Clinical applications of 3D printing in colorectal surgery: A systematic review.

BACKGROUND: The utilization of three-dimensional printing has grown rapidly within the field of surgery over recent years. Within the subspecialty of colorectal surgery, the technology has been used to create personalized anatomical models for preoperative planning, models for surgical training, and occasionally customized implantable devices and surgical instruments. We aim to provide a systematic review of the current literature discussing clinical applications of three-dimensional printing in colorectal surgery. METHODS: Full-text studies published in English which described the application of 3D printing in pre-surgical planning, advanced surgical planning, and patient education within the field of colorectal surgery were included. Exclusion criteria were duplicate articles, review papers, studies exclusively dealing with surgical training and/or education, studies which used only virtual models, and studies which described colorectal cancer only as it pertained to other organs. RESULTS: Eighteen studies were included in this review. There were two randomized controlled trials, one retrospective outcomes study, five case reports/series, one animal model, and nine technical notes/feasibility studies. There were three studies on advanced surgical planning/device manufacturing, six on pre-surgical planning, two on pelvic anatomy modeling, eight on various types of anatomy modeling, and one on patient education. CONCLUSIONS: While more studies with a higher level of evidence are needed, the findings of this review suggest many promising applications of three-dimensional printing within the field of colorectal surgery with the potential to improve patient outcomes and experiences.

Utilizing connectome fingerprinting functional MRI models for motor activity prediction in presurgical planning: A feasibility study.

Presurgical planning prior to brain tumor resection is critical for the preservation of neurologic function post-operatively. Neurosurgeons increasingly use advanced brain mapping techniques pre- and intra-operatively to delineate brain regions which are "eloquent" and should be spared during resection. Functional MRI (fMRI) has emerged as a commonly used non-invasive modality for individual patient mapping of critical cortical regions such as motor, language, and visual cortices. To map motor function, patients are scanned using fMRI while they perform various motor tasks to identify brain networks critical for motor performance, but it may be difficult for some patients to perform tasks in the scanner due to pre-existing deficits. Connectome fingerprinting (CF) is a machine-learning approach that learns associations between resting-state functional networks of a brain region and the activations in the region for specific tasks; once a CF model is constructed, individualized predictions of task activation can be generated from resting-state data. Here we utilized CF to train models on high-quality data from 208 subjects in the Human Connectome Project (HCP) and used this to predict task activations in our cohort of healthy control subjects (n = 15) and presurgical patients (n = 16) using resting-state fMRI (rs-fMRI) data. The prediction quality was validated with task fMRI data in the healthy controls and patients. We found that the task predictions for motor areas are on par with actual task activations in most healthy subjects (model accuracy around 90%-100% of task stability) and some patients suggesting the CF models can be reliably substituted where task data is either not possible to collect or hard for subjects to perform. We were also able to make robust predictions in cases in which there were no task-related activations elicited. The findings demonstrate the utility of the CF approach for predicting activations in out-of-sample subjects, across sites and scanners, and in patient populations. This work supports the feasibility of the application of CF models to presurgical planning, while also revealing challenges to be addressed in future developments. PRACTITIONER POINTS: Precision motor network prediction using connectome fingerprinting. Carefully trained models' performance limited by stability of task-fMRI data. Successful cross-scanner predictions and motor network mapping in patients with tumor.

Verbal memory network mapping in individual patients predicts postoperative functional impairments.

Verbal memory decline is a significant concern following temporal lobe surgeries in patients with epilepsy, emphasizing the need for precision presurgical verbal memory mapping to optimize functional outcomes. However, the inter-individual variability in functional networks and brain function-structural dissociations pose challenges when relying solely on group-level atlases or anatomical landmarks for surgical guidance. Here, we aimed to develop and validate a personalized functional mapping technique for verbal memory using precision resting-state functional MRI (rs-fMRI) and neurosurgery. A total of 38 patients with refractory epilepsy scheduled for surgical interventions were enrolled and 28 patients were analyzed in the study. Baseline 30-min rs-fMRI scanning, verbal memory and language assessments were collected for each patient before surgery. Personalized verbal memory networks (PVMN) were delineated based on preoperative rs-fMRI data for each patient. The accuracy of PVMN was assessed by comparing post-operative functional impairments and the overlapping extent between PVMN and surgical lesions. A total of 14 out of 28 patients experienced clinically meaningful declines in verbal memory after surgery. The personalized network and the group-level atlas exhibited 100% and 75.0% accuracy in predicting postoperative verbal memory declines, respectively. Moreover, six patients with extra-temporal lesions that overlapped with PVMN showed selective impairments in verbal memory. Furthermore, the lesioned ratio of the personalized network rather than the group-level atlas was significantly correlated with postoperative declines in verbal memory (personalized networks: r = -0.39, p = .038; group-level atlas: r = -0.19, p = .332). In conclusion, our personalized functional mapping technique, using precision rs-fMRI, offers valuable insights into individual variability in the verbal memory network and holds promise in precision verbal memory network mapping in individuals.

Comparative validation of automated presurgical tractography based on constrained spherical deconvolution and diffusion tensor imaging with direct electrical stimulation.

OBJECTIVES: Accurate presurgical brain mapping enables preoperative risk assessment and intraoperative guidance. This cross-sectional study investigated whether constrained spherical deconvolution (CSD) methods were more accurate than diffusion tensor imaging (DTI)-based methods for presurgical white matter mapping using intraoperative direct electrical stimulation (DES) as the ground truth. METHODS: Five different tractography methods were compared (three DTI-based and two CSD-based) in 22 preoperative neurosurgical patients undergoing surgery with DES mapping. The corticospinal tract (CST, N = 20) and arcuate fasciculus (AF, N = 7) bundles were reconstructed, then minimum distances between tractograms and DES coordinates were compared between tractography methods. Receiver-operating characteristic (ROC) curves were used for both bundles. For the CST, binary agreement, linear modeling, and posthoc testing were used to compare tractography methods while correcting for relative lesion and bundle volumes. RESULTS: Distance measures between 154 positive (functional response, pDES) and negative (no response, nDES) coordinates, and 134 tractograms resulted in 860 data points. Higher agreement was found between pDES coordinates and CSD-based compared to DTI-based tractograms. ROC curves showed overall higher sensitivity at shorter distance cutoffs for CSD (8.5 mm) compared to DTI (14.5 mm). CSD-based CST tractograms showed significantly higher agreement with pDES, which was confirmed by linear modeling and posthoc tests (PFWE < .05). CONCLUSIONS: CSD-based CST tractograms were more accurate than DTI-based ones when validated using DES-based assessment of motor and sensory function. This demonstrates the potential benefits of structural mapping using CSD in clinical practice.

Case Report: Use of novel AR registration system for presurgical planning during vestibular schwannoma resection surgery.

Background and importance: Vestibular schwannomas are benign tumors and are the most common tumor found in the cerebellopontine angle. Surgical management of these lesions involves consideration of various operative approaches, which can have profound effects on procedural course and patient outcomes. Therefore, a comprehensive understanding of the location of the tumor and surrounding anatomical structures is vital for a positive outcome. We present a case of a 47-year-old female patient with vestibular schwannoma. A novel mixed reality (MR) system was used to register patient-specific 3D models onto the patient's head for operative planning and anatomical visualization. Case description: A 47-year-old female presented with a history of left-sided hearing loss, tinnitus, and episodic left facial tingling. Magnetic Resonance Imaging (MRI) demonstrated a 3.3 cm enhancing lesion in the left cerebellopontine angle at the with mass effect on the brachium pontis and medulla. Surgical resection was performed via retrosigmoid craniotomy. Conclusions: In this study, we report the use of Augmented Reality (AR) visualization for planning of vestibular schwannoma resection. This technology allows for efficient and accurate registration of a patient's 3D anatomical model onto their head while positioned in the operating room. This system is a powerful tool for operative planning as it allows the surgeon to visualize critical anatomical structures where they lie on the patient's head. The present case demonstrates the value and use of AR for operative planning of complex cranial lesions.

Tailored Concept for Accurate Neuroendoscopy: A Comparative Retrospective Single-Center Study on Image-Guided Neuroendoscopic Procedures.

OBJECTIVE: Precise planning and execution is key for neuroendoscopic interventions, which can be based on different available aiding technologies. The aim of this retrospective study is to report a case-based use of guided neuroendoscopy and to develop a stratification algorithm for the available technologies. METHODS: We reviewed consecutive neuroendoscopic cases performed at our center from 2016 to 2018. We distinguished between patients receiving a new burr hole (group A) and those with a preexisting burr hole (group B). Case-specific technical requirements for procedure planning and execution, complication rate, surgical outcome, and possible subsequent surgery were evaluated. From this experience, a stratification system was developed to tailor the available guiding technologies. RESULTS: A total of 309 neuroendoscopic interventions in 243 patients were included in the present study. The cases included hydrocephalic (81.6%) and nonhydrocephalic (18.4%) conditions. The interventions were supported by coordinate-based (group A, n = 49; group B, n = 67), guide-based (group A, n = 42; group B, n = 0), ultrasound-guided (group A, n = 50; group B, n = 7), or navigated augmented reality-guided (group A, n = 85; group B, n = 9) techniques. The overall complication rate was 4.5%. Stratified by the surgical indication, fontanel status, entry point localization, presence of a preexisting burr hole, ventricular size, and number of targets, an approach toward image-guided neuroendoscopy is suggested. CONCLUSIONS: Planning and technical guidance is essential in neuroendoscopic procedures. The stratified decision-making algorithm for different available technologies aims to achieve lower cost and time consumption, which was found to be safe and efficient. Further investigations are warranted to deliver solid data on procedure efficiency.

iEEG-recon: A fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices.

OBJECTIVE: Clinicians use intracranial electroencephalography (iEEG) in conjunction with noninvasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms. METHODS: We created iEEG-recon, a scalable electrode reconstruction pipeline for semiautomatic iEEG annotation, rapid image registration, and electrode assignment on brain magnetic resonance imaging (MRI). Its modular architecture includes a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts. RESULTS: We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography and stereoelectroencephalography cases with a 30-min running time per case (including semiautomatic electrode labeling and reconstruction). iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and postimplant T1-MRI visual inspections. We also found that our use of ANTsPyNet deep learning-based brain segmentation for electrode classification was consistent with the widely used FreeSurfer segmentations. SIGNIFICANCE: iEEG-recon is a robust pipeline for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting fast data analysis and integration into clinical workflows. iEEG-recon's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide.

Accuracy of ZedView, the Software for Three-Dimensional Measurement and Preoperative Planning: A Basic Study.

Background and Objectives: In the field of orthopedic surgery, novel techniques of three-dimensional shape modeling using two-dimensional tomographic images are used for bone-shape measurements, preoperative planning in joint-replacement surgery, and postoperative evaluation. ZedView® (three-dimensional measurement instrument and preoperative-planning software) had previously been developed. Our group is also using ZedView® for preoperative planning and postoperative evaluation for more accurate implant placement and osteotomy. This study aimed to evaluate the measurement error in this software in comparison to a three-dimensional measuring instrument (3DMI) using human bones. Materials and Methods: The study was conducted using three bones from cadavers: the pelvic bone, femur, and tibia. Three markers were attached to each bone. Study 1: The bones with markers were fixed on the 3DMI. For each bone, the coordinates of the center point of the markers were measured, and the distances and angles between these three points were calculated and defined as "true values." Study 2: The posterior surface of the femur was placed face down on the 3DMI, and the distances from the table to the center of each marker were measured and defined as "true values." In each study, the same bone was imaged using computed tomography, measured with this software, and the measurement error from the corresponding "true values" was calculated. Results: Study 1: The mean diameter of the same marker using the 3DMI was 23.951 ± 0.055 mm. Comparisons between measurements using the 3DMI and this software revealed that the mean error in length was <0.3 mm, and the error in angle was <0.25°. Study 2: In the bones adjusted to the retrocondylar plane with the 3DMI and this software, the average error in the distance from the planes to each marker was 0.43 (0.32-0.58) mm. Conclusion: This surgical planning software could measure the distance and angle between the centers of the markers with high accuracy; therefore, this is very useful for pre- and postoperative evaluation.

Dural Tail Sign and Middle Meningeal Artery Hypertrophy in Glioblastoma: A Rarity?

BACKGROUND: Dural tail sign and increased caliber of branches of the external carotid artery (ECA) are common findings in meningioma and they have been rarely reported in intra-axial lesions. Anyway, some cases of glioblastoma (GBM) are reported in the literature, mostly superficially localized, characterized by these 2 findings and therefore, misdiagnosed with meningioma. The aim of this study is to verify the prevalence of dural tail sign and hypertrophy of middle meningeal artery (MMA) in a large cohort of GBMs. METHODS: 180 GBM patients were retrospectively evaluated. Deep or superficial localization of GBM was established and the presence of dural tail sign and hypertrophy of the ipsilateral MMA were assessed. The rate of tumor necrosis and the incidence of dural metastases during the radiological follow-up were also evaluated. Inter-rater reliability was calculated using Cohen's K-test. RESULTS: Dural tail sign and enlarged MMA were evident in 30% and 19% of 96 superficial GBM, respectively. Deep GBM did not present those signs. Only one patient developed dural metastasis at follow-up and no differences in terms of tumor necrosis and hypoxic biomarkers expression were evident among GBMs with and without dural and vessel signs. CONCLUSIONS: Dural tail sign and hypertrophy of the MMA in superficial GBM are more common than expected. They probably represent reactive rather than a neoplastic infiltration. Knowing these radiological signs may be important in terms of neurosurgery planning and avoiding excessive bleeding. Anyway, this hypothesis should be confirmed by a prospective neurosurgery studio.

Augmented Reality in Otology/Neurotology: A Scoping Review with Implications for Practice and Education.

OBJECTIVE: To determine how augmented reality (AR) has been applied to the field of otology/neurotology, examine trends and gaps in research, and provide an assessment of the future potential of this technology within surgical practice and education. DATA SOURCES: PubMed, EMBASE, and Cochrane Library were assessed from their inceptions through October 2022. A manual bibliography search was also conducted. REVIEW METHODS: A scoping review was conducted and reported according to PRISMA-ScR guidelines. Data from studies describing the application of AR to the field of otology/neurotology were evaluated, according to a priori inclusion/exclusion criteria. Exclusion criteria included non-English language articles, abstracts, letters/commentaries, conference papers, and review articles. RESULTS: Eighteen articles covering a diverse range of AR platforms were included. Publication dates spanned from 2007 to 2022 and the rate of publication increased over this time. Six of 18 studies were case series in human patients although the remaining were proof of concepts in cadaveric/artificial/animal models. The most common application of AR was for surgical navigation (14 of 18 studies). Computed tomography was the most common source of input data. Few studies noted potential applications to surgical training. CONCLUSION: Interest in the application of AR to otology/neurotology is growing based on the number of recent publications that use a broad range of hardware, software, and AR platforms. Large gaps in research such as the need for submillimeter registration error must be addressed prior to adoption in the operating room and for educational purposes. LEVEL OF EVIDENCE: N/A Laryngoscope, 133:1786-1795, 2023.

Tentorial Notch Meningiomas: Innovative Preoperative Management and Literature Review.

Background: Tentorial meningiomas account for only 3-6% of all intracranial meningiomas. Among them, tentorial incisura (notch) location must be considered as a subgroup with specific surgical anatomy and indications, morbidity, and mortality. In this study, we propose an update on preoperative management in order to reduce postoperative deficits. Methods: We retrospectively collected adult patients treated for incisural meningioma between January 1992 and December 2016 in two different neurosurgical departments. Demographic, clinical, and neuroradiological preoperative and postoperative data were analyzed. In the most recent subgroup of tumors, a preoperative digital simulation was performed to define a volumetric digital quantification of the tumor resection. A review of the pertinent literature has been also done. Results: We included 26 patients. The median age was 58.4 years. Onset neurological signs were cranial nerve deficit in 9 patients, hemiparesis in 7, gait disturbance in 3, and intracranial hypertension in 3 patients. Simpson grade I removal was achieved in 12 patients, II in 10, III in 3, and IV in 1 patient. An overall rate of 23% postoperative complications was observed. The average follow-up duration was 68.5 months. Residual tumor was reported in 8 patients. Five patients underwent gamma knife radiosurgery. In 34.6% of patients, the surgical approach was chosen with preoperative digital planning estimating the potential volume of postoperative residual tumor, the target for radiosurgical treatment. Conclusions: A multidisciplinary approach to plan incisural meningiomas management is important. To lower postoperative morbidity and mortality, a careful preoperative case analysis is useful. A planned residual tumor, supported by preoperative simulation imaging, could be safely treated with radiosurgery.

Computer-Assisted Frontofacial Monobloc Advancement and Facial Bipartition for Pfeiffer Syndrome: Surgical Technique.

BACKGROUND: In patients with Pfeiffer syndrome, several corrections are required to correct facial retrusion, maxillary deficiency, or even hypertelorism. The frontofacial monobloc advancement (FFMA) and the facial bipartition (FB) are the gold standard surgeries. We present the correction of this deformity using a simultaneous computer-assisted FFMA and FB. METHODS: The 3-dimensional surgical planning defined the virtual correction and bone-cutting guide in view of the FFMA and FB. Coronal and intraoral approaches were combined to perform the osteotomies. Four internal distractors were also placed for the postoperative distraction osteogenesis. RESULTS: We reported 2 cases of computer-assisted surgery with satisfying outcomes. The sagittal deficiency (fronto-facial retrusion) was corrected by FFMA and the transversal abnormality (i.e., hypertelorism and maxillary deficiency) by the FB, then followed by an internal distraction osteogenesis. CONCLUSIONS: Computer-assisted surgery is helpful and a reliable option for the management of complex faciocraniosynostosis such as hypertelorism and frontofacial retrusion.

Task-based and Resting State Functional MRI in Children.

Functional MR imaging (MRI) is a valuable tool for presurgical planning and is well established in adult patients. The use of task-based fMRI is increasing in pediatric populations because it provides similar benefits for pre-surgical planning in children. This article reviews special adaptations that are required for successful applications of task-based fMRI in children, especially in the motor and language systems. The more recently introduced method of resting state fMRI is reviewed and its relative advantages and disadvantages discussed. Common pitfalls and other systems and networks that may be of interest in special circumstances also are reviewed.

3D Printed Patient-Specific Complex Hip Arthroplasty Models Streamline the Preoperative Surgical Workflow: A Pilot Study.

Introduction: Surgical planning for complex total hip arthroplasty (THA) often presents a challenge. Definitive plans can be difficult to decide upon, requiring unnecessary equipment to be ordered and a long theatre list booked. We present a pilot study utilising patient-specific 3D printed models as a method of streamlining the pre-operative planning process. Methods: Complex patients presenting for THA were referred to the research team. Patient-specific 3D models were created from routine Computed Tomography (CT) imaging. Simulated surgery was performed to guide prosthesis selection, sizing and the surgical plan. Results: Seven patients were referred for this pilot study, presenting with complex conditions with atypical anatomy. Surgical plans provided by the 3D models were more detailed and accurate when compared to 2D CT and X ray imaging. Streamlined equipment selection was of great benefit, with augments avoided post simulation in three cases. The ability to tackle complex surgical problems outside of the operating theatre also flagged potential complications, while also providing teaching opportunities in a low risk environment. Conclusion: This study demonstrated that 3D printed models can improve the surgical plan and streamline operative logistics. Further studies investigating the optimal 3D printing material and workflow, along with cost-benefit analyses are required before this process is ready for routine use.

Comparison of compressional and elastic wave simulations for patient-specific planning prior to transcranial photoacoustic-guided neurosurgery.

SIGNIFICANCE: Simulations have the potential to be a powerful tool when planning the placement of photoacoustic imaging system components for surgical guidance. While elastic simulations (which include both compressional and shear waves) are expected to more accurately represent the physical transcranial acoustic wave propagation process, these simulations are more time-consuming and memory-intensive than the compressional-wave-only simulations that our group previously used to identify optimal acoustic windows for transcranial photoacoustic imaging. AIM: We present qualitative and quantitative comparisons of compressional and elastic wave simulations to determine which option is more suitable for preoperative surgical planning. APPROACH: Compressional and elastic photoacoustic k-Wave simulations were performed based on a computed tomography volume of a human cadaver head. Photoacoustic sources were placed in the locations of the internal carotid arteries and likely positions of neurosurgical instrument tips. Transducers received signals from three previously identified optimal acoustic windows (i.e., the ocular, nasal, and temporal regions). Target detectability, image-based target size estimates, and target-to-instrument distances were measured using the generalized contrast-to-noise ratio (gCNR), resolution, and relative source distances, respectively, for each simulation method. RESULTS: The gCNR was equivalent between compressional and elastic simulations. The areas of the -6 dB contours of point spread functions utilized to measure resolution differed by 0.33 to 3.35 mm2. Target-to-instrument distance measurements were within 1.24 mm of the true distances. CONCLUSIONS: These results indicate that it is likely sufficient to utilize the less time-consuming, less memory-intensive compressional wave simulations for presurgical planning.

Patient-specific Virtual Temporal Bone Simulation Based on Clinical Cone-beam Computed Tomography.

OBJECTIVES: Patient-specific surgical simulation allows presurgical planning through three-dimensional (3D) visualization and virtual rehearsal. Virtual reality simulation for otologic surgery can be based on high-resolution cone-beam computed tomography (CBCT). This study aimed to evaluate clinicians' experience with patient-specific simulation of mastoid surgery. METHODS: Prospective, multi-institutional study. Preoperative temporal bone CBCT scans of patients undergoing cochlear implantation (CI) were retrospectively obtained. Automated processing and segmentation routines were used. Otologic surgeons performed a complete mastoidectomy with facial recess approach on the patient-specific virtual cases in the institution's temporal bone simulator. Participants completed surveys regarding the perceived accuracy and utility of the simulation. RESULTS: Twenty-two clinical CBCTs were obtained. Four attending otologic surgeons and 5 otolaryngology trainees enrolled in the study. The mean number of simulations completed by each participant was 16.5 (range 3-22). "Overall experience" and "usefulness for presurgical planning" were rated as "good," "very good," or "excellent" in 84.6% and 71.6% of the simulations, respectively. In 10.7% of simulations, the surgeon reported to have gained a significantly greater understanding of the patient's anatomy compared to standard imaging. Participants were able to better appreciate subtle anatomic findings after using the simulator for 60.4% of cases. Variable CBCT acquisition quality was the most reported limitation. CONCLUSION: Patient-specific simulation using preoperative CBCT is feasible and may provide valuable insights prior to otologic surgery. Establishing a CBCT acquisition protocol that allows for consistent segmentation will be essential for reliable surgical simulation. LEVEL OF EVIDENCE: 3 Laryngoscope, 131:1855-1862, 2021.

Presurgical brain mapping of the language network in pediatric patients with epilepsy using resting-state fMRI.

OBJECTIVE: Epilepsy affects neural processing and often causes intra- or interhemispheric language reorganization, rendering localization solely based on anatomical landmarks (e.g., Broca's area) unreliable. Preoperative brain mapping is necessary to weigh the risk of resection with the risk of postoperative deficit. However, the use of conventional mapping methods (e.g., somatosensory stimulation, task-based functional MRI [fMRI]) in pediatric patients is technically difficult due to low compliance and their unique neurophysiology. Resting-state fMRI (rs-fMRI), a "task-free" technique based on the neural activity of the brain at rest, has the potential to overcome these limitations. The authors hypothesized that language networks can be identified from rs-fMRI by applying functional connectivity analyses. METHODS: Cases in which both task-based fMRI and rs-fMRI were acquired as part of the preoperative clinical protocol for epilepsy surgery were reviewed. Task-based fMRI consisted of 2 language tasks and 1 motor task. Resting-state fMRI data were acquired while the patients watched an animated movie and were analyzed using independent component analysis (i.e., data-driven method). The authors extracted language networks from rs-fMRI data by performing a similarity analysis with functionally defined language network templates via a template-matching procedure. The Dice coefficient was used to quantify the overlap. RESULTS: Thirteen children underwent conventional task-based fMRI (e.g., verb generation, object naming), rs-fMRI, and structural imaging at 1.5T. The language components with the highest overlap with the language templates were identified for each patient. Language lateralization results from task-based fMRI and rs-fMRI mapping were comparable, with good concordance in most cases. Resting-state fMRI-derived language maps indicated that language was on the left in 4 patients (31%), on the right in 5 patients (38%), and bilateral in 4 patients (31%). In some cases, rs-fMRI indicated a more extensive language representation. CONCLUSIONS: Resting-state fMRI-derived language network data were identified at the patient level using a template-matching method. More than half of the patients in this study presented with atypical language lateralization, emphasizing the need for mapping. Overall, these data suggest that this technique may be used to preoperatively identify language networks in pediatric patients. It may also optimize presurgical planning of electrode placement and thereby guide the surgeon's approach to the epileptogenic zone.

Reflectance confocal microscopy: Principles, basic terminology, clinical indications, limitations, and practical considerations.

Reflectance confocal microscopy (RCM) is a noninvasive imaging tool used for in vivo visualization of the skin. It has been extensively studied for use in the evaluation of equivocal cutaneous neoplasms to decrease the number of biopsy procedures in patients with benign lesions. Furthermore, its applications are broadening to include presurgical cancer margin mapping, tumor recurrence surveillance, monitoring of ablative and noninvasive therapies, and stratification of inflammatory disorders. With the approval of category I Current Procedural Terminology reimbursement codes for RCM image acquisition and interpretation, use of this technology has been increasingly adopted by dermatologists. The first article in this 2-part continuing medical education series highlights basic terminology, principles, clinical applications, limitations, and practical considerations in the clinical use of RCM technology.

Advancing Imaging to Enhance Surgery: From Image to Information Guidance.

Conventional magnetic resonance imaging (cMRI) has an established role as a crucial disease parameter in the multidisciplinary management of glioblastoma, guiding diagnosis, treatment planning, assessment, and follow-up. Yet, cMRI cannot provide adequate information regarding tissue heterogeneity and the infiltrative extent beyond the contrast enhancement. Advanced magnetic resonance imaging and PET and newer analytical methods are transforming images into data (radiomics) and providing noninvasive biomarkers of molecular features (radiogenomics), conveying enhanced information for improving decision making in surgery. This review analyzes the shift from image guidance to information guidance that is relevant for the surgical treatment of glioblastoma.

Resting State Functional MR Imaging of Language Function.

Resting state functional MR imaging methods can provide localization of the language system; however, presurgical functional localization of the language system with task-based functional MR imaging is the current standard of care before resection of brain tumors. These methods provide similar results and comparing them could be helpful for presurgical planning. We combine information from 3 data resources to provide quantitative information on the components of the language system. Tables and figures compare anatomic information, localization information from resting state fMR imaging, and activation patterns in different components of the language system expected from commonly used task fMR imaging experiments.