Background/aims
Electroencephalography (EEG) recorded as evoked brain potentials (EPs) reflects the cortical processing to an external event. This approach is often used to study the altered response to acute pain in chronic pain patients compared to healthy volunteers. However, discrimination of the responses from the study populations is a non-trivial task, which calls for improved objective methods.
Methods
To develop and validate a new methodology, we analyzed data from 16 type-1 diabetes mellitus patients and 15 age and gender matched volunteers, by means of brain activity recorded from 62 EEG channels. The EEG signals were recorded as EPs elicited by painful electrical stimulations in the oesophagus with an intensity corresponding to the individual pain detection threshold. The EPs from all channels and subjects were decomposed simultaneously by a temporal matching pursuit (TMP) algorithm with Gabor atoms.
Results
Amplitude and phase features were classified by a support vector machine (SVM) to discriminate patients from healthy volunteers. A classification performance of 93.1% (P<0.001) was obtained when applying a majority voting scheme to the 3 best performing channels (FC4, C1, and C6) and including features from 2 atoms. The most discriminative features were determined by the slope coefficients from the SVM decision rule, which identified the biomarkers as delayed latency of the first atom (N2–P2 complex) and decreased amplitude of the second atom (NI–P1 complex).
Conclusion
The combination of TMP and SVM is a novel approach to classify two study populations, which may provide a new objective tool to identify biomarkers from various chronic pain populations.
TPS777 Background: Pancreatic ductal adenocarcinoma (PDAC) is 3% of cancers diagnosed in the United States and it is the fourth leading cause of cancer-related deaths. Hence, there is a considerable clinical need to develop innovative strategies for effective drug delivery and treatment. Sonoporation is a novel method that can enhance the therapeutic efficacy of co-administered chemotherapy by localized contrast-enhanced ultrasound imaging (CEUS) of gas-filled microbubbles (ultrasound contrast agent UCA), which temporarily changes tumor vascular microenvironment by increasing angiogenic vessel leakage through microstreaming, shockwaves and the activation of various intracellular signaling responses. Our Phase I clinical trial of sonoporation in 10 PDAC patients treated with Gemcitabine demonstrated no additional toxicity and an increase in median survival compared to 63 historical controls (8.9 vs 17.6 months; p = 0.011). Animal studies investigated 4 commercial UCAs under 2 different acoustic regimes and established the optimal UCA (Sonazoid, GE Healthcare, Oslo, Norway) as well as acoustic settings for sonoporation of PDAC. Methods: This Phase II clinical trial aims to improve standard of care (SoC) chemotherapy treatment by adding sonoporation (i.e., augmenting the SoC treatment with CEUS and microbubbles). Two sites (one in USA and one in Norway) will enroll 120 subjects with PDAC stage III or IIV prior to starting SoC chemotherapy. Exclusion criteria include known allergies to the UCA. The primary objective is to evaluate the safety and therapeutic efficacy of sonoporation on PDAC SoC treatment based on local progression-free and overall survival. Two groups: SoC chemotherapy or SoC chemotherapy followed by sonoporation. The optimal CEUS and microbubble conditions will be applied to a single PDAC tumor imaged by ultrasound. Treatment delivered day of SoC chemotherapeutic treatment for PDAC when the concentration of drugs is maximum. Gehan-Breslow-Wilcoxon test and Log-rank test will be used to compare survival. All clinical variables (e.g., concomitant imaging results, blood tests, etc.) will also be compared between groups with and without sonoporation. Clinical trial information: NCT04821284 .
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