Mikkel Gram

Morphological and functional evaluation of chronic pancreatitis with magnetic resonance imaging

Magnetic resonance imaging (MRI) techniques for assessment of morphology and function of the pancreas have been improved dramatically the recent years and MRI is very often used in diagnosing and follow-up of chronic pancreatitis (CP) patients. Standard MRI including fat-suppressed T1-weighted and T2-weighted imaging techniques reveal decreased signal and glandular atrophy of the pancreas in CP. In contrast-enhanced MRI of the pancreas in CP the pancreatic signal is usually reduced and delayed due to decreased perfusion as a result of chronic inflammation and fibrosis. Thus, morphological changes of the ductal system can be assessed by magnetic resonance cholangiopancreatography (MRCP). Furthermore, secretin-stimulated MRCP is a valuable technique to evaluate side branch pathology and the exocrine function of the pancreas and diffusion weighted imaging can be used to quantify both parenchymal fibrotic changes and the exocrine function of the pancreas. These standard and advanced MRI techniques are supplementary techniques to reveal morphological and functional changes of the pancreas in CP. Recently, spectroscopy has been used for assessment of metabolite concentrations in-vivo in different tissues and may have the potential to offer better tissue characterization of the pancreas. Hence, the purpose of the present review is to provide an update on standard and advanced MRI techniques of the pancreas in CP.

Stenosis Detection Algorithm for Screening of Arteriovenous Fistulae

The aim of the study was to develop an algorithm that can detect stenosis formation in arteriovenous fistulae based on audio recordings. 34 patients with a mature arteriovenous fistula were examined with use of an electronic stethoscope and subsequently by ultrasound. 27 patients had a patent fistula, while the other group consisted of 5 patients with stenosis and 2 with artificial narrowing of the fistula. Feature extraction was carried out using wavelet packet decomposition at depth 4. For each recording the scale energies SE i and the percentage of scale energy versus total energy SEp i , were calculated. The two most discriminative features with low correlation were found to be SE8 and SEp8. These features were evaluated using leave-one-out cross-validation with a quadratic discriminant function. Cross-validation using SE8 and SEp8 yielded a sensitivity of 100% and a specificity of 94%. The algorithm developed using the features obtained by wavelet analysis is reliable for detecting stenosis in a vein segment of an arteriovenous fistula. Based on these results, the prospects of developing an accurate, low-cost screening method for patients undergoing hemodialysis, are promising.

Quantification and variability in colonic volume with a novel magnetic resonance imaging method.

Segmental distribution of colorectal volume is relevant in a number of diseases, but clinical and experimental use demands robust reliability and validity. Using a novel semi‐automatic magnetic resonance imaging‐based technique, the aims of this study were to describe: (i) inter‐individual and intra‐individual variability of segmental colorectal volumes between two observations in healthy subjects and (ii) the change in segmental colorectal volume distribution before and after defecation.

Dynamic spectral indices of the electroencephalogram provide new insights into tonic pain.

OBJECTIVE This study aimed to investigate reliability of electroencephalography (EEG) during rest and tonic pain. Furthermore, changes in EEG between the two states as well as dynamics and relation to pain ratings were investigated. METHODS On two separate days EEG was recorded in 39 subjects during rest and tonic pain (cold pressor test: left hand held in 2°C water for 2 min.) while pain intensity was rated continuously. Dynamic spectral analysis was performed on the EEG. Between-day reliability of spectral indices was assessed and correlations to pain ratings were investigated. RESULTS EEG reliability was high during both states. The relative spectral indices increased in delta (1-4 Hz; P=0.0002), beta3 (18-32 Hz; P<0.0001) and gamma (32-70 Hz; P<0.0001) bands during tonic pain, and decreased in theta (4-8 Hz; P<0.0001), alpha1 (8-10 Hz; P<0.0001), alpha2 (10-12 Hz; P<0.0001) bands. Theta, beta3 and gamma bands correlated significantly to the area-under-curve of pain ratings, but only theta was dynamic and correlated to the pain ratings (R=0.88, P<0.0001). CONCLUSIONS EEG assessed during tonic pain is a valid experimental pain model both in terms of reliability between days and in connection between cortical activity and pain perception. SIGNIFICANCE EEG during tonic pain is more pain-specific and should be used in future basic and pharmacological studies.

Machine learning on encephalographic activity may predict opioid analgesia.

Opioids are used for the treatment of pain. However, 30–50% of patients have insufficient effect to the opioid initially selected by the physician, and there is an urgent need for biomarkers to select responders to the most appropriate drug. Since opioids mediate their effect in the central nervous system, this study aimed to investigate if electroencephalography (EEG) during rest or pain before treatment could predict the analgesic response.

A novel approach to pharmaco‐EEG for investigating analgesics: assessment of spectral indices in single‐sweep evoked brain potentials

AIMS To compare results from analysis of averaged and single-sweep evoked brain potentials (EPs) by visual inspection and spectral analysis in order to identify an objective measure for the analgesic effect of buprenorphine and fentanyl. METHODS Twenty-two healthy males were included in a randomized study to assess the changes in EPs after 110 sweeps of painful electrical stimulation to the median nerve following treatment with buprenorphine, fentanyl or placebo patches. Bone pressure, cutaneous heat and electrical pain ratings were assessed. EPs and pain assessments were obtained before drug administration, 24, 48, 72 and 144 h after beginning of treatment. Features from EPs were extracted by three different approaches: (i) visual inspection of amplitude and latency of the main peaks in the average EPs, (ii) spectral distribution of the average EPs and (iii) spectral distribution of the EPs from single-sweeps. RESULTS Visual inspection revealed no difference between active treatments and placebo (all P > 0.05). Spectral distribution of the averaged potentials showed a decrease in the beta (12-32 Hz) band for fentanyl (P = 0.036), which however did not correlate with pain ratings. Spectral distribution in the single-sweep EPs revealed significant increases in the theta, alpha and beta bands for buprenorphine (all P < 0.05) as well as theta band increase for fentanyl (P = 0.05). For buprenorphine, beta band activity correlated with bone pressure and cutaneous heat pain (both P = 0.04, r = 0.90). CONCLUSION In conclusion single-sweep spectral band analysis increases the information on the response of the brain to opioids and may be used to identify the response to analgesics.

Abnormal neuronal response to rectal and anal stimuli in patients with idiopathic fecal incontinence

The pathophysiology behind idiopathic fecal incontinence (IFI) is poorly understood. We hypothesized abnormal sensory pathways along the brain‐gut axis as a key player in this disease, reflected in cortical evoked potentials (CEP) from mechanical stimuli of the rectum and the anal canal.

Prediction of postoperative opioid analgesia using clinical-experimental parameters and electroencephalography.

Opioids are often used for pain treatment, but the response is often insufficient and dependent on e.g. the pain condition, genetic factors and drug class. Thus, there is an urgent need to identify biomarkers to enable selection of the appropriate drug for the individual patient, a concept known as personalized medicine. Quantitative sensory testing (QST) and clinical parameters can provide some guidance for response, but better and more objective biomarkers are urgently warranted. Electroencephalography (EEG) may be suitable since it assesses the central nervous system where opioids mediate their effects.

Opioid-induced bowel dysfunction in healthy volunteers assessed with questionnaires and MRI

Objective Opioid treatment is associated with numerous gastrointestinal adverse effects collectively known as opioid-induced bowel dysfunction (OIBD). Most current knowledge of the pathophysiology derives from animal studies limited by species differences and clinical studies, which have substantial confounders that make evaluation difficult. An experimental model of OIBD in healthy volunteers in a controlled setting is therefore highly warranted. The aim of this study was to assess bowel function in healthy volunteers during opioid treatment using subjective and objective methods. Methods Twenty-five healthy men were assigned randomly to oxycodone or placebo for 5 days in a cross-over design. The analgesic effect was assessed with muscle pressure algometry and adverse effects were measured using questionnaires including the bowel function index, gastrointestinal symptom rating scale, patient assessment of constipation symptoms and the Bristol stool form scale. Colorectal volumes were determined using a newly developed MRI method. Results Compared with baseline, oxycodone increased pain detection thresholds by 8% (P=0.02). Subjective OIBD was observed as increased bowel function index (464% increase; P<0.001), gastrointestinal symptom rating scale (37% increase; P<0.001) and patient assessment of constipation symptoms (198% increase; P<0.001). Objectively, stools were harder and drier during oxycodone treatment (P<0.001) and segmental colorectal volumes increased in the caecum/ascending colon by 41% (P=0.005) and in the transverse colon by 20% (P=0.005). No associations were detected between questionnaire scores and colorectal volumes. Conclusion Experimental OIBD in healthy volunteers was induced during oxycodone treatment. This model has potential for future interventional studies to discriminate the efficacies of different laxatives, peripheral morphine antagonists and opioid treatments.

New spectral thresholds improve the utility of the electroencephalogram for the diagnosis of hepatic encephalopathy

OBJECTIVE The utility of the electroencephalogram (EEG) for the diagnosis of hepatic encephalopathy, using conventional spectral thresholds, is open to question. The aim of this study was to optimise its diagnostic performance by defining new spectral thresholds. METHODS EEGs were recorded in 69 healthy controls and 113 patients with cirrhosis whose neuropsychiatric status was classified using clinical and psychometric criteria. New EEG spectral thresholds were calculated, on the parietal P3-P4 lead derivation, using an extended multivariable receiver operating characteristic curve analysis. Thresholds were validated in a separate cohort of 68 healthy controls and 113 patients with cirrhosis. The diagnostic performance of the newly derived spectral thresholds was further validated using a machine learning technique. RESULTS The diagnostic performance of the new thresholds (sensitivity 75.0%; specificity 77.4%) was better balanced than that of the conventional thresholds (58.3%; 93.2%) and comparable to the performance of a machine learning technique (72.9%; 76.8%). The diagnostic utility of the new thresholds was confirmed in the validation cohort. CONCLUSIONS Adoption of the new spectral thresholds would significantly improve the utility of the EEG for the diagnosis of hepatic encephalopathy. SIGNIFICANCE These new spectral EEG thresholds optimise the performance of the EEG for the diagnosis of hepatic encephalopathy and can be adopted without the need to alter data recording or the initial processing of traces.