Dataset Information

Electrical noise in the intraoperative magnetic resonance imaging setting.

ABSTRACT: Intraoperative magnetic resonance imaging (iMRI) is a tool now commonly used in neurosurgery. Safe and reliable patient care in this (or any other) operating room setting depends on an environment, where electrical noise (EN) does not interfere with the operation of the electronic monitoring or imaging equipment. In this investigation, we evaluated the EN generated by the iMRI system and the anesthesia patient monitor used at this institution that impacts the performance of these two devices.We measured the EN generated by our iMRI-compatible anesthesia patient monitor as detected by the EN analysis algorithm in our iMRI system. We measured the EN generated by our iMRI system during scanning as detected in the electrocardiogram (ECG) waveform of our patient monitor. We analyzed the effects on EN reduction and signal quality of the ECG noise filters provided in our iMRI-compatible anesthesia patient monitor.Our patient monitor generated EN that was detectable by the iMRI EN analysis algorithm; however, this interference was within the iMRI manufacturer's acceptable limits for an iMRI scan (<10% more than background system-level noise). In the clinical case analyzed, the iMRI generated a narrow-band low-frequency (20 Hz) relatively high-energy EN that interfered with the ECG signal of our patient monitor during an iMRI scan. This EN was correlated with the acoustic noise from the iMRI system during the scan and was associated with the radio frequency (RF) and magnetic gradient pulsations of the iMRI system. The integrity of the ECG waveform was nearly entirely lost during a scan. The filters of the ECG monitor diminished but did not entirely eliminate this 20 Hz interference. We found that the filters alter the morphology of the ECG signal, which may make it difficult to identify clinically relevant ECG changes.The EN generated by our anesthesia patient monitor is within acceptable limits for the iMRI system. The iMRI generates EN which renders the ECG unreadable in the most commonly used filter mode. The monitor's filters diminish this noise but also alter the morphology of the ECG waveform. The anesthesiologist must be cognizant of these technical compromises and recognize that adjusting the ECG filters on the monitor is required to obtain a useful ECG signal for patient monitoring during the iMRI scan but that the diagnostic value of the ECG will be reduced.

SUBMITTER: Dzwonczyk R

PROVIDER: S-EPMC5166575 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Electrical noise in the intraoperative magnetic resonance imaging setting.

Dzwonczyk Roger R Fujii Jeffrey T JT Simonetti Orlando O Nieves-Ramos Ricardo R Bergese Sergio D SD

Anesthesia and analgesia 20090101 1

<h4>Background</h4>Intraoperative magnetic resonance imaging (iMRI) is a tool now commonly used in neurosurgery. Safe and reliable patient care in this (or any other) operating room setting depends on an environment, where electrical noise (EN) does not interfere with the operation of the electronic monitoring or imaging equipment. In this investigation, we evaluated the EN generated by the iMRI system and the anesthesia patient monitor used at this institution that impacts the performance of th ...[more]

PMID: 19095847

Similar Datasets

Project description:BackgroundMagnetic resonance imaging (MRI)-based rotator cuff assessment is often qualitative and subjective; few studies have tried to validate such preoperative assessments. This study investigates relationships of preoperative MRI assessments made by conventional approaches to intraoperative findings of tear type, location, and size or MRI-assessed muscle occupation ratio.MethodsIntraoperatively, surgeons assessed tear type, location, anterior-posterior (AP) width, and medial-lateral length in 102 rotator cuff repair patients. Two musculoskeletal radiologists independently assessed the preoperative MRI scans for these same parameters and supraspinatus muscle atrophy by both Warner classification and quantitative occupation ratio. Exact agreement proportions, kappa statistics, and correlation coefficients were used to quantify agreement relationships.ResultsAgreement between MRI readers' and surgeons' observations of tear status averaged 93% with κ = 0.38, and that of tear location averaged 77% with κ = 0.50. Concordance correlations of MRI and intraoperative measures of anterior-posterior and medial-lateral tear length averaged 0.59 and 0.56 across readers, respectively. Despite excellent interrater agreement on Warner classification (exact agreement proportion 0.91) and occupation ratio (concordance correlation 0.93) separately, correlations between these 2 measures were -0.54 and -0.64 for the 2 readers, respectively. Patients with Warner grade 0 had occupation ratios ranging from 0.5 to 1.5.ConclusionCorrelations of preoperative MRI tear dimensions and muscle atrophy assessed by conventional approaches with intraoperatively measured tear dimensions and quantitative occupation ratio, respectively, were only fair. Since tear size and muscle atrophy are known strong predictors of outcomes following rotator cuff repair that may influence treatment decisions, surgeons need to be aware of the limitations of MRI methods. Continued development and validation of quantitative preoperative imaging methods to accurately assess these parameters are needed to improve surgical planning and prognosis.

Project description:OBJECT:Glioblastoma is a highly malignant brain tumor, for which standard treatment consists of surgery, radiotherapy, and chemotherapy. Increasing extent of tumor resection (EOTR) is associated with prolonged survival. Intraoperative magnetic resonance imaging (iMRI) is used to increase EOTR, based on contrast enhanced MR images. The correlation between intraoperative contrast enhancement and tumor has not been studied systematically. METHODS:For this prospective cohort study, we recruited 10 patients with a supratentorial brain tumor suspect for a glioblastoma. After initial resection, a 0.15 Tesla iMRI scan was made and neuronavigation-guided biopsies were taken from the border of the resection cavity. Scores for gadolinium-based contrast enhancement on iMRI and for tissue characteristics in histological slides of the biopsies were used to calculate correlations (expressed in Kendall's tau). RESULTS:A total of 39 biopsy samples was available for further analysis. Contrast enhancement was significantly correlated with World Health Organization (WHO) grade (tau 0.50), vascular changes (tau 0.53), necrosis (tau 0.49), and increased cellularity (tau 0.26). Specificity of enhancement patterns scored as "thick linear" and "tumor-like" for detection of (high grade) tumor was 1, but decreased to circa 0.75 if "thin linear" enhancement was included. Sensitivity for both enhancement patterns varied around 0.39-0.48 and 0.61-0.70, respectively. CONCLUSIONS:Presence of intraoperative contrast enhancement is a good predictor for presence of tumor, but absence of contrast enhancement is a bad predictor for absence of tumor. The use of gadolinium-based contrast enhancement on iMRI to maximize glioblastoma resection should be evaluated against other methods to increase resection, like new contrast agents, other imaging modalities, and "functional neurooncology" - an approach to achieve surgical resection guided by functional rather than oncological-anatomical boundaries.

Project description:There has been increasing experience in the utilization of intraoperative magnetic resonance imaging (iMRI) for intracranial surgery. Despite this trend, only a few U.S centers have examined the use of this technology for transsphenoidal resection of tumors of the sella. We present the largest series in North America examining the role of iMRI for pituitary adenoma resection. We retrospectively reviewed our institutional experience of 59-patients who underwent transsphenoidal procedures for sellar and suprasellar tumors with iMRI guidance. Of these, 52 patients had a histological diagnosis of pituitary adenoma. The technical results of this subgroup were examined. A 1.5-T iMRI was integrated with the BrainLAB (Feldkirchen, Germany) neuronavigation system. The majority (94%) of tumors in our series were macroadenomas. Seventeen percent of tumors were confined to the sella, 49% had suprasellar extensions without involvement of the cavernous sinus, 34% had frank cavernous sinus invasion. All patients underwent at least one iMRI, and 19% required one or more additional sets of intraoperative imaging. In 58% of patients, iMRI led to the surgeon attempting more resection. A gross total resection was obtained in 67% of the patients with planned total resections. There was one case of permanent postoperative diabetes insipidus and no other instances of new hormone replacement. In summary, iMRI was most useful for tumors of the sella with and without suprasellar extension where the information from the iMRI extended the complete resection rate from 40 to 72% and 55 to 88%, respectively. As one would expect, it did not substantially increase the rate of resection of tumors with cavernous sinus invasion. Overall, iMRI was particularly useful in guiding resection safely, aiding in clinical decision making, and allowing identification and preservation of the pituitary stalk and normal pituitary gland. Limitations of the iMRI include a need for additional personnel and training as well as additional operative time, which diminishes over time as personnel learn to optimize workflow efficiency. Additional costs are mitigated in part by using the iMRI as an immediate postoperative scan. Other data emerging from our experience suggest that preservation of normal gland and thus avoidance of hypopituitarism may be improved by iMRI use, but longer follow-up periods are required to test this conclusion. iMRI can detect unsuspected complications sooner than routine postoperative imaging, potentially leading to improved outcomes. However, larger studies are needed.

Dataset Information

Electrical noise in the intraoperative magnetic resonance imaging setting.

Publications

Electrical noise in the intraoperative magnetic resonance imaging setting.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets