COMPARING THE EFFICIENCY OF A REAL-TIME ARTIFICIAL INTELLIGENCE INSTRUCTOR TO HUMAN EXPERT INSTRUCTORS IN SIMULATED SURGICAL TECHNICAL SKILLS TRAINING– A RANDOMIZED CONTROLLED TRIAL

BTFC travel award recipient

Artificial intelligence systems provide risk-free training on realistically simulated patient cases and objective assessment of surgical technical skills. This randomized controlled study compared a real-time intelligent tutoring system in technical skills learning with human expert instructor-mediated training.

METHODS: Ninety-eight medical students performed six simulated brain tumor resections. Participants were randomly allocated into (1)no-real-time feedback, (2)real-time intelligent instruction, and (3)in- person human instruction. All students performed the first repetition without receiving feedback (baseline). Group-1 received visual feedback only after each procedure based on expert benchmarks. Group-2 was instructed by the intelligent system in real-time. After each task, the students were shown their error-video clips generated by this system alongside expert-level demonstrations on how to improve. Group-3 was instructed by human instructors during the tasks. After each task, instructors summarized the areas of improvement and demonstrated correction techniques. Participant performance was scored by the intelligent system and also by blinded experts using OSATS scores. The performance score was compared within groups and between groups to compare learning. RESULTS: Compared to baseline performance, Group-2 and Group-3 significantly improved in the performance score by the third and second repetition, respectively (p<0.01, p=0.01). The between-groups comparison demonstrated that Group-2 scored significantly higher than Group-3 in the fifth repetition (p<0.01). Group-2 achieved significantly higher OSATS scores than Group-1 in the sixth task. CONCLUSIONS: Artificial intelligence may facilitate trainee learning by providing equally or more efficient learning when compared to human instruction. These systems may aid in developing competency-based standardized curricula in surgical training.

Suicidal ideation and attempts in brain tumor patients and survivors: A systematic review

Background

Subsequent to a diagnosis of a brain tumor, psychological distress has been associated with negative effects on mental health as well as suicidality. The magnitude of such impact has been understudied in the literature. We conducted a systematic review to examine the impact of a brain tumor on suicidality (both ideation and attempts).

Methods

In accordance with the PRISMA guidelines, we searched for relevant peer-reviewed journal articles on PubMed, Scopus, and Web of Science databases from inception to October 20, 2022. Studies investigating suicide ideation and/or attempt among patients with brain tumors were included.

Results

Our search yielded 1,998 articles which were screened for eligibility. Seven studies consisting of 204,260 patients were included in the final review. Four studies comprising 203,906 patients (99.8%) reported elevated suicidal ideation and suicide attempt incidence compared with the general population. Prevalence of ideation and attempts ranged from 6.0% to 21.5% and 0.03% to 3.33%, respectively. Anxiety, depression, pain severity, physical impairment, glioblastoma diagnosis, male sex, and older age emerged as the primary risk factors associated with increased risk of suicidal ideation and attempts.

Conclusion

Suicidal ideation and attempts are increased in patients and survivors of brain tumors compared to the general population. Early identification of patients exhibiting these behaviors is crucial for providing timely psychiatric support in neuro-oncological settings to mitigate potential harm. Future research is required to understand pharmacological, neurobiological, and psychiatric mechanisms that predispose brain tumor patients to suicidality.

Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task

Virtual reality surgical simulators have facilitated surgical education by providing a safe training environment. Electroencephalography (EEG) has been employed to assess neuroelectric activity during surgical performance. Machine learning (ML) has been applied to analyze EEG data split into frequency bands. Although EEG is widely used in fields requiring expert performance, it has yet been used to classify surgical expertise. Thus, the goals of this study were to (a) develop an ML model to accurately differentiate skilled and less-skilled performance using EEG data recorded during a simulated surgery, (b) explore the relative importance of each EEG bandwidth to expertise, and (c) analyze differences in EEG band powers between skilled and less-skilled individuals. We hypothesized that EEG recordings during a virtual reality surgery task would accurately predict the expertise level of the participant. Twenty-one participants performed three simulated brain tumor resection procedures on the NeuroVR™ platform (CAE Healthcare, Montreal, Canada) while EEG data was recorded. Participants were divided into 2 groups. The skilled group was composed of five neurosurgeons and five senior neurosurgical residents (PGY4-6), and the less-skilled group was composed of six junior residents (PGY1-3) and five medical students. A total of 13 metrics from EEG frequency bands and ratios (e.g., alpha, theta/beta ratio) were generated. Seven ML model types were trained using EEG activity to differentiate between skilled and less-skilled groups. The artificial neural network achieved the highest testing accuracy of 100% (AUROC = 1.0). Model interpretation via Shapley analysis identified low alpha (8-10 Hz) as the most important metric for classifying expertise. Skilled surgeons displayed higher (p = 0.044) low-alpha than the less-skilled group. Furthermore, skilled surgeons displayed significantly lower TBR (p = 0.048) and significantly higher beta (13-30 Hz, p = 0.049), beta 1 (15-18 Hz, p = 0.014), and beta 2 (19-22 Hz, p = 0.015), thus establishing these metrics as important markers of expertise. ACGME CORE COMPETENCIES: Practice-Based Learning and Improvement.

Nondominant Hand Skills Spatial and Psychomotor Analysis During a Complex Virtual Reality Neurosurgical Task-A Case Series Study

BACKGROUND

Virtual reality surgical simulators provide detailed psychomotor performance data, allowing qualitative and quantitative assessment of hand function. The nondominant hand plays an essential role in neurosurgery in exposing the operative area, assisting the dominant hand to optimize task execution, and hemostasis. Outlining expert-level nondominant hand skills may be critical to understand surgical expertise and aid learner training.

OBJECTIVE

To (1) provide validity for the simulated bimanual subpial tumor resection task and (2) to use this simulation in qualitative and quantitative evaluation of nondominant hand skills for bipolar forceps utilization.

METHODS

In this case series study, 45 right-handed participants performed a simulated subpial tumor resection using simulated bipolar forceps in the nondominant hand for assisting the surgery and hemostasis. A 10-item questionnaire was used to assess task validity. The nondominant hand skills across 4 expertise levels (neurosurgeons, senior trainees, junior trainees, and medical students) were analyzed by 2 visual models and performance metrics.

RESULTS

Neurosurgeon median (range) overall satisfaction with the simulated scenario was 4.0/5.0 (2.0-5.0). The visual models demonstrated a decrease in high force application areas on pial surface with increased expertise level. Bipolar-pia mater interactions were more focused around the tumoral region for neurosurgeons and senior trainees. These groups spent more time using the bipolar while interacting with pia. All groups spent significantly higher time in the left upper pial quadrant than other quadrants.

CONCLUSION

This work introduces new approaches for the evaluation of nondominant hand skills which may help surgical trainees by providing both qualitative and quantitative feedback.

Machine Learning Identification of Surgical and Operative Factors Associated With Surgical Expertise in Virtual Reality Simulation

IMPORTANCE

Despite advances in the assessment of technical skills in surgery, a clear understanding of the composites of technical expertise is lacking. Surgical simulation allows for the quantitation of psychomotor skills, generating data sets that can be analyzed using machine learning algorithms.

OBJECTIVE

To identify surgical and operative factors selected by a machine learning algorithm to accurately classify participants by level of expertise in a virtual reality surgical procedure.

DESIGN, SETTING, AND PARTICIPANTS

Fifty participants from a single university were recruited between March 1, 2015, and May 31, 2016, to participate in a case series study at McGill University Neurosurgical Simulation and Artificial Intelligence Learning Centre. Data were collected at a single time point and no follow-up data were collected. Individuals were classified a priori as expert (neurosurgery staff), seniors (neurosurgical fellows and senior residents), juniors (neurosurgical junior residents), and medical students, all of whom participated in 250 simulated tumor resections.

EXPOSURES

All individuals participated in a virtual reality neurosurgical tumor resection scenario. Each scenario was repeated 5 times.

MAIN OUTCOMES AND MEASURES

Through an iterative process, performance metrics associated with instrument movement and force, resection of tissues, and bleeding generated from the raw simulator data output were selected by K-nearest neighbor, naive Bayes, discriminant analysis, and support vector machine algorithms to most accurately determine group membership.

RESULTS

A total of 50 individuals (9 women and 41 men; mean [SD] age, 33.6 [9.5] years; 14 neurosurgeons, 4 fellows, 10 senior residents, 10 junior residents, and 12 medical students) participated. Neurosurgeons were in practice between 1 and 25 years, with 9 (64%) involving a predominantly cranial practice. The K-nearest neighbor algorithm had an accuracy of 90% (45 of 50), the naive Bayes algorithm had an accuracy of 84% (42 of 50), the discriminant analysis algorithm had an accuracy of 78% (39 of 50), and the support vector machine algorithm had an accuracy of 76% (38 of 50). The K-nearest neighbor algorithm used 6 performance metrics to classify participants, the naive Bayes algorithm used 9 performance metrics, the discriminant analysis algorithm used 8 performance metrics, and the support vector machine algorithm used 8 performance metrics. Two neurosurgeons, 1 fellow or senior resident, 1 junior resident, and 1 medical student were misclassified.

CONCLUSIONS AND RELEVANCE

In a virtual reality neurosurgical tumor resection study, a machine learning algorithm successfully classified participants into 4 levels of expertise with 90% accuracy. These findings suggest that algorithms may be capable of classifying surgical expertise with greater granularity and precision than has been previously demonstrated in surgery.

Development of a performance model for virtual reality tumor resections

OBJECTIVE

Previous work from the authors has shown that hand ergonomics plays an important role in surgical psychomotor performance during virtual reality brain tumor resections. In the current study they propose a hypothetical model that integrates the human and task factors at play during simulated brain tumor resections to better understand the hand ergonomics needed for optimal safety and efficiency. They hypothesize that 1) experts (neurosurgeons), compared to novices (residents and medical students), spend a greater proportion of their time in direct contact with critical tumor areas; 2) hand ergonomic conditions (most favorable to unfavorable) prompt participants to adapt in order to optimize tumor resection; and 3) hand ergonomic adaptation is acquired with increasing expertise.

METHODS

In an earlier study, experts (neurosurgeons) and novices (residents and medical students) were instructed to resect simulated brain tumors on the NeuroVR (formerly NeuroTouch) virtual reality neurosurgical simulation platform. For the present study, the simulated tumors were divided into four quadrants (Q1 to Q4) to assess hand ergonomics at various levels of difficulty. The spatial distribution of time expended, force applied, and tumor volume removed was analyzed for each participant group (total of 22 participants).

RESULTS

Neurosurgeons spent a significantly greater percentage of their time in direct contact with critical tumor areas. Under the favorable hand ergonomic conditions of Q1 and Q3, neurosurgeons and senior residents spent significantly more time in Q1 than in Q3. Although forces applied in these quadrants were similar, neurosurgeons, having spent more time in Q1, removed significantly more tumor in Q1 than in Q3. In a comparison of the most favorable (Q2) to unfavorable (Q4) hand ergonomic conditions, neurosurgeons adapted the forces applied in each quadrant to resect similar tumor volumes. Differences between Q2 and Q4 were emphasized in measures of force applied per second, tumor volume removed per second, and tumor volume removed per unit of force applied. In contrast, the hand ergonomics of medical students did not vary across quadrants, indicating the existence of an “adaptive capacity” in neurosurgeons.

CONCLUSIONS

The study results confirm the experts’ (neurosurgeons) greater capacity to adapt their hand ergonomics during simulated neurosurgical tasks. The proposed hypothetical model integrates the study findings with various human and task factors that highlight the importance of learning in the acquisition of hand ergonomic adaptation.

A Comparison of Visual Rating Scales and Simulated Virtual Reality Metrics in Neurosurgical Training: A Generalizability Theory Study

BACKGROUND

Adequate assessment and feedback remains a cornerstone of psychomotor skills acquisition, particularly within neurosurgery where the consequence of adverse operative events is significant. However, a critical appraisal of the reliability of visual rating scales in neurosurgery is lacking. Therefore, we sought to design a study to compare visual rating scales with simulated metrics in a neurosurgical virtual reality task.

METHODS

Neurosurgical faculty rated anonymized participant video recordings of the removal of simulated brain tumors using a visual rating scale made up of seven composite elements. Scale reliability was evaluated using generalizability theory, and scale subcomponents were compared with simulated metrics using Pearson correlation analysis.

RESULTS

Four staff neurosurgeons evaluated 16 medical student neurosurgery applicants. Overall scale reliability and internal consistency were 0.73 and 0.90, respectively. Reliability of 0.71 was achieved with two raters. Individual participants, raters, and scale items accounted for 27%, 11%, and 0.6% of the data variability. The hemostasis scale component related to the greatest number of simulated metrics, whereas respect for no-go zones and tissue was correlated with none. Metrics relating to instrument force and patient safety (brain volume removed and blood loss) were captured by the fewest number of rating scale components.

CONCLUSIONS

To our knowledge, this is the first study comparing participant's ratings with simulated performance. Given rating scales capture less well instrument force, quantity of brain volume removed, and blood loss, we suggest adopting a hybrid educational approach using visual rating scales in an operative environment, supplemented by simulated sessions to uncover potentially problematic surgical technique.

Is Virtual Reality Surgical Performance Influenced by Force Feedback Device Utilized?

OBJECTIVE

The study objectives were to assess if surgical performance and subjective assessment of a virtual reality simulator platform was influenced by changing force feedback devices.

DESIGN

Participants used the NeuroVR (formerly NeuroTouch) simulator to perform 5 practice scenarios and a realistic scenario involving subpial resection of a virtual reality brain tumor with simulated bleeding. The influence of force feedback was assessed by utilizing the Omni and Entact haptic systems. Tier 1, tier 2, and tier 2 advanced metrics were used to compare results. Operator subjective assessment of the haptic systems tested utilized seven Likert criteria (score 1 to 5).

SETTING

The study is carried out at the McGill Neurosurgical Simulation Research and Training Centre, Montreal Neurological Institute and Hospital, Montreal, Canada.

PARTICIPANTS

Six expert operators in the utilization of the NeuroVR simulator platform.

RESULTS

No significant differences in surgical performance were found between the two haptic devices. Participants significantly preferred the Entact system on all 7 Likert criteria of subjective assessment.

CONCLUSIONS

Our results show no statistical differences in virtual reality surgical performance utilizing the two bimanual haptic devices tested. Subjective assessments demonstrated that participants preferred the Entact system. Our results suggest that to maximize realism of the training experience educators employing virtual reality simulators may find it useful to assess expert opinion before choosing a force feedback device.

Learning brain aneurysm microsurgical skills in a human placenta model: predictive validity

OBJECTIVE

Surgery for brain aneurysms is technically demanding. In recent years, the process to learn the technical skills necessary for these challenging procedures has been affected by a decrease in the number of surgical cases available and progressive restrictions on resident training hours. To overcome these limitations, surgical simulators such as cadaver heads and human placenta models have been developed. However, the effectiveness of these models in improving technical skills is unknown. This study assessed concurrent and predictive validity of brain aneurysm surgery simulation in a human placenta model compared with a “live” human brain cadaveric model.

METHODS

Two human cadaver heads and 30 human placentas were used. Twelve neurosurgeons participated in the concurrent validity part of this study, each operating on 1 human cadaver head aneurysm model and 1 human placenta model. Simulators were evaluated regarding their ability to simulate different surgical steps encountered during real surgery. The time to complete the entire aneurysm task in each simulator was analyzed. The predictive validity component of the study involved 9 neurosurgical residents divided into 3 groups to perform simulation exercises, each lasting 6 weeks. The training for the 3 groups consisted of educational video only (3 residents), human cadaver only (3 residents), and human placenta only (3 residents). All residents had equivalent microsurgical experience with superficial brain tumor surgery. After completing their practice training, residents in each of the 3 simulation groups performed surgery for an unruptured middle cerebral artery (MCA) aneurysm, and their performance was assessed by an experienced vascular neurosurgeon who watched the operative videos.

RESULTS

All human cadaver heads and human placentas were suitable to simulate brain aneurysm surgery. In the concurrent validity portion of the experiment, the placenta model required a longer time (p < 0.001) than cadavers to complete the task. The placenta model was considered more effective than the cadaver model in simulating sylvian fissure splitting, bipolar coagulation of oozing microvessels, and aneurysm neck and dome dissection. Both models were equally effective in simulating neck aneurysm clipping, while the cadaver model was considered superior for simulation of intraoperative rupture and for reproduction of real anatomy during simulation. In the predictive validity portion of the experiment, residents were evaluated for 4 tasks: sylvian fissure dissection, microvessel bipolar coagulation, aneurysm dissection, and aneurysm clipping. Residents trained in the human placenta simulator consistently had the highest overall performance scores when compared with those who had trained in the cadaver model and those who had simply watched operative videos (p < 0.001).

CONCLUSIONS

The human placenta biological simulator provides excellent simulation for some critical tasks of aneurysm surgery such as splitting of the sylvian fissure, dissection of the aneurysm neck and dome, and bipolar coagulation of surrounding microvessels. When performing surgery for an unruptured MCA aneurysm, residents who had trained in the human placenta model performed better than residents trained with other simulation scenarios/models. In this age of reduced exposure to aneurysm surgery and restrictions on resident working hours, the placenta model is a valid simulation for microneurosurgery with striking similarities with real surgery.

Automaticity of Force Application During Simulated Brain Tumor Resection: Testing the Fitts and Posner Model

OBJECTIVE

The Fitts and Posner model of motor learning hypothesized that with deliberate practice, learners progress through stages to an autonomous phase of motor ability. To test this model, we assessed the automaticity of neurosurgeons, senior residents, and junior residents when operating on 2 identical tumors using the NeuroVR virtual reality simulation platform.

DESIGN

Participants resected 9 identical simulated tumors on 2 occasions (total = 18 resections). These resections were separated by the removal of a variable number of tumors with different visual and haptic complexities to mirror neurosurgical practice. Consistency of force application was used as a metric to assess automaticity and was defined as applying forces 1 standard deviation above or below a specific mean force application. Amount and specific location of force application during second identical tumor resection was compared to that used for the initial tumor.

SETTING

This study was conducted at the McGill Neurosurgical Simulation Research and Training Center, Montreal Neurologic Institute and Hospital, Montreal, Canada.

PARTICIPANTS

Nine neurosurgeons, 10 senior residents, and 8 junior residents.

RESULTS

Neurosurgeons display statistically significant increased consistency of force application when compared to resident groups when results from all tumor resections were assessed. Assessing individual tumor types demonstrates significant differences between the neurosurgeon and resident groups when resecting hard stiffness similar-to-background (white) tumors and medium-stiffness tumors. No statistical difference in consistency of force application was found when junior and senior residents were compared.

CONCLUSION

"Experts" display significantly more automaticity when operating on identical simulated tumors separated by a series of different tumors using the NeuroVR platform. These results support the Fitts and Posner model of motor learning and are consistent with the concept that automaticity improves after completing residency training. The potential educational application of our findings is outlined related to neurosurgical resident training.

Face, content, and construct validity of human placenta as a haptic training tool in neurointerventional surgery

OBJECT

The development of neurointerventional treatments of central nervous system disorders has resulted in the need for adequate training environments for novice interventionalists. Virtual simulators offer anatomical definition but lack adequate tactile feedback. Animal models, which provide more lifelike training, require an appropriate infrastructure base. The authors describe a training model for neurointerventional procedures using the human placenta (HP), which affords haptic training with significantly fewer resource requirements, and discuss its validation.

METHODS

Twelve HPs were prepared for simulated endovascular procedures. Training exercises performed by interventional neuroradiologists and novice fellows were placental angiography, stent placement, aneurysm coiling, and intravascular liquid embolic agent injection.

RESULTS

The endovascular training exercises proposed can be easily reproduced in the HP. Face, content, and construct validity were assessed by 6 neurointerventional radiologists and 6 novice fellows in interventional radiology.

CONCLUSIONS

The use of HP provides an inexpensive training model for the training of neurointerventionalists. Preliminary validation results show that this simulation model has face and content validity and has demonstrated construct validity for the interventions assessed in this study.

Face, Content, and Construct Validity of Brain Tumor Microsurgery Simulation Using a Human Placenta Model

BACKGROUND

Brain tumors are complex 3-dimensional lesions. Their resection involves training and the use of the multiple microsurgical techniques available for removal. Simulation models, with haptic and visual realism, may be useful for improving the bimanual technical skills of neurosurgical residents and neurosurgeons, potentially decreasing surgical errors and thus improving patient outcomes.

OBJECTIVE

To describe and assess an ex vivo placental model for brain tumor microsurgery using a simulation tool in neurosurgical psychomotor teaching and assessment.

METHODS

Sixteen human placentas were used in this research project. Intravascular blood remnants were removed by continuous saline solution irrigation of the 2 placental arteries and placental vein. Brain tumors were simulated using silicone injections in the placental stroma. Eight neurosurgeons and 8 neurosurgical residents carried out the resection of simulated tumors using the same surgical instruments and bimanual microsurgical techniques used to perform human brain tumor operations. Face and content validity was assessed using a subjective evaluation based on a 5-point Likert scale. Construct validity was assessed by analyzing the surgical performance of the neurosurgeon and resident groups.

RESULTS

The placenta model simulated brain tumor surgical procedures with high fidelity. Results showed face and content validity. Construct validity was demonstrated by statistically different surgical performances among the evaluated groups.

CONCLUSION

Human placentas are useful haptic models to simulate brain tumor microsurgical removal. Results using this model demonstrate face, content, and construct validity.

Development of the McGill simulator for endoscopic sinus surgery: a new high-fidelity virtual reality simulator for endoscopic sinus surgery

BACKGROUND

The technical challenges of endoscopic sinus surgery (ESS) and the high risk of complications support the development of alternative modalities to train residents in these procedures. Virtual reality simulation is becoming a useful tool for training the skills necessary for minimally invasive surgery; however, there are currently no ESS virtual reality simulators available with valid evidence supporting their use in resident education. Our aim was to develop a new rhinology simulator, as well as to define potential performance metrics for trainee assessment.

METHODS

The McGill simulator for endoscopic sinus surgery (MSESS), a new sinus surgery virtual reality simulator with haptic feedback, was developed (a collaboration between the McGill University Department of Otolaryngology-Head and Neck Surgery, the Montreal Neurologic Institute Simulation Lab, and the National Research Council of Canada). A panel of experts in education, performance assessment, rhinology, and skull base surgery convened to identify core technical abilities that would need to be taught by the simulator, as well as performance metrics to be developed and captured.

RESULTS

The MSESS allows the user to perform basic sinus surgery skills, such as an ethmoidectomy and sphenoidotomy, through the use of endoscopic tools in a virtual nasal model. The performance metrics were developed by an expert panel and include measurements of safety, quality, and efficiency of the procedure.

CONCLUSION

The MSESS incorporates novel technological advancements to create a realistic platform for trainees. To our knowledge, this is the first simulator to combine novel tools such as the endonasal wash and elaborate anatomic deformity with advanced performance metrics for ESS.

Abstract B24: Detection of O6- and N7-methylguanine adducts by LC/MS in brain tumor tissues obtained from patients treated with temozolomide

The current standard of care for glioblastoma includes surgery, radiotherapy and chemotherapeutic agents such as temozolomide (TMZ), a DNA methylating compound. The cytotoxic effects of TMZ have been linked to guanine methylation at the N7 and O6 positions. These adducts are not currently used as markers of TMZ efficacy.

Using liquid chromatography/mass spectrometry (LC/MS), we have established a sensitive analytical assay to directly detect both N7- and O6-methylguanine adducts from DNA following TMZ treatment. A limit of detection below 1 fmol was observed for O6-methylguanine, while N7-methylguanine was observed below 5 fmol. O6- and N7-methylguanine were successfully detected by LC/MS in tumour and normal brain tissue samples from patients treated with a neoadjuvant TMZ regimen for 14 days (75 mg/m2). Variations in levels of both methylated guanines were detected between patients as well as within different locations of the same tumour sample. This technique provides a direct detection of the damage inflicted by TMZ. This could potentially indicate the efficacy of the drug, allowing for prompt analysis and response. It also holds potential for determining efficacy of treatment dose, schedule and possible concomitant drugs.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr B24.

Low-grade oligodendroglioma: an indolent but incurable disease? Clinical article

OBJECT

The authors reviewed their institutional experience with pure low-grade oligodendroglioma (LGO), correlating outcomes with several variables of possible prognostic values.

METHODS

Sixty-nine patients with WHO-classified LGOs were treated between 1992 and 2006 at the McGill University Health Center. Clinical, pathological, and radiological records were carefully reviewed. Demographic characteristics; the nature and duration of presenting symptoms; baseline neurological function; extent of resection; Karnofsky Performance Scale score; preoperative radiological findings including tumor size, location, and absence/presence of enhancement; and pathological data including chromosome arms 1p/19q codeletion and O-methylguanine-DNA methyltransferase promoter gene methylation status were all compiled. The timing and dose of radio- and/or chemotherapy, date of tumor progression, pathological finding at disease progression, treatment at time of disease progression, and status at the last follow-up were also recorded.

RESULTS

The median follow-up period was 6.1 years (range 1.3-16.3 years). The majority (78%) of patients presented with seizures; contrast enhancement was initially seen in 16 patients (25%). All patients had undergone an initial surgical procedure: gross-total resection in 27%, partial resection in 59%, and biopsy only in the remaining 13%. Fifteen patients received adjuvant radiotherapy. Data on O-methylguanine-DNA methyltransferase promoter gene methylation status was available in 47 patients (68%) and in all but 1 patient for 1p/19q status. Survival at 5, 10, and 15 years was 83, 63, and 29%, respectively. Multivariate analysis showed that seizures at presentation and the absence of contrast enhancement were the only independent favorable prognostic factors for survival. The 5-, 10-, and 15-year progression-free survival rates were 46, 7.7, and 0%, respectively.

CONCLUSIONS

This retrospective review confirms the indolent but progressively fatal nature of LGOs. Contrast enhancement was the most evident single prognostic factor. New treatment strategies are clearly needed in the management of this disease.

Preoperative functional magnetic resonance imaging assessment of higher-order cognitive function in patients undergoing surgery for brain tumors

OBJECT

Resection of brain tumors has been shown to increase patient survival. The extent of the possible resection, however, depends on whether the tumor has invaded brain regions important for motor, sensory, or cognitive processes and whether the brain tissue surrounding the tumor maintains its functional role. The goal of the present study was to develop new pre- and intraoperative tools to specifically assess the function of the rostral part of the dorsal premotor cortex (PMdr) in 4 patients with brain tumors close to this region.

METHODS

Using functional magnetic resonance (fMR) imaging and a task developed to assess accurate selection between competing responses based on conditional rules, the authors preoperatively assessed the function of the PMdr in 4 patients with brain tumors close to this region. In 1 patient, the authors developed an intraoperative procedure to assess performance on the task during the tumor resection.

RESULTS

Preoperative fMR imaging data showed specific activity increases in the vicinity of the tumors, that is, in the PMdr. As confirmed by postoperative structural MR imaging, the extent of the tumor resection was optimal and the functional region within the PMdr was preserved. Furthermore, patients exhibited no postoperative deficits during task performance, demonstrating that the function was preserved. Intraoperative behavioral results demonstrated that the cognitive processes underlying performance on the task remained intact throughout the tumor resection.

CONCLUSIONS

These findings suggest that preoperative fMR imaging, together with intraoperative behavioral evaluation, may be a useful paradigm to assist neurosurgeons in preserving cognitive function in patients with brain tumors.

Frequent expression loss of Inter-alpha-trypsin inhibitor heavy chain (ITIH) genes in multiple human solid tumors: a systematic expression analysis

Background

The inter-alpha-trypsin inhibitors (ITI) are a family of plasma protease inhibitors, assembled from a light chain – bikunin, encoded by AMBP – and five homologous heavy chains (encoded by ITIH1, ITIH2, ITIH3, ITIH4, and ITIH5), contributing to extracellular matrix stability by covalent linkage to hyaluronan. So far, ITIH molecules have been shown to play a particularly important role in inflammation and carcinogenesis.

Methods

We systematically investigated differential gene expression of the ITIH gene family, as well as AMBP and the interacting partner TNFAIP6 in 13 different human tumor entities (of breast, endometrium, ovary, cervix, stomach, small intestine, colon, rectum, lung, thyroid, prostate, kidney, and pancreas) using cDNA dot blot analysis (Cancer Profiling Array, CPA), semiquantitative RT-PCR and immunohistochemistry.

Results

We found that ITIH genes are clearly downregulated in multiple human solid tumors, including breast, colon and lung cancer. Thus, ITIH genes may represent a family of putative tumor suppressor genes that should be analyzed in greater detail in the future. For an initial detailed analysis we chose ITIH2 expression in human breast cancer. Loss of ITIH2 expression in 70% of cases (n = 50, CPA) could be confirmed by real-time PCR in an additional set of breast cancers (n = 36). Next we studied ITIH2 expression on the protein level by analyzing a comprehensive tissue micro array including 185 invasive breast cancer specimens. We found a strong correlation (p < 0.001) between ITIH2 expression and estrogen receptor (ER) expression indicating that ER may be involved in the regulation of this ECM molecule.

Conclusion

Altogether, this is the first systematic analysis on the differential expression of ITIH genes in human cancer, showing frequent downregulation that may be associated with initiation and/or progression of these malignancies.

Randomized, double-blind, placebo-controlled trial of marimastat in glioblastoma multiforme patients following surgery and irradiation

PURPOSE

Because raised matrix metalloprotease (MMP) levels are associated with glioma invasion and angiogenesis, we tested the efficacy of marimastat (MT) an orally active drug that can reduce MMP levels, in patients with gliomas.

PATIENTS AND METHODS

A total of 162 patients with intracranial glioblastoma multiforme or gliosarcomas who had undergone surgery and radiotherapy participated in this multicenter, double-blind, placebo-controlled, parallel group study conducted at 20 institutions. Seventy-nine patients (57 male, 22 female, median age 58 years) were randomized to receive placebo (PB), and 83 patients (51 male, 32 female, median age 57 years) were randomized to receive MT, 10 mg orally twice daily, until tumor progression.

RESULTS

This intention-to-treat efficacy analysis showed no statistically significant difference between MT and PB groups with respect to survival (P = 0.38, log rank test). The median survival time from protocol initiation was 37.9 weeks for the PB group and 42.9 weeks for the MT group, with a hazard ratio of 1.16 (95% CI 0.83 to 1.60). There were no statistically significant differences in quality of life between the PB and MT groups, as assessed by the FACT-BR questionnaire. Musculoskeletal toxicities led to dose modification or withdrawal in 20% of MT-treated and 1.2% of PB-treated patients.

CONCLUSION

MT does not improve survival in patients with glioblastoma or gliosarcoma following surgery and radiotherapy. Therefore, single-agent MT appears unwarranted; however, MT in combination with cytotoxic chemotherapy may be warranted, as suggested by observations in our study and other studies.

Hydrocephalus and Hirschsprung's disease with a mutation of L1CAM

Abnormalities of the L1CAM gene, a member of the immunoglobulin gene superfamily of neural-cell adhesion molecules, are associated with X-linked hydrocephalus and some allelic disorders. Hirschsprung's disease (HSCR) is characterized by the absence of ganglion cells and the presence of hypertrophic nerve trunks in the distal bowel. There have been three reports of patients with X-linked hydrocephalus and HSCR with a mutation in the L1CAM gene. We report three more patients with similar conditions. We suspect that decreased L1CAM may be a modifying factor in the development of HSCR.

Dynamics of C6 astrocytoma invasion into three-dimensional collagen gels

OBJECTIVE

The dynamic mechanisms underlying the three-dimensional invasive paradigm of C6 astrocytoma cells has been assessed.

METHODS

Spheroids of C6 astrocytoma cells were implanted into three-dimensional collagen type I gels (vitrogen 100) and individual C6 astrocytoma cell invasion monitored. Time-lapsed videomicroscopy was used to assess the dynamic components of cell invasion in three dimensions while scanning and transmission electron microscopy were used to assess matrix architecture and the static aspects of cell invasion.

RESULTS

Videomicroscopy outlined an invasion paradigm continuum with repeating phases. A cell surface ruffling phase was followed by invadopodia extension and pull up phases. For some cells the collagen type I matrix extracellular matrix appeared to modify the ability of C6 cells to carry out their invasion paradigm.

CONCLUSIONS

C6 astrocytoma cells invading a three-dimensional collagen type I matrix utilize a invasion paradigm made up of a number of phases. A better understanding of the dynamic invasion paradigms of malignant glial cells may be useful in the development of effective treatment strategies to prevent or modify malignant glioma invasion.