, false positive rate and false negative rate and our method achieved accurate and robust segmentation for multiple abdominal organs simultaneously.

Generalized regional disorder-sensitive-weighting scheme for 3D neuroimaging retrieval

3D functional neuroimaging is used in the diagnosis and management of neurological disorders. The efficient management and analysis of these large imaging datasets has prompted research in the field of content-based image retrieval. In this context, our generalized regional disorder-sensitive-weighting (DSW) scheme gives greater weight to brain regions affected by the diseases than regions that are relatively spared. We used two DSW matrices; one matrix is based on the occurrence maps that highlight abnormal functional regions; the other is based on the regional Fisher discriminant ratio. Our results suggest that our DSW matrices enhance neuroimaging data retrieval and provide a flexible weighting solution for the clinical analysis of different types of neurological disorders.

Automated PET-guided liver segmentation from low-contrast CT volumes using probabilistic atlas

The use of the functional PET information from PET-CT scans to improve liver segmentation from low-contrast CT data is yet to be fully explored. In this paper, we fully utilize PET information to tackle challenging liver segmentation issues including (1) the separation and removal of the surrounding muscles from liver region of interest (ROI), (2) better localization and mapping of the probabilistic atlas onto the low-contrast CT for a more accurate tissue classification, and (3) an improved initial estimation of the liver ROI to speed up the convergence of the expectation-maximization (EM) algorithm for the Gaussian distribution mixture model under the guidance of a probabilistic atlas. The primary liver extraction from the PET volume provides a simple mechanism to avoid the complicated pre-processing of feature extraction as used in the existing liver CT segmentation methods. It is able to guide the probabilistic atlas to better conform to the CT liver region and hence helps to overcome the challenge posed by liver shape variability. Our proposed method was evaluated against manual segmentation by experienced radiologists. Experimental results on 35 clinical PET-CT studies demonstrated that our method is accurate and robust in automated normal liver segmentation.

Thoracic image matching with appearance and spatial distribution

Positron emission tomography--computed tomography (PET-CT) produces co-registered anatomical (CT) and functional (PET) patient information (3D image set) from a single scanning session, and is now accepted as the best imaging technique to accurately stage the most common form of primary lung cancer--non-small cell lung cancer (NSCLC). This paper presents a content-based image retrieval (CBIR) method for retrieving similar images as a reference dataset to potentially aid the physicians in PET-CT scan interpretation. We design a spatial distribution to describe the spatial information of each region-of-interest (ROI), and a pairwise ROI mapping scheme between images to compute the image matching level. Similar images are then retrieved based on the local and spatial information of the detected ROIs, and a learned weighted sum of ROI distances. Our evaluation on clinical data shows good image retrieval performance.

Analgesia without sedatives during colonoscopies: worth considering?

Colonoscopy is a proven method for bowel cancer screening and is often experienced as a painful procedure. Today, there are two main strategies to facilitate colonoscopy. First, deep sedation results in satisfied patients but increases sedation-associated risks and raises costs for healthcare providers. Second, there is the advocacy for colonoscopies without any form of sedation. This might be an option for a special group of patients, but does not hold true for everybody. Following Moerman’s hypothesis: “If pain is the crucial point, why do we need sedation?” this review shows the analgesic options for a painless procedure, increasing success rates without increasing risk of sedation. There are two agents, with the potential to be a nearly ideal analgesic agent for colonoscopy: alfentanil and nitrous oxide (N₂O). Administration of either substance causes the patient to be comfortable yet alert and facilitates a short turnover. Advantages of these drugs include rapid onset and offset of action, analgesic and anxiolytic effects, ease of titration to desired level, rapid recovery, and an excellent safety profile.

Brain tissue segmentation in PET-CT images using probabilistic atlas and variational Bayes inference

PET-CT provides aligned anatomical (CT) and functional (PET) images in a single scan, and has the potential to improve brain PET image segmentation, which can in turn improve quantitative clinical analyses. We propose a statistical segmentation algorithm that incorporates the prior anatomical knowledge represented by probabilistic brain atlas into the variational Bayes inference to delineate gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) in brain PET-CT images. Our approach adds an additional novel aspect by allowing voxels to have variable and adaptive prior probabilities of belonging to each class. We compared our algorithm to the segmentation approaches implemented in the expectation maximization segmentation (EMS) and statistical parametric mapping (SPM8) packages in 26 clinical cases. The results show that our algorithm improves the accuracy of brain PET-CT image segmentation.

A rapid solid-phase extraction method for measurement of non-metabolised peripheral benzodiazepine receptor ligands, [(18)F]PBR102 and [(18)F]PBR111, in rat and primate plasma

OBJECTIVES

To develop a rapid and reliable method for estimating non-metabolised PBR ligands fluoroethoxy ([(18)F]PBR102)- and fluoropropoxy ([(18)F]PBR111)-substituted 2-(6-chloro-2-phenyl)imidazo[1,2-a]pyridine-3-yl)-N,N-diethylacetamides in plasma.

METHODS

Rats and baboons were imaged with PET up to 2 h postinjection of [(18)F]PBR102 and [(18)F]PBR111 under baseline conditions, after pre-blocking or displacement with PK11195. Arterial plasma samples were directly analysed by reverse-phase solid-phase extraction (RP-SPE) and RP-HPLC and by normal-phase TLC. SPE cartridges were successively washed with acetonitrile/water mixtures. SPE eluant radioactivity was measured in a γ-counter to determine the parent compound fraction and then analysed by HPLC and TLC for validation.

RESULTS

In SPE, hydrophilic and lipophilic radiolabelled metabolites were eluted in water and 20% acetonitrile/water. All non-metabolised [(18)F]PBR102 and [(18)F]PBR111 were in SPE acetonitrile fraction as confirmed by HPLC and TLC analysis. Unchanged (%) [(18)F]PBR102 and [(18)F]PBR111 from SPE analysis in rat and baboon plasma agreed with those from HPLC and TLC analysis. In rats and baboons, the fraction of unchanged tracer followed a bi-exponential decrease, with half-lives of 7 to 10 min for the fast component and >80 min for the slow component for both tracers.

CONCLUSIONS

Direct plasma SPE analysis of [(18)F]PBR102 and [(18)F]PBR111 can reliably estimate parent compound fraction. SPE was superior to HPLC for samples with low activity; it allows rapid and accurate metabolite analysis of a large number of plasma samples for improved estimation of metabolite-corrected input function during quantitative PET imaging studies.

A robust volumetric feature extraction approach for 3D neuroimaging retrieval

The increased volume of 3D neuroimaging data has created a need for efficient data management and retrieval. We suggest that image retrieval via robust volumetric features could benefit managing these large image datasets. In this paper, we introduce a new feature extraction method, based on disorder-oriented masks, that uses the volumetric spatial distribution patterns in 3D physiological parametric neurological images. Our preliminary results indicate that the proposed volumetric feature extraction approach could support reliable 3D neuroimaging data retrieval and management.

Multicenter evaluation of a standardized protocol for rest and acetazolamide cerebral blood flow assessment using a quantitative SPECT reconstruction program and split-dose 123I-iodoamphetamine

SPECT can provide valuable diagnostic and treatment response information in large-scale multicenter clinical trials. However, SPECT has been limited in providing consistent quantitative functional parametric values across the centers, largely because of a lack of standardized procedures to correct for attenuation and scatter. Recently, a novel software package has been developed to reconstruct quantitative SPECT images and assess cerebral blood flow (CBF) at rest and after acetazolamide challenge from a single SPECT session. This study was aimed at validating this technique at different institutions with a variety of SPECT devices and imaging protocols.

METHODS

Twelve participating institutions obtained a series of SPECT scans on physical phantoms and clinical patients. The phantom experiments included the assessment of septal penetration for each collimator used and of the accuracy of the reconstructed images. Clinical studies were divided into 3 protocols, including intrainstitutional reproducibility, a comparison with PET, and rest-rest study consistency. The results from 46 successful studies were analyzed.

RESULTS

Activity concentration estimation (Bq/mL) in the reconstructed SPECT images of a uniform cylindric phantom showed an interinstitution variation of ±5.1%, with a systematic underestimation of concentration by 12.5%. CBF values were reproducible both at rest and after acetazolamide on the basis of repeated studies in the same patient (mean ± SD difference, -0.4 ± 5.2 mL/min/100 g, n = 44). CBF values were also consistent with those determined using PET (-6.1 ± 5.1 mL/min/100 g, n = 6).

CONCLUSION

This study demonstrates that SPECT can quantitatively provide physiologic functional images of rest and acetazolamide challenge CBF, using a quantitative reconstruction software package.

Beneficial effect of inhaled mannitol and cough in asthmatics with mucociliary dysfunction

Asthmatics with overproduction of mucus that is viscous and sticky have impaired mucociliary clearance (MCC) leading to mucus plugs, and airway obstruction. Inhaled mannitol improves mucus clearance in other hypersecretory diseases. This study investigated the effect of mannitol and cough in asthmatics with mucociliary dysfunction. Seven stable asthmatics, age 52 ± 20 yr, lifelong non-smokers, without the diagnosis of bronchiectasis, with chronic cough and sputum production, treated with inhaled corticosteroids participated in the study. MCC and cough clearance (CC) was measured on 4 visits: at baseline (no cough or mannitol), with mannitol (240 and 480 mg) and cough control (no mannitol) over total 90 min using a radioaerosol technique and imaging with a gamma camera. Cough clearance was assessed after MCC by asking subjects to cough 100 times over 30 min. Premedication with eformoterol (12 μg) on all visits protected all subjects from bronchoconstriction (fall in FEV(1) > 15%) in response to mannitol. Mean (±SD) clearance over 60 min increased from 5.5 ± 5.6% at baseline and 7.3 ± 6.6% with cough control to 19.5 ± 14.6% and 26.4 ± 11.5% with 240 mg (p < 0.003) and 480 mg (p < 0.0001) of mannitol respectively. Total clearance (MCC + CC) over 90 min increased from 6.9 ± 6.5% (baseline) and 12.6 ± 8.3% without mannitol (cough control) to 34.6 ± 13.5 and 36.6 ± 10.4% with 240 and 480 mg mannitol respectively (p < 0.0001). Clearance over 90 min at baseline was not significantly different to cough control (p > 0.05). Mannitol improved clearance in all lung regions (p < 0.005). In conclusion, mannitol improved both mucociliary and cough clearance in asthmatics with mucociliary dysfunction and ineffective cough clearance. Clinical Trial registered with www.anzctr.org.au; Number ACTRN 12609001066279.aspx.

Automated liver segmentation for whole-body low-contrast CT images from PET-CT scanners

Accurate objective automated liver segmentation in PET-CT studies is important to improve the identification and localization of hepatic tumor. However, this segmentation is an extremely challenging task from the low-contrast CT images captured from PET-CT scanners because of the intensity similarity between liver and adjacent loops of bowel, stomach and muscle. In this paper, we propose a novel automated three-stage liver segmentation technique for PET-CT whole body studies, where: 1) the starting liver slice is automatically localized based on the liver - lung relations; 2) the "masking" slice containing the biggest liver section is localized using the ratio of liver ROI size to the right half of abdomen ROI size; 3) the liver segmented from the "masking" slice forms the initial estimation or mask for the automated liver segmentation. Our experimental results from clinical PET-CT studies show that this method can automatically segment the liver for a range of different patients, with consistent objective selection criteria and reproducible accurate results.

Genetic algorithm-based PCA eigenvector selection and weighting for automated identification of dementia using FDG-PET imaging

Parametric FDG-PET data offer the potential for an automated identification of the different dementia syndromes. Principal component analysis (PCA) can be used for feature extraction in FDG-PET. However, standard PCA is not always successful in delineating the features that have the best discrimination ability. We report a genetic algorithm-based method to identify an optimal combination of eigenvectors so that the resultant features are capable of successfully separating patients with suspected Alzheimer's disease and frontotemporal dementia from normal controls. We compared our approach with standard PCA on a set of 210 clinical cases and improved the performance in separating the dementia types with an accuracy of 90.0% and a Kappa statistic of 0.849. There was very good agreement between the automated technique and the diagnosis given by clinicians.

A graph-based approach to the retrieval of dual-modality biomedical images using spatial relationships

The increasing size of medical image archives and the complexity of medical images have led to the development of medical content-based image retrieval (CBIR) systems. These systems use the visual content of images for image retrieval in addition to conventional textual annotation, and have become a useful technique in biomedical data management. Existing CBIR systems are typically designed for use with single-modality images, and are restricted when multi-modal images, such as co-aligned functional positron emission tomography and anatomical computed tomography (PET/CT) images, are considered. Furthermore, the inherent spatial relationships among adjacent structures in biomedical images are not fully exploited. In this study, we present an innovative retrieval system for dual-modality PET/CT images by proposing the use of graph-based methods to spatially represent the structural relationships within these images. We exploit the co-aligned functional and anatomical information in PET/CT, using attributed relational graphs (ARG) to represent both modalities spatially and applying graph matching for similarity measurements. Quantitative evaluation demonstrated that our dual-modal ARG enabled the CBIR of dual-modality PET/CT. The potential of our dual-modal ARG in clinical application was also explored.

Constructing reliable parametric images using enhanced GLLS for dynamic SPECT

The generalized linear least square (GLLS) method can successfully construct unbiased parametric images from dynamic positron emission tomography data. Quantitative dynamic single photon emission computed tomography (SPECT) also has the potential to generate physiological parametric images. However, the high level of noise, intrinsic in SPECT, can give rise to unsuccessful voxelwise fitting using GLLS, resulting in physiologically meaningless estimates. In this paper, we systematically investigated the applicability of our recently proposed approaches to improve the reliability of GLLS to parametric image generation from noisy dynamic SPECT data. The proposed approaches include use of a prior estimate of distribution volume (V(d)), a bootstrap Monte Carlo (BMC) resampling technique, as well as a combination of both techniques. Full Monte Carlo simulations were performed to generate dynamic projection data, which were then reconstructed with and without resolution recovery, before generating parametric images with the proposed methods. Four experimental clinical datasets were also included in the analysis. The GLLS methods incorporating BMC resampling could successfully and reliably generate parametric images. For high signal-to-noise ratio (SNR) imaging data, the BMC-aided GLLS provided the best estimates of K(1) , while the BMC-V(d)-aided GLLS proved superior for estimating V(d). The improvement in reliability gained with BMC-aided GLLS in low SNR image data came at the expense of some overestimation of V(d) and increased computation time.

Optimal dual time point for FDG-PET in the differentiation of benign from malignant lung lesions: a simulation study

Dual time point imaging has been proposed as a means of improving the accuracy of Fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) in the diagnosis of lung malignancy. However, various sampling schedules have been used, which makes direct comparisons between their results difficult. It is unclear whether these schedules have the same accuracy for the diagnosis of lung malignancy, limiting the further development and adoption of these techniques. Although theoretically malignant and benign lesions show increasing difference in FDG uptake with longer uptake periods, the increasing noise due to decay may counteract this advantage and increase variability. In this paper, a method for the design of an optimal dual time point 18F-FDG PET imaging protocol has been proposed to address this issue.

Effect of particle size of dry powder mannitol on the lung deposition in healthy volunteers

There is a lack of in vivo studies focusing on the effect of particle size of dry powder aerosols on lung deposition and distribution. We investigated the dose and distribution of radiolabelled powder aerosols of mannitol in the lungs using single photon emission tomography (SPECT). Three different sized radiolabelled powders were produced by co-spray drying mannitol with 99mTc-DTPA. The primary particle size distribution of the powders measured by laser diffraction showed a volume median diameter of 2, 3 and 4 microm with span 2.3, 2.0 and 2.1, respectively, which corresponded to an aerodynamic diameter of 2.7, 3.6, 5.4 microm and geometric standard deviation of 2.6, 2.4 and 2.7 when the powders were dispersed using an Aeroliser dry powder inhaler. Three capsules each containing approximately 20mg (i.e. a total of 60 mg containing 60-90 MBq) of each of the radiolabelled powders were inhaled by eight healthy volunteers using the Aeroliser inhaler. Images of aerosol deposition in the lungs were acquired using fast, multi-bed position SPECT. The lung dose markedly decreased with increasing aerosol particle size (mean+/-S.E.M.: 44.8+/-2.4, 38.9+/-0.9, 20.6+/-1.6% for 2.7, 3.6, 5.4 microm, respectively, p<0.0001). The sites of deposition of the 2.7 and 3.6 microm aerosols were similar (penetration index, PI=0.63+/-0.05, 0.60+/-0.03, respectively, p>0.3), but different to the 5.4 microm aerosols (PI=0.52+/-0.04, p<0.02). The lung dose followed the in vitro powder dispersion performance, with the % lung dose being related to fine particle fraction by a slope of 0.8 for a regression with intercepts forced through the origin. The SPECT results provide direct evidence that the lung deposition of dry powder aerosols depends on the particle size. The lung dose of the 2.7 and 3.6 microm aerosols using the Aeroliser was double compared to that of the 5.4 microm aerosols and the deposition of the smaller particles was more peripheral.