Intraoperative magnetic resonance imaging and magnetic resonance imaging–guided therapy for brain tumors

Neuroimag Clin N Am 12 (2002) 665 – 683

Intraoperative magnetic resonance imaging and magnetic resonance imaging–guided therapy for brain tumors Ferenc A. Jolesz, MD *, Ion-Florin Talos, MD, Richard B. Schwartz, MD, PhD, Hatsuho Mamata, MD, PhD, Daniel F. Kacher, MS, Kullervo Hynynen, PhD, Nathan McDannold, PhD, Pairash Saivironporn, PhD, Lei Zao, MD Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA

The aim of brain tumor surgery is to target, access, and remove intracranial lesions without damaging normal functioning brain tissue, thus preserving essential neurological function. To achieve this goal, the surgeon must exhibit complete mastery of structural and functional anatomy — a prerequisite to achieving maximal lesion removal while avoiding postoperative neurologic deficits. Even under the most ideal circumstances, this information is difficult to obtain intraoperatively. Indeed, distinguishing infiltrating tumors from the surrounding normal brain tissue (based solely on the visual appearance of the lesion) is an especially challenging task. Complete resection of infiltrating gliomas is almost impossible to accomplish because of the difficulty in recognizing tumor margins. Of all the contributions of image guidance, perhaps none is more significant than improved definition of tumor margins, better localization of lesions, and optimization of surgical strategies. Computerassisted, image-guided techniques now play an important role in neurosurgery and allow brain tumor surgery to be performed using minimally invasive procedures and with improved precision. Imageguided neurosurgical techniques are routinely practiced today, and as these methods have evolved during the past decade, they have generated major advances in the surgical treatment of brain tumors.

* Corresponding author. E-mail address: [email protected] (F.A. Jolesz).

Along with an exponential increase in the use of computerized, intraoperative navigational tools, the role of computer-based neurosurgical planning has likewise expanded. This form of surgical planning allows production of three-dimensional (3D) models that integrate data from multiple imaging modalities, each highlighting one or more aspects of morphology or function. These multimodality, fusion-based 3D models are then used for optimizing trajectory and simulating surgical procedures. The use of these preoperatively generated models for surgical navigation is limited, however, if they cannot be displayed in the coordinate system of the patient. At the outset of any given procedure, surgical manipulations and maneuvers produce changes in the anatomic position of brain structures and intracerebral tumors. For example, the initial loss of cerebrospinal fluid (CSF) after a craniotomy as well as retraction and resection of tissue play a role in intraoperative brain shift. Hence, localization and targeting of brain tumors on the basis of preoperatively acquired images is unreliable. Brain deformations and shifts become even more unpredictable as the procedure continues. Intraoperative imaging provides a means of offsetting these variables and allows the surgeon to now rely upon true, updated anatomical information. Intraoperative imaging, in fact, has become the essential tool by which the position of continuously deforming brain tissue is updated and through which the interactivity required for image-based surgical guidance is achieved. Interactive, intraoperative image guidance allows the surgeon to accurately

1052-5149/02/$ – see front matter D 2002, Elsevier Science (USA). All rights reserved. PII: S 1 0 5 2 - 5 1 4 9 ( 0 2 ) 0 0 0 3 6 - 9

666

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

localize and target during neurosurgery and to optimize surgical approaches, thereby avoiding critical structures and surrounding normal tissues. Using intraoperative imaging, neurosurgeons can ‘‘see’’ beyond the exposed surfaces, and in so doing, overcome the inherent limits of conventional visualization. In addition, using various intraoperative imaging methods such as ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), it is possible to distinguish tumor from normal tissue. In this respect, intraoperative imaging systems provide greater sensitivity than direct visualization does. Among the potential intraoperative imaging methods, MRI offers the best tissue characterization, which is essential in defining tumor boundaries. Intraoperative MRI improves not only surgical localization and targeting but also intraoperative navigation by using interactive multiplanar imaging. Moreover, it can monitor and detect changes in tissue integrity (ie, breakdown of the blood-brain barrier, brain swelling, bleeding, ischemia) during surgical procedures. Interactive MRI guidance offers neurosurgeons several advantages over previous intraoperative guidance systems. For example, intraoperative imaging and navigation can be fully integrated with various MRI scan configurations, dynamic MRI methods, surgical tools, robotic devices, and thermal ablation systems such as MRI-guided focused ultrasound.

emission computed tomography (SPECT), allowing further differentiation of brain tissue and improved characterization of brain lesions. The ultimate goal of intraoperative image guidance is to combine preoperative and intraoperative image data in such a way that the surgeon uses the most comprehensive information in surgical decision-making. The surgeon can also use special features unique to MRI that enhance the information available during a procedure, effectively guiding therapy with greater precision. These features include flow sensitivity, evaluation of perfusion, administration of gadolinium to detect a breakdown of the blood-brain barrier, or communication between CSF compartments. In addition, MRI’s ability to detect temperature changes can be exploited to monitor and control thermal ablations. In our intraoperative MRI system, images can be obtained at each stage of a procedure without moving the patient and without significantly lengthening the operating room time. There are several advantages to this: namely, a lesion can be accurately and directly localized. Changes in the anatomy caused by brain shifting can also be appreciated in real time. The correlation between the surgeon’s field of view and the image allows confirmation of the exact location of pathologic tissue. Finally, equipped with serial images, the surgeon can evaluate the extent of excision and completely remove the tumor, if possible.

Tumor localization by intraoperative MRI

Localization of tumor margins

The aim of surgical treatment of primary, intracranial neoplasms is to achieve complete resection, which requires precise localization with accurate definition of tumor margins and the surrounding normal brain. Limitations in spatial and contrast resolution make this task challenging. Fortunately, MRI has greatly enhanced our ability to obtain comprehensive lesion characterization with multiple sequences and imaging methods. Other imaging modalities can also supplement information furnished by intraoperative MRI in a meaningful way. In addition to intraoperatively obtained MRI, all available and relevant preoperative data [eg, preoperative MRI, functional MRI (fMRI), and diffusion tensor imaging (DTI)] should play a role in localization. This information, taken as whole, significantly improves our ability to localize and target the lesion within the cortical gray matter and along deep white matter structures. The surgeon can also obtain critical physiologic and/or metabolic data from contrast-enhanced dynamic MRI, magnetic resonance spectroscopy, positron emission tomography, and single photon

MRI is the most effective means of evaluating the extent of low-grade gliomas including astrocytomas, oligodendrogliomas, and oligoastrocytomas. We are convinced, moreover, that resections of low-grade gliomas performed under MR guidance provide the best opportunity for maximal tumor resection. Low-grade gliomas are of low T1 and high T2 signal on MRI, have well-defined margins, mild mass effect, and demonstrate no enhancement or hemorrhage (Fig. 1). There is usually little, if any, surrounding edema. It is particularly difficult for the neurosurgeon to distinguish these tumors intraoperatively from normal brain using either visual or tactile cues. As a result, neurosurgeons tend to be conservative, deliberately performing incomplete tumor resections, especially when they present in the vicinity of eloquent cortex. Many studies [1,2], however, have shown that the survival of patients with lowgrade gliomas is strongly correlated with the extent of tumor resection. Nonsurgical therapies such as chemotherapy and radiotherapy have not proven effective in controlling these tumors, and if they are

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

Fig. 1. Left frontal low-grade glioma (axial T2-weighted FSE).

not removed, they tend to undergo anaplastic transformation (ie, develop into higher grades). Unlike low-grade gliomas, high-grade gliomas (anaplastic astrocytomas and glioblastomas) cannot be treated solely by extirpation. Further complicating matters, the margins of these high-grade tumors may be impossible to accurately delineate with MRI. Moreover, these tumors tend to enhance rather heterogeneously, suggesting the recruitment of abnormal vessels with endothelial proliferation (ie, angiogenesis resulting in neovascularity). Tissue formation of this nature does not typically possess an effective blood-brain barrier, which is a diagnostically useful characteristic generally pointing to the presence of tumor. Tumor cells tend to advance beyond the enhancing margin, however, and although this may be associated with peritumoral edema, it is usually difficult, if not impossible, to determine whether the edema is reactive or whether the edematous tissue contains malignant tumor cells. Moreover, thin-section pathologic analysis has shown that individual tumor cells may extend even beyond the edema margins into apparently normal tissue. Hence, as a rule, treatment of high-grade astrocytomas consists of tumor debulking and high-dose radiation brachytherapy that is delivered to the margins of the tumor to control cellular growth. Interstitial radiotherapy is then delivered in staggered doses to disrupt protein synthesis in tumor cells. Within the radiation field, other pathophysiologic changes also occur (albeit poorly understood) that result in gliosis and necrosis of normal tissue. Kumar et al [3] have noted several likely effects including vascular injury (endothelial damage, vascular ectasia, and telangiectasia), which results in increased vascular permeability and attendant vasogenic edema, vessel wall hyalinization,

667

thrombosis, small infarctions, and cytotoxic edema. Oligodendrocytes are also very sensitive to radiation damage, resulting in demyelination. Other possible causes for radiation-induced brain damage include cytotokine release, which may stimulate the formation of leaky capillaries; fibrinolytic enzyme disturbances, which may contribute to tissue necrosis; and autoimmune vasculitis, which may result in small vessel thrombosis and small infarcts. The end result of radiation-induced damage is fibrinoid necrosis with surrounding coagulative necrosis and demyelination that may develop months to years after radiotherapy and may be progressive and irreversible. Radiographically speaking, this phenomenon manifests itself as zones of necrosis surrounded by enhancing margins and extensive edema. The MR characteristics of radiation change, therefore, are frequently indistinguishable from residual or recurrent tumor using conventional imaging techniques.

Dynamic imaging to localize tumor recurrence Because the abnormal vessels recruited by highgrade glial neoplasms (ie, tumor neovascularity) are inherently highly permeable, the rate and degree of enhancement should be demonstrably greater at the site of tumor recurrence than in areas associated with radiation necrosis, which results from damage to existing vessels. We have used dynamic MRI as a means of intraoperatively distinguishing patterns of enhancement within the treated tumor bed [4]. In this technique, a spoiled gradient echo (SPGR) sequence (two-dimensional (2D) fast spoiled gradient (FSPGR), with echo time (TE) minimum, 45° flip angle, 1 number of excitation (NEX), sequential, multiphase, interleaved, variable bandwidth, and extended dynamic range, 10 phases/location; 22 cm field of vision (FOV); 256128; 1.87 seconds per image) is performed sequentially while gadolinium is infused intravenously. This technique produces a series of images depicting regional rates of enhancement through the tumor volume. We reported a series of 24 patients who underwent dynamic MR imaging while in the intraoperative magnet [4]. Using this technique, we were able to distinguish patients with recurrent tumor from those without tumor recurrence with an accuracy of more than 90%. We also plotted the signal intensity through the region of greatest enhancement for each patient and found that in patients with tumor recurrence, the signal intensity at first pass through active tumor had increased approximately 50% over baseline. In those patients without evidence of recurrent

668

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

tumor, however, the maximal signal intensity change at first pass was only approximately 15% above baseline. These data suggest that dynamic MR imaging can establish at once whether active tumor is likely present within a treated tumor bed and direct the surgeon to these sites; we now routinely use it for these purposes.

Diffusion tensor imaging for surgical planning Information about the course of white matter fiber tracts adjacent to intracerebral tumors is very important for planning brain tumor resection. Diffusion tensor imaging (DTI) in particular can add important information about the proximity of tumors to critical white matter fiber tracts, thereby enhancing localization. Precise knowledge of white matter fiber tract locations as well as their topographic relationship with the lesion is not only essential to accurate surgical planning, but also to understanding and predicting neurological function both before and after surgery. White matter fiber tracts can be depicted by displaying the eigenvectors of the diffusion tensor [5] or by colorcoding the directional information [6]. With such information overlaid on anatomical images, white matter fiber displacements such as shift, disruption, and widening by edema or infiltration of tumor can be observed readily [7,8]. Fig. 2 shows an example of a white matter fiber map. Lines on the map indicate in-plane directional fibers and dots indicate the presence of a throughplane component. Eigenvectors are displayed voxel by voxel. Fiber directions that run with an angle to the plane are displayed by a dot with a line. In Fig. 2, the left posterior limb of the internal capsule is shifted posteriorly by the tumor and peritumoral edema extends between the fibers of the anterior limb of the internal capsule. The fibers of the anterior limb seem to be intact although a slight widening of the tract is evident. However, it is important to note the difficulty of identifying a tract in a two-dimensional plane even if multiple planes are scanned (Fig. 3). We have recently introduced a technique whereby eigenvectors are tracked in three dimensions [9]. Unlike the task of detecting white matter fiber tracts within a two-dimensional plane, the 3D approach enables more precise track identification and produces more reliable anatomic information, which in turn contributes to more accurate surgical planning. By registering multiple image data sets, such as functional MRI, diffusionweighted tensor images, and structural images including contrast-enhanced images in three dimensions, and by rendering all information onto a 3D brain model,

Fig. 2. Colon carcinoma metastasis; axial section through internal capsule. (Blue lines) In-plane directional fibers. (Blue dots)Through-plane directional fibers. Posterior limb of the right internal capsule ( yellow dots) is shifted in a posterior direction by the tumor. Edema extends into fibers of the internal capsule.

the surgeon can interpret the overall view of tumor and white matter fiber relationship with relative ease.

The use of fMRI for surgical planning fMRI provides information about cortical function by noninvasive means. Such functional information is of paramount value for surgical planning in lesions located in or around eloquent cortex. The interpretation of fMRI data is based on statistical analysis of the temporal variations in voxel intensity distribution. The functional maps are obtained by displaying the distribution of the voxels activated by various physiological tasks (ie, motor, sensory, and visual tasks). Although fMRI data do not alter the diagnosis, they can substantially contribute to surgical planning by providing critical information about optimal positioning of craniotomy and corticotomy sites, surgical excision margins, and access routes to the lesions. fMRI-based surgical planning also yields various potential strategies that enable the surgeon to avoid targeting the lesion too close to eloquent cortex or to other essential structures [78 – 80]. The relationship between intra-axial infiltrative brain tumors, such as low- and high-grade glial neoplasms, and functionally active neural tissue has not been elucidated entirely [10]. A recent magneto-ence-

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

669

shape, which inevitably occurs during any neurosurgical procedure. Intraoperative fMRI acquisitions are not practical in low- and mid-field intraoperative (iMRI) systems. The high-field systems, however, do not suffer from this limitation [14]. Fig. 4 shows the case of a 31-year-old, left-handed woman harboring a right posterior temporal T2 hyperintense mass lesion suspicious for low-grade glioma. The preoperative fMRI located Wernicke’s area in the right hemisphere, data that proved useful in guiding intraoperative electrical mapping, which in turn confirmed the fMRI findings.

Intraoperative detection of complications

Fig. 3. Glioblastoma multiforme. (A) Tumor is located in the splenium of the corpus callosum and disrupts the crossing fibers. Tumor is shown as a high signal lesion on T2-weighted background image. (B) Fig. 2b shows the tracking of the eigenvector (light green). Starting points were located within normal fiber tracts, and corpus callosum fibers were tracked toward the lesion. The fibers were disrupted and could not be tracked further at the tumor area. Infiltration of the tumor is suspected between the fibers (arrow).

phalography – based study [11] demonstrated the presence of functionally active tissue within the tumor as defined by MRI in 18% of grade 2, 17% of grade 3, and 8% of grade 4 tumors. Thus, obtaining functional information well in advance of the surgical procedure is critical in defining the safest surgical strategy. Moreover, the incorporation of preoperative fMRI information into frameless, stereotactic systems is becoming routine at some institutions [12,13,78 – 80]. In our experience, preoperative fMRI data has proven very useful in guiding electrophysiological cortical mapping. Furthermore, such information may be crucial to stereotactic biopsies, where cortical stimulation is not practicable because of the small skull opening. The intraoperative use of fMRI data, however, is limited by the changes in the brain’s

One of the great advantages of performing surgery within the intraoperative MR system is the ability of the operator to evaluate for intraoperative or perioperative hemorrhage. To this end, we routinely use a ‘‘heme-susceptibility sequence’’ that consists of a series of gradient echo images with a repetition time (TR) of 600 ms, a 30° flip angle, 1 NEX, and TE of 9, 20, 40, and 60 ms. These images are acquired as two sets of double echoes: one with TE of 9 and 40 ms, and the other with TE of 20 and 60 ms. We have found that gradient echo sequences with long TE (ie, 40 to 60 ms) show dark signal (‘‘blooming’’) due to hyperacute blood collections, which is not evident on conventional imaging sequences or on shorter gradient echo (GRE) sequences. This most likely reflects the greater sensitivity of the long TE GRE sequence to the presence of small amounts of deoxyhemoglobin that develop in the periphery of a hyperacute blood collection (Fig. 5). Atlas and Thulborn [15] have suggested that the low partial pressure of dissolved oxygen in the brain, when compressed by the hematoma, leads to deoxygenation of the blood at the hematoma-brain interface. Hence, deoxyhemoglobin can be visualized only on long TE GRE image, and the attendant conspicuity of blood is directly correlated with increasing TE. It is important, however, to compare these images with conventional sequences to differentiate acute blood from postoperative air collections, which are visible as signal voids on all imaging sequences. By understanding the changing appearance of the operative site on GRE images as a function of increasing TE, we can intraoperatively measure the amount of acute blood in a way that improves the outcome of intracranial surgery performed in the intraoperative MR system. In 15 of the 18 cases studied, a small amount of hemorrhage was noted on the periphery of the operative cavity but was

670

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

Fig. 4. Right posterior temporal oligodendroglioma; World Health Organization II/IV. The patient’s right hemisphere is shown on the viewer’s right (ie, viewed from above). The tracked Ojeman probe ( yellow) points at Wernicke’s area (red ) as determined by fMRI in this left-handed patient. Electrical stimulation of the cortex in this area confirmed the fMRI findings. (Blue), 3D reconstruction of the lateral ventricles. (Pink), 3D reconstruction of the tumor.

considered too small to warrant any further action by either the radiologist or surgeon. In three cases, however, the collections produced significant mass effect on surrounding brain structures or were enlarging and subsequently drained using MR guidance. In the most extreme case, where acute hemorrhage was rapidly increasing in size and exerting mass effect on the surrounding brain, the collection was removed under MR guidance. This method shows great potential for detecting white matter tracts as well as avoiding surgical complications related to vascular spasm and occlusion because diffusionweighted MRI can detect ischemic injury. As proof of concept, intraoperative line scan diffusion imaging (LSDI) on a 0.5 Tesla interventional MRI was performed during surgery in three patients. Diffusion trace images were obtained in acute ischemic cases. Diagnosis of acutely developed vascular occlusion was confirmed with follow-up scans [16]. The development of new imaging modalities during the last three decades has significantly impacted brain biopsy techniques. In the early 1970s, CT imaging was used for targeting intracranial lesions in a free-hand fashion followed by the use of stereotactic frames. By translating the image data into the coordinate system of the stereotactic frame, the surgeon was able to improve targeting precision. Frame-based

stereotactic systems next evolved into so-called ‘‘frameless’’ devices wherein the bulky metal frame was replaced by a set of external fiducial markers attached to the patient’s head. This apparatus is, in effect, an ‘‘ultra’’ miniaturized version of a stereotactic frame. The subsequent introduction of intraoperative MR imaging assisted by high-performance computing methods represented a watershed event in the evolution of stereotaxy by offering multiple advantages over other imaging modalities. These advantages include the ability to produce multiplanar acquisitions, to achieve high anatomic accuracy and high sensitivity, to achieve accurate targeting and localization of the tumor, to compensate for intraoperative changes in brain morphology and position (brain shift), and to immediately detect complications such as bleeding, edema, and ischemia. Since 1995, we have performed a total of 154 brain biopsies using intraoperative MR imaging with the following protocol: After positioning the head in the Mayfield clamp, prepping, and draping, a set of T1 contrast – enhanced spin echo, T2-weighted fastspin echo, and 3D SPGR images is acquired. Preoperative scans and/or 3D anatomical models are then registered in the 3D Slicer environment in the patient’s coordinate system. To determine the optimal target region, we use MR spectroscopy, 201Tl-

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

671

Fig. 5. Right insular low-grade glioma. (A) Preoperative axial T2FSE. (B) Intraoperative axial T2FSE at the end of resection, showing inhomogenous, T2 hyperintense filling of the resection cavity. (C and D) Intraoperative axial gradient echo sequences with increasing TE (40 and 60 milliseconds, respectively). The arrows point at an air bubble in the resection cavity. Note the ‘‘blooming’’ arrowheads in D, indicating the presence of hyperacute blood.

SPECT, or dynamic contrast imaging that is coregistered with the structural MRI scans. Using the LED locator without attached biopsy needle, different trajectories are simulated and the optimal entry point is determined. The targeting device is then immobilized in the optimal position using a Boockwalter arm or a trajectory guide screwed to the patient’s skull (Daum GmbH, Schwerin, Germany). After drilling a burr hole and performing the durotomy, ‘‘real-time’’ imaging is used to monitor the needle’s progression towards the lesion. After the target is reached, a new high-resolution scan is acquired verifying the correct needle position. In phantom tests, we have shown that the targeting accuracy of this method falls well within the range established for frame-based systems (1 to 2 millimeters) [17,83,84]. According to the literature, the diagnostic yield for brain biopsies ranges from 80 to 100% [18,19]. Our initial experience in 69 cases using intraoperative MRI for brain biopsies was published in 1999

[17]. In our series, we were able to localize the target and confirm the correct needle position within the MR abnormality in 100% of cases. Four biopsies yielded normal brain tissue, resulting in a 97.4% diagnostic yield in our series. Reasons for diagnostic failure in brain biopsy include small sample size; inaccurate tissue targeting, resulting in sampling error; very small target size; lesions that are difficult to penetrate; and intraventricular, pediculated (mobile) lesions. The literature also indicates that the intraoperative hemorrhage rate for brain biopsies ranges from 0 to 11.5% [18,19]. In our series, we encountered two cases of immediate postoperative bleeding (1.2%), both of which were immediately detected using ‘‘heme-sensitive’’ imaging (see section on heme imaging). In both cases, hematomas were evacuated during the same session and an excellent postoperative outcome was achieved. There was no case of permanent neurologic deficit in this series.

672

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

Surgical navigation using intraoperative MRI Before the introduction of intraoperative MRI, the localization of brain tumors and the surrounding anatomy was exclusively based upon a combination of preoperative image data and intraoperative electrophysiology. Historically, preoperative data has been used exclusively for surgical planning and intraoperative navigational guidance but, because frame-based systems are considered inconvenient, many neurosurgeons have turned to frameless stereotaxic systems on the basis of the clear potential for interactive image guidance to positively influence surgical outcomes. Interactive image guidance, however, remains limited because of brain deformations that occur during surgery. Fortunately, intraoperative, interactive serial MRI can offset this problem but only using the most appropriate navigational tools can preserve adequate interactivity. Ideal iMRI combines MRI imaging with interactive localization of the surgical instruments, intraoperative displays, and computer workstations. First, software tools for displaying the 3D models and the 2D MRI scans are necessary for visualization. Second, tracking instruments are needed to provide interactive display and they provide positional feedback to the surgeon. Third, the 3D model of the patient must be directly related to the actual images. Simply stated, the trackable probe enables us to visually present the position of the surgical instrument relative to the anatomical structures and to the original scan, thereby providing the surgeon with an enhanced view of the surgical field relative to the entire model of the patient’s brain. Other studies have described in detail the design of the integrated system for intraoperative imaging and navigation [19]. Between December 1999 and September 2001, we undertook a total of 239 neurosurgical procedures using iMRI in conjunction with the 3D-Slicer visualization software [23]. We performed 171 craniotomies, 25 brain biopsies, 13 Laser ablations, and 29 trans-nasal, trans-sphenoidal resections for pituitary mass lesions. The patient population consisted of 125 men and 79 women, with a median age of 40 years; 27 procedures were performed in pediatric patients. For the multimodal MRI information to be of real use during a surgical procedure, preoperatively acquired scans must be incorporated into the surgical navigation system and displayed in the patient’s coordinate system just as he is positioned for surgery. The value of preoperative image data for intraoperative navigation is limited, however, by the inherent changes in brain shape that occur during surgery. Possible causes include brain swelling, CSF loss, the

effects of anesthetic drugs and diuretics administered during the procedure, PACO2-dependent variations in vascular tone, and the effect of resection (‘‘brain shift’’). It is widely recognized that these changes occur according to a nonlinear pattern [21,83]. An algorithm for warping pre- or intraoperative image data, based on a linearly elastic biomechanical model of the brain, was developed by Ferrant [22]. After extensive off-line testing of the algorithm, we were able to successfully use it during five neurosurgical procedures. Intraoperative image alignment involves both rigid body registration (to correct for rotation, translation, and scaling differences) as well as nonrigid warping (biomechanical simulation of brain deformation). Preoperative volumetric MRI is first parcelated into tetrahedral units, each including several voxels. The resulting unstructured grid faithfully models key biomechanical characteristics of the relevant anatomy (finite element discretization). Next, a volumetric deformation field relating preoperative image acquisitions to the intraoperative update scan is computed by matching the corresponding surfaces of the two acquisitions. In the third and last step, the computed deformation field is applied to the preoperative data set (MRI scans, 3D models), bringing it into the correct position. For this approach to be practical, the time constraints imposed by the ongoing surgical procedure must be met. By using a finite element model, we can significantly reduce the number of equations that must be solved. We can further increase computation speed by implementing in parallel the algorithm described above. Warping of corticospinal tract, optic radiation, and cerebral vessels typically can be achieved in less than 10 minutes on our platform [23 – 25] (Fig. 6).

Intraoperative MR imaging system Since intraoperative MRI was introduced into neurosurgery in 1993 as an effective means of providing real-time feedback during surgery, this technique has seen increasing popularity [19,33,35]. The original concept was first tested using an open access 0.5 Tesla MRI system (SIGNA SP; General Electric Medical Systems, Milwaukee, WI, USA), which incorporates several principles of intraoperative guidance. Since then, several other intraoperative MRI systems have been used in neurosurgery. Both lowand high-field systems have been tested and various open configurations have been applied [19,26,27,33]. Closed-configuration, high-field systems are also being used for intraoperative imaging [14,27].

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

673

Fig. 6. Diagram of the intraoperative; non – rigid registration method.

In the future, magnet designs will strike a compromise between field strength and accessibility. Optimal image quality demands relatively high-field strength as well as surgical access in completely open systems. The optimal system for neurosurgical guidance, therefore, is likely be equipped with several flexible features from mid to high field and from closed to completely open scanners. In performing image-guided neurosurgery at our institution, we typically use a vertically open, ‘‘double-donut’’ – shaped interventional MR scanner (SignaSP; General Electric) with 0.5 Tesla field strength. The MR scanner incorporates an optical instrument tracking system that consists of three high-resolution infrared cameras mounted in the magnet’s bore above the surgical field; a star-shaped hand piece (‘‘locator’’) equipped with a light-emitting diode on each of the three arms, a centrally located hole in which an instrument of predetermined length (eg, a biopsy needle) can be inserted, and a computer unit. The patient can be positioned supine, prone, or lateral decubitus; the operating table can be docked to the scanner along its longitudinal axis (‘‘front dock’’) or perpendicular to it (‘‘side dock’’). (When the table is front-docked, two surgeons can access the patient simultaneously.) An MR-compatible, carbon fiber Mayfield clamp is attached and the head is positioned in the magnet’s field of view. A flexible radio frequency (RF) coil is then wrapped around the region of interest and left in place for the duration of the

procedure. The operative field is prepped and draped in the usual manner and, finally, the drapes are applied to the inner surface of each ‘‘donut’’ of the scanner.

Initial imaging Before skin incision, a set of axial, coronal, and sagittal T1-weighted spin echo and T2-weighted fastspin echo images is acquired. The imaging is completed with a T1-weighted, 3D SPGR sequence over the course of 10 to 15 minutes on average. We have modified the original computer design by adding an additional visualization workstation that runs the navigation software (3D-Slicer). The visualization workstation receives data on the locator’s position and orientation, which is updated at a rate of 10 Hz. These images can be displayed simultaneously on the workstation’s 20-inch monitor as well as on the two LCD monitors mounted in the bore of the magnet.

Intraoperative navigation Head localization in the scanner space is achieved by the imaging process itself. Instrument localization is achieved using the optical tracking system. The field of view (FOV) of the optical tracking system is aligned precisely to the scanner’s FOV; the dimensions of the latter slightly exceed those of the form-

674

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

er—a feature that enables accurate tracking of instruments even in situations where the LED locator lies beyond the scanner’s FOV. Rigid registration of preoperative data (ie, slices, 3D models) to the patient’s head (as it is positioned for surgery) is readily accomplished by either manual or fully automatic means by using the initial intraoperative SPGR as a frame of reference. The average time required for registration is between 60 and 90 seconds. We can then simulate different approaches by moving the locator without the attached instruments in the FOV. The operation then proceeds in a standard fashion. Because brain shift occurs after durotomy in most of the cases, we typically acquire a new set of images for intraoperative navigation. If appropriate, a bolus of contrast agent is administered at this time; dynamic, T1-weighted spin echo images are acquired, followed by a 3D SPGR data set that is then used for navigation. In cases where nonenhancing lesions such as low-grade glial neoplasms are evident, a set of (usually axial) T2-weighted fast-spin echo images is acquired instead of contrast-enhanced T1-weighted sequences. If the lesion abuts or lies within eloquent cortex, cortical mapping is routinely performed under conscious analgo-sedation. fMRI data along with the tracked cortical stimulator can then be displayed and the results are verified. If brain retraction is necessary, images are acquired with the retractor in place. The locator with attached biopsy needle is then used to localize the lesion. Resection is started at the least critical point and performed either piecemeal or en bloc, as the situation dictates. Image updates are obtained at the surgeon’s discretion. Residual tumor tissue is identified by probing the resection margins with the tracking instrument. The locator acts as a 3D computer mouse, which drives the MR slices in real time to depict the position of the instrument’s tip. Depending on the circumstances, the surgeon is left to interpret either orthogonal slices in the conventional axial, sagittal, and coronal plane or arbitrary, oblique slices along the plane of the probe or perpendicular to it. If necessary (as in case of a bloodfilled resection cavity after contrast administration), to differentiate between residual lesion and contrastenriched blood, ‘‘heme-sensitive’’ acquisitions may be added to the imaging protocol [15]. With increasing TE, spots containing blood become darker because of their deoxy-hemoglobin content, while residual, enhancing tumor essentially retains its signal characteristics. If residual tumor is detected and further resection appears safe, the new data set is loaded into the 3D slicer and the surgical probe is used to localize the residual tumor fragments. Using

the segmentation and volume measurement capabilities of the 3D-Slicer software, we can quantitatively assess the degree of resection that has been achieved. After hemostasis and dural closing, a new set of images (taken according to the same protocol used for the initial imaging) is supplemented by a ‘‘hemesensitive’’ gradient echo sequence. This data set is used to rule out immediate postoperative complications such as hemorrhage and as a baseline from which to interpret follow-up studies.

Interactive intraoperative MR imaging Adapting image acquisition ‘‘on the fly’’ can increase the quality and value of MR images and the information gleaned from them. Retrospective imaging techniques are limited, however, necessitating the application of ‘‘closed-loop control’’ practices that entail placing a human in the loop (manual user feedback) or applying algorithms that analyze raw data or image data to effectively adapt the acquisition to maximize information (adaptive imaging). Correct implementation of imaging parameters such as FOV, matrix size, phase/frequency resolution, frequency direction, scan plane, TR, TE, slice thickness, the RF pulse waveform, and encoding strategies may benefit the acquisition. We have successfully developed interactive imaging applications that adapt scan plane to cardiac, body, and head imaging requirements. Similar techniques can be applied to brain imaging for guiding more accurate interventions and surgeries. In most applications, a software graphical user interface (GUI) is used to interactively select the scan plane of the interest [28] (Fig. 8). An added benefit of open architecture magnets is their ability to optimize manual user control with tracking systems (eg, EM, optical, or mechanical). Such tracking systems are routinely used in conventional operating rooms to plan trajectories with images acquired before surgery. In the intraoperative MRI setting, the tracking system can also be used to specify scan plane. To implement interactive MRI, a workstation is needed for data processing (including image reconstruction if necessary), image display, and generation of new encoding schemes, determined either automatically by computer algorithms or manually through a GUI. The host computer used to prescribe and control scans can also be used as the interactive MRI control workstation. For example, ‘‘Needle Tracking’’ enables the user to select the optimal view for probe placement by controlling scan plane rota-

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

tion and offset. A virtual probe and probe trajectory may be overlaid on the image (Fig. 7). Alternatively, a separate workstation that is connected to the MRI scanner can be dedicated to controlling interactive MRI scanning [28]. To preserve system stability and to take advantage of advanced computing systems, a high-end computer can serve as an interactive workstation and a low-end computer can function as a communication control relay between the scanner and the high-end computer [29,85]. The control workstation can thereby control image acquisition and receive image data from the scanner—all at the same time (Fig. 9). The architecture of such a system is shown in Fig. 8). This system, moreover, allows the user to adjust the acquisition and display parameters ‘‘on the fly’’ such that real-time visualization can be used as feedback for modifying image acquisition. The display can also illustrate data in 2D as well as in 3D. The 2D information can be displayed as gray-scale images with pseudocolored information overlayed. A surface model or volume rendering can be used to represent 3D information. Using this technique, a refresh rate of about 20 frames per second on the 2D 256256 grayscale display and about one frame per second on the 256256 128 volume-rendering display can be obtained. These update rates can handle most interventional MR applications (Fig. 10).

Fig. 7. Catheter tracking in a phantom. Image plane (left) can be specified on the basis of a set of previously acquired images (right).

675

It is clear that the added dimension of control enables rapid adaptation of acquisition that is currently not possible with a conventional MRI system. Moreover, by adding a computer to the loop, we can now manipulate complicated features that, until recently, have been beyond the scope of human abilities alone. From these humble beginnings, we see the first encouraging clinical applications that have established the feasibility of controlling the thermal ablation of lesions.

Intraoperative MRI-based resection control The appropriate management of low- and highgrade gliomas is uncertain. With the exception of patients with intractable epilepsy and symptomatic mass effect, the role of surgery in the management of these pathologic entities remains controversial. Although there is a lack of definitive evidence in support for surgical treatment as the primary therapy in low- and high-grade gliomas, the literature suggests that the extent of resection correlates with increased overall and recurrence-free survival. The literature on this topic in low-grade gliomas has been reviewed recently. For example, in Kelles et al [30], surgical resection is supported in a majority of studies even though the quality of the data is not overwhelming. A recent study on 416 patients with glioblastoma multiforme [31] found a significant survival advantage associated with resection of 98% or more of the tumor volume (median survival 13 months compared with 8.8 months for resections of less than 98%). The visual appearance (to the unaided eye) of lowgrade gliomas, especially at the periphery, is very similar to that of normal brain tissue, which is also the case in the peripheral zone of high-grade tumors. MRI has a much higher sensitivity in detecting these lesions than visual inspection alone. There is a general consensus in the literature that, in the absence of intraoperative image updates, in more than one third of cases, visual inspection of the surgical field alone fails to detect the residual lesion accessible for resection [26,32,33]. For this reason, intraoperative MRI has become the method of choice, achieving the safest and most accurate resection of glial neoplasms. Frequent intraoperative image updates allow for close monitoring of resection progress and also provide an excellent means of detecting changes in the lesion’s position due to brain shift (see section on brain shift). Modern image processing and navigation systems, such as the 3D Slicer package, in conjunction with the interventional MR scanner, allow for quantita-

676

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

Fig. 8. The Needle Tracking (GEMS, Haifa, Israel) GUI and display for interactive MRI applications. Desired scan planes can be ‘‘bookmarked’’ and easily recalled. Control of the pulse sequence is afforded to make needle artifact bigger or smaller. The position on the biopsy needle or probe, based on the coordinates of the tracking system, can be overlaid on the image.

tive assessment of the extent to which resection is achieved by providing near – real-time segmentation and volume measurements. Serial biopsy studies have shown that both lowand high-grade gliomas exhibit an infiltrative growth pattern through white matter fiber tracts and along blood vessels. In fact, tumor cells can be found at distances greater than 2 centimeters from the radiologically visible tumor bulk. Rroutine MR imaging protocols, however, fail to directly visualize the complete extent of infiltration zone as well as the fine white matter structure and its exact relationship to the tumor (e.g., infiltration, displacement) [23]. Anisotropic diffusion tensor imaging (DTI) provides excellent definition of tumor/fiber tract relationship (see section on DTI). Although such sophisticated imaging protocols cannot be performed during surgery, if such data are acquired preoperatively, it can be easily registered in the patient’s frame of reference during surgery and displayed along with the intraoperative image updates (see section on registration issues). There is no current standardized method of intraoperative functional mapping of white matter, which is analogous to electrical cortical map-

ping, a limitation that further underscores the importance of DTI in guiding tumor resection. As stated previously, MRI is highly sensitive to intracerebral pathologic changes; however, MRI lacks specificity and different lesions may appear indistinguishable on conventional T1- and T2-weighted scans. The paramagnetic contrast agents currently in use are only able to highlight zones of blood-brain barrier breakdown. These are nonspecific changes and may be caused by multiple factors beyond tumor infiltration. Surgical manipulation itself is also prone to produce zones of enhancement, which can easily be confounded with residual high-grade glioma [34]. The interpretation might be rendered more useful by a thorough analysis of the spatial and temporal enhancement pattern. Because low-grade gliomas generally do not show contrast enhancement, paramagnetic contrast agents are of very limited use in their detection and surgical targeting. Some researchers advocate the use of paramagnetic contrast agents in differentiating between residual low-grade glioma margin and surgically induced changes at the tumor-brain interface, arguing that zones of contrast enhancement at the tumor border

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

677

Fig. 9. (A) The interactive MRI hardware diagram, as implemented at Brigham and Women’s Hospital. (B) The interactive MRI software diagram, as implemented at Brigham and Women’s Hospital.

that appeared during the surgical procedure, as defined by MRI, indicate zones of microcontusion in the tumor surrounding brain parenchyma induced by surgical manipulation [35]. It can be argued reasonably, however, that microcontusions in the brain parenchyma should not differ in their contrast enhancement patterns microcontusions in from the peripheral zone of tumor. Resolution of this argument must wait for a new generation of contrast agents that, independently of the blood-brain barrier, will selectively bind on tumorspecific receptors.

Thermal ablation in intraoperative MRI One of the most important reasons for extracting dynamic information from intraoperative images is to guide thermal ablation through the ability of MRI to

detect temperature changes. Multiple MRI parameters (eg, T1, diffusion, and chemical shift) are sensitive to temperature changes and can be effectively applied in thermal mapping and monitoring. MRI also can depict thermally induced changes in tissue water mobility and compartmentalization (which can be measured by diffusion- and perfusion-weighted sequences), which reflect any corresponding tissue damage. MRI-based guidance, however, is achievable only if the imaging and therapy systems are integrated. Near – real-time MRI monitoring is also useful in recognizing time-dependent characteristics of heat conduction within heterogeneous tissue. The changes in both microvasculature and large blood vessels can modify treatment plans because blood flow and tissue perfusion can influence the spatial distribution of energy delivery (thereby changing the tissue volume that requires treatment).

678

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

Fig. 10. An example of a GUI and visualization display for the interactive and intraoperative MR applications. The effect of thermal ablation in the brain is simulated. The first row of images shows baseline images (t = 0 seconds), while the second row demonstrates dynamic images after heating (t = 64 seconds). The third row presents 3D visualization of the calculated temperature (left) and accumulation of temperature with time or dose (right) at t = 64 seconds.

During thermal therapy, the magnitude and spatial distribution of temperature changes depend heavily on both the delivery parameters (eg, intensity, duration) of the thermal exposure as well as the tissue properties (eg, absorption, blood perfusion, and flow). Because tissue properties are as individual as the patient and the setting in which the therapy takes place, the outcome of treatments are difficult to control, even after the treatment device has been positioned successfully in the target tissue. Guidance (monitoring and control) of thermal therapy must therefore be adhered to even more stringently. The literature clearly indicates that most endogenous MRI-sensitive parameters are temperature sensitive. The most often exploited of these parameters have been T1 [20,36,37], the apparent diffusion coefficient [38 – 40], and the water proton resonant frequency (PRF) [41,42]. Of these, the PRF method has shown the most promise [43], being the most sensitive [44] and independent of tissue type. This measurement, however, is only applicable in water-based tissues, and it is highly sensitive to motion. These issues should not pose significant limitations in brain treatments, except perhaps for tissue swelling effects

when the exposure time is unexpectedly protracted [45]. Fig. 10 shows an example of thermal imaging.

Control of energy delivery Three approaches have been proposed for controlling thermal therapies with MRI: temperature control, thermal dose control, and imaging control. In the first approach, the threshold of peak temperature necessary to cause necrosis in a given tissue is empirically determined on the basis of animal experiments and clinical experience. Several investigations correlate temperature with tissue necrosis [46]. In selected studies, some investigators have used thresholds measured by MRI as indicators of tissue death during thermal therapies [47,48]. While such correlation studies based on temperature are reliable indicators of tissue necrosis using a specific protocol, hyperthermia studies also suggest that exposure time can also play a significant role in determining the threshold for tissue damage. To take exposure time into account, the thermal dose is calculated to determine the threshold for tissue dam-

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

age [49]. The thermal dose, which is a nonlinear function of the temperature and time, is typically used in hyperthermia treatments where the heating profile is lengthy and remains near 43°C, although it has been also suggested for use during short-duration, high-temperature focused ultrasound therapy [50]. The feasibility of temperature threshold based MRIderived dosimetry for predicting the size of lesions produced during focused ultrasound therapy [51,52] and for predicting the onset of tissue damage [53] has been demonstrated. This dosimetry method may be useful if the heating profile remains constant (ie, retains the same shape and size). Control systems based on temperature and thermal dose feedback have been proposed and developed for MRI-guided hyperthermia with ultrasound heating [54 – 56]. The third approach involves imaging control. Standard T1- and T2-weighted or contrast-enhanced MR images are sensitive to thermally induced tissue changes and can be acquired during the thermal energy depositions [57 – 59]. These images indicate that the evolving lesion either closely approximates or slightly underestimates the final lesion size. While each of these approaches may be useful in controlling thermal therapies, it may be difficult or even impossible to differentiate diseased tissue from thermally ablated tissue and surrounding edema [60]. In addition to the immediate direct effect of heating, delayed secondary tissue changes also occur [60 – 62]. Thus, initial imaging studies can result in underestimating the extent of tissue damage during the time of treatment. It is therefore essential that clinicians both understand and apply tissue response to thermal therapy to safeguard against damage to critical structures adjacent to the target tissue.

679

the demarcation between irreversible cell death and reversible tissue damage. Reversible tissue damage may allow tissue survival and subsequent tumor recurrence. The difficulty presented by a limited treatment volume per optical fiber can be addressed by using multiple optical fibers or specially designed diffusing tips. The problem of separating effectively treated and untreated volumes, however, remains unsolved. One possible solution may be to rely upon temperaturesensitive MRI to map temperatures noninvasively within tissue. It is also important to establish intraoperative dosimetry in the tissue on the basis of the degree and duration of the temperatures achieved. The role of ILT as a therapeutic alternative treatment of brain tumors has yet to be defined. Only a few preliminary reports have been published about the clinical applications of ILT in brain tumors. The fact that ILT has a low incidence of postoperative morbidity and no mortality is very promising. However, transient neurological deficits may occur in the early postoperative period due to perifocal vasogenic edema, though full recovery occurs within few weeks. These early results suggest that ILT is a safe therapy if the laser-induced lesion is confined to the tumor margins. Although a definitive conclusion regarding the value of ILT cannot be drawn, it appears ILT can be of benefit in patients with low-grade gliomas. Thermal therapy in more malignant gliomas has been essentially unsuccessful [33,65], which is expected because in general, no surgical approach or concept has succeeded in significantly altering survival rates of glioblastoma multiforme to date.

Focused ultrasound Interstitial laser therapy Interstitial laser therapy (ILT) is a minimally invasive, high-temperature ablative procedure designed for localized tumor tissue coagulation. Clinical applications for treating malignant gliomas and brain metastases have been initiated using this method. Control was achieved by terminating the ILT when the diameter of the outermost margin of the laser-induced effect (as seen on MRI) covered the tumor. Functional, localization-based control by online monitoring rendered ILT particularly effective in treating brain tumors that are located in areas of significant functional relevance. Disadvantages of ILT include (1) relatively small depth of penetration of the tissue effect, which limits the treated volume, and (2) the ambiguity of

A completely noninvasive interventional technique would be the most desirable treatment for central nervous system diseases. It has been long known that ultrasound energy can be focused deep in the brain and can be used therapeutically. However, since the skull attenuates and distorts ultrasound beam propagation, all of the clinical trials in the brain to this point have been performed after removal of the skull bone to create an ultrasound window for the treatment [63 – 65]. While these trials have demonstrated that ultrasound is well suited for treating intracranial pathology, the requirement for skull removal limits its usefulness. Because of this complexity, this method has not been used in the brain beyond these initial clinical trials. Simulation [66,67] and experimental studies [68 – 70] have demonstrated recently that it is possible to accurately focus through the skull by using an array

680

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683

of multiple ultrasound transducers arranged over a large surface area. The driving signal for each transducer element of this phased array can be adjusted (determined by either an invasive hydrophone probe or on the basis of detailed images of the head) to correct the beam distortion. The large surface area distributes the ultrasound energy over the skull surface, effectively reducing heating. The first experiments using this technique have shown great promise. An experimental, hemispherical phased array has been built and was shown to be capable of creating a nondistorted focus through ex vivo human skulls and delivering adequate power to thermally coagulate tissues at the focus while keeping the temperature elevations low enough to avoid skin or bone damage [70]. Such arrays can be made MRI compatible, so it should be possible to thermally coagulate tumors in the brain, through the skull, under MRI thermometry control. In addition, the sharply focused ultrasound can be used to occlude blood vessels [71 – 73]. In addition to thermal coagulation, focused ultrasound can produce other biological effects that could be exploited for brain treatments. It has been shown that ultrasound can open the blood-brain barrier without damaging the surrounding brain tissue [74]. This can be accomplished with time-averaged power levels that are one to two orders of magnitude below the energy levels required for thermal coagulation by introducing preformed gas bubbles into the vasculature (as is done with ultrasound contrast agents). These bubbles act as cavitation sites that are selectively present in the vasculature. Such MRIguided focal opening of blood-brain barrier, combined with the ultrasound technology that permit sonications through the intact skull, will make new approaches for targeted brain therapy possible. Specifically, it would provide targeted access for chemotherapy and gene therapy, and allow the use of recombinant proteins, monoclonal antibodies, or antisense oligonucleotides as pharmaceuticals for the brain. It could even provide a vascular route for implanting cells in the brain [75]. In addition, the controllable and precise focal energy delivery could be useful in other CNS therapies. Ultrasound has also proven useful in accelerating thrombolysis [76], increasing cell membrane permeability and enhancing gene therapy [77].

Summary Since their introduction into surgical practice in the mid 1990s, intraoperative MRI systems have

evolved into essential, routinely used tools for the surgical treatment of brain tumors in many centers. Clear delineation of the lesion, ‘‘under-the-surface’’ vision, and the possibility of obtaining real-time feedback on the extent of resection and the position of residual tumor tissue (which may change during surgery due to ‘‘brain-shift’’) are the main strengths of this method. High-performance computing has further extended the capabilities of intraoperative MRI systems, opening the way for using multimodal information and 3D anatomical reconstructions, which can be updated in ‘‘near real time.’’ MRI sensitivity to thermal changes has also opened the way for innovative, minimally invasive (LASER ablations) as well as noninvasive therapeutic approaches for brain tumors (focused ultrasound). Although we have not used intraoperative MRI in clinical applications sufficiently long to assess longterm outcomes, this method clearly enhances the ability of the neurosurgeon to navigate the surgical field with greater accuracy, to avoid critical anatomic structures with greater efficacy, and to reduce the overall invasiveness of the surgery itself.

References [1] Nicolato A, Gerosa MA, Fina P, Iuzzolino P, Giorgiutti F, Bricolo A. Prognostic factors in low-grade supratentorial astrocytomas: a uni-multivariate statistical analysis in 76 surgically treated adult patients. Surg Neurol 1995;44:208 – 23. [2] Talos I-F, Walker DG, Zou K, Kikinis R, Jolesz FA, Black PM. Intraoperative magnetic resonance imaging for resection of adult supratentorial low-grade gliomas – factors affecting resectability and early outcome (submitted for publication). [3] Kumar AJ, Leeds NE, Fuller GN, et al. Malignant gliomas: MR imaging spectrum of radiation therapy-and chemotherapy-induced necrosis of the brain after treatment. Radiology 2000;217:377 – 84. [4] Schwartz RB, Hsu L, Okon S, et al. Intraoperative dynamic MR imaging: localization of sites of brain tumor recurrence after high-dose radiotherapy. J Magn Reson Imag 1998;8:1085 – 9. [5] Mamata H, Mamata Y, Westin C-F, et al. High-resolution line-scan diffusion-tensor MRI of white matter fiber tract anatomy. Am J Neuroradiol 2002;23: 67 – 75. [6] Pajevic S, Pierpaoli C. Color schemes to represent the orientation of anisotropic tissues from diffusion tensor data: application to white matter fiber tract mapping in the human brain. Magn Reson Med 1999;42: 526 – 40. [7] Inoue T, Shimizu H, Yoshimoto T. Imaging the pyramidal tract in patients with brain tumors. Clin Neurol Neurosurg 1999;101:4 – 10.

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683 [8] Mamata H, Mamata Y, Westin CF, Shenton ME, Kikinis R, Jolesz FA, et al. High-resolution line scar diffusion tensor MR imaging of white matter fiber tract anatomy. AJNR Am J Neuroradiol 2002 Jan;23(1): 67 – 5. [9] Basser PJ, Pajevic S, Pierpaoli C, Duda J, Aldroubi A. In vivo fiber tractography using DT-MRI data. Magn Reson Med 2000;44:625 – 32. [10] Logothetis NK, Pauls J, Augath M, Trinath T, Oeltermann A. Neurophysiological investigation of the basis of the fMRI signal. Nature 2001;412:150 – 7. [11] Schiffbauer H, Ferrari P, Rowley HA, Berger MS, Roberts TPL. Functional activity within brain tumors: a magnetic source imaging study. Neurosurgery 2001; 49:1313 – 21. [12] Rohlfing T, West JB, Beier J, Liebig T, Taschner CA, Thomale U-W. Registration of functional and anatomical MRI: accuracy assessment and application in navigated neurosurgery. Comput Aided Surg 2000;5: 414 – 25. [13] Moche M, Busse H, Dannenberg C, et al. Fusion von MRT-, fMRT- und intraoperativen MRT-Daten. Methode und klinische Bedeutung am Beispiel neurochirurgischer Interventionen. Radiologe 2001;41: 993 – 1000. [14] Liu H, Hall WA, Martin AJ, Maxwell RE, Truwit CL. MR-guided and MR-monitored neurosurgical procedures at 1.5 T. J Comput Assist Tomogr 2000;24: 909 – 18. [15] Atlas SW, Thulborn KR. MR detection of hyperacute parenchymal hemorrhage of the brain. Am J Neuroradiol 1998;19:1471 – 507. [16] Mamata Y, Mamata H, Nabavi A, Kacher DF, Pergolizzi Jr RS, Schwartz RB, et al. Intraoperative diffusion imaging on a 0.5 Tesla interventional scanner. J Magn Reson Imag 2001;13:115 – 9. [17] Moriarty TM, Quinosnes-Hinojosa A, Larson PS, et al. Frameless stereotactic neurosurgery using intraoperative magnetic resonance imaging: stereotactic brain biopsy. Neurosurgery 2000;47:1138 – 46. [18] Hall WA, Martin A, Liu H, Truwit CL. Improving diagnostic yield in brain biopsy: coupling spectroscopic targeting with real-time needle placement. J Magn Reson Imag 2001;13:12 – 5. [19] Truwit CL, Liu H. Prospective stereotaxy: a novel method of trajectory alignment using real-time image guidance. J Magn Reson Imag 2001;13:452 – 7. [20] Parker DL, Smith V, Sheldon P, Crooks LE, Fussell L. Temperature distribution measurements in twodimensional NMR imaging. Med Phys 1983;10: 321 – 5. [21] Nabavi A, Black PM, Gering DT, Westin CF, Mehta V, Pergolizzi RS, et al. Serial intraoperative magnetic resonance imaging of brain shift. Neurosurgery 2001; 48:787 – 98. [22] Ferrant M, Warfield SK, Guttmann CRG, Mulkern RV, Jolesz FA, Kikinis R. 3D image matching using a finite element based elastic deformation model. Proceedings of Second International Conference on Medical Image

[23]

[24]

[25]

[26]

[27]

[28]

[29]

[30]

[31]

[32]

[33]

[34]

[35]

681

Computing and Computer-assisted Interventions. Cambridge, UK: Springer Verlag; 1999. p. 202 – 9. Talos I-F, Walker DG, Gering DT, et al. Integration of intraoperative MRI, multi-modality image fusion and frameless stereotaxy for neurosurgical procedures (2002, submitted for publication). Warfield SK, Talos I-F, Tei A, et al. Real-time registration of volumetric brain MRI by biomechanical simulation of deformation during image guided neurosurgery. Comput Visual Sci 2002;5:3 – 11. Tei A, Talos I-F, Bharatha A, et al. Tracking volumetric brain deformation during image-guided neurosurgery. In: Ghebreab S, Smeulders AWM, editors. Proceedings of VISIM workshop on information retrieval and exploration in large medical image collections. Urecht, the Netherlands: Spinger Verlag; 2001. Hadani M, Spiegelman R, Feldman Z, Berkenstadt H, Ram Z. Novel, compact, intraoperative magnetic resonance imaging-guided system for conventional neurosurgical operating rooms. Neurosurgery 2001;48: 799 – 808. Sutherland GR, Kaibara T, Louw D, Hoult DI, Tomanek B, Saunders J. A mobile high-field magnetic resonance system for neurosurgery. J Neurosurg 1999; 91:804 – 13. Hardy CJ, Darrow RD, Nieters EJ, Roemer PB, Watkins RD, Adams WJ, et al. Real-time acquisition, display, and interactive graphic control of NMR cardiac profiles and images. Magn Reson Med 1993;29: 667 – 73. Zhao L, Panych LP. Reduced field-of-view dynamic imaging using the combination of a two-dimensional spatial excitation pulse and a dynamic rFOV reconstruction. Radiological Society of North America RSNA 2001:220. Kelles GE, Lamborn KR, Berger MS. Low-grade hemispheric gliomas in adults: a critical review of extent of resection as a factor influencing outcome. J Neurosurg 2001;95:735 – 45. Lacroix M, Abi-Said D, Fourney DR, et al. Multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. J Neurosurg 2001;95:190 – 8. Schneider JP, Schulz T, Schmidt F, Dietrich J, Lieberenz S, Trantakis C, et al. Gross-total surgery of supratentorial low-grade gliomas under intraoperative MR guidance. Am J Neuroradiol 2001;22:89 – 98. Black PM, Alexander III E, Martin C, Moriarty T, Nabavi A, Wong TZ, et al. Craniotomy for tumor treatment in an intraoperative magnetic resonance imaging unit. Neurosurgery 1999;45:423 – 33. Knauth M, Egelhof T, Roth SU, Wirtz CR, Sartor K. Monocrystalline iron oxide nanoparticles: possible solution to the problem of surgically induced intracranial contrast enhancement in intra-operative MR imaging. AINR Am J Neuroradiol 2001 Jan;22(1): 99 – 102. Dietrich J, Schulz T, Schneider JP, Trantakis C, Vitzthum HE. Hirntumorresektionen in einem offenen 0,5

682

[36]

[37]

[38]

[39]

[40]

[41]

[42]

[43]

[44]

[45]

[46]

[47]

[48]

[49]

[50]

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683 T-MRT. Zweija¨hrige Erfahrungen aus neuroradiologischer Sicht. Radiologe 1999;39:988 – 94. Parker DL. Applications of NMR imaging in hyperthermia: an evaluation of the potential for localized tissue heating and noninvasive temperature monitoring. IEEE Trans Biomed Eng 1984;31:161 – 7. Dickinson RJ, Hall AS, Hind AJ, Young IR. Measurement of changes in tissue temperature using MR imaging. J Comput Assist Tomogr 1986;10:468 – 72. Le Bihan D, Delannoy J, Levin RL. Temperature mapping with MR imaging of molecular diffusion: application to hyperthermia. Radiology 1989;171: 853 – 7. Bleier AR, Jolesz FA, Cohen MS, et al. Real-time magnetic resonance imaging of laser heat deposition in tissue. Magn Reson Med 1991;21:132 – 7. Macfall J, Prescott DM, Fullar E, Samulski TV. Temperature dependence of canine brain tissue diffusion coefficient measured in vivo with magnetic resonance echo-planar imaging. Int J Hyperthermia 1995;11: 73 – 86. Kuroda K, Abe K, Tsutsumi S, Ishihara Y, Suzuki Y, Sato K. Water proton magnetic resonance spectroscopic imaging. Biomed Thermol 1994;13:43 – 62. Ishihara Y, Calderon A, Watanabe H, Okamoto K, Suzuki Y, Kuroda K. A precise and fast temperature mapping using water proton chemical shift. Magn Reson Med 1995;34:814 – 23. Peters RD, Hinks RS, Henkelman RM. Ex vivo tissuetype independence in proton resonance frequency shift MR thermometry. Magn Reson Med 1998;40: 454 – 9. Wlodarczyk W, Hentschel M, Wust P, et al. Comparison of four magnetic resonance methods for mapping small temperature changes. Phys Med Biol 1999;44: 607 – 24. McDannold NJ, King RL, Jolesz FA, Hynynen K. Usefulness of MR imaging-derived thermometry and dosimetry in determining the threshold for tissue damage induced by thermal surgery in rabbits. Radiology 2000;216:517 – 23. Meshorer A, Prionas SD, Fajardo LF, Meyer JL, Hahn GM, Martinez AA. The effects of hyperthermia on normal mesenchymal tissues. Application of a histologic grading system. Arch Pathol Lab Med 1983; 107:328 – 34. Kahn T, Harth T, Kiwit JC, Schwarzmaier HJ, Wald C, Modder U. In vivo MRI thermometry using a phase-sensitive sequence: preliminary experience during MRI-guided laser-induced interstitial thermotherapy of brain tumors. J Magn Reson Imaging 1998;8: 160 – 4. Vykhodtseva NI, Sorrentino V, Jolesz FA, Bronson RT, Hynynen K. MRI detection of the thermal effects of focused ultrasound on the brain. Ultrasound Med Biol 2000;26:871 – 80. Sapareto SA, Dewey WC. Thermal dose determination in cancer therapy. Int J Radiat Oncol Biol Phys 1984;10:787 – 800. Damianou C, Hynynen K. The effect of various physical parameters on the size and shape of necrosed

[51]

[52]

[53]

[54]

[55]

[56]

[57]

[58]

[59]

[60]

[61]

[62]

[63]

[64]

tissue volume during ultrasound surgery. J Acoust Soc Am 1994;95:1641 – 9. Chung AH, Jolesz FA, Hynynen K. Thermal dosimetry of a focused ultrasound beam in vivo by magnetic resonance imaging. Med Phys 1999;26:2017 – 26. Hazle JD, Stafford RJ, Price RE. Magnetic resonance imaging-guided focused ultrasound thermal therapy in experimental animal models: correlation of ablation volumes with pathology in rabbit muscle and VX2 tumors. J Magn Reson Imag 2002;15:185 – 94. McDannold NJ, Hynynen K, Jolesz FA. MRI monitoring of the thermal ablation of tissue: effects of long exposure times. J Magn Reson Imag 2001;13: 421 – 7. Vimeux FC, de Zwart JA, Palussiere J, et al. Real-time control of focused ultrasound heating based on rapid MR thermometry. Invest Radiol 1999;34:190 – 3. Salomir R, Vimeux FC, de Zwart JA, Grenier N, Moonen CT. Hyperthermia by MR-guided focused ultrasound: accurate temperature control based on fast MRI and a physical model of local energy deposition and heat conduction. Magn Reson Med 2000;43: 342 – 7. Smith NB, Merilees NK, Hynynen K, Dahleh M. Control system for an MRI compatible intracavitary ultrasound array for thermal treatment of prostate disease. Int J Hyperthermia 2001;17:271 – 82. Lewin JS, Connell CF, Duerk JL, et al. Interactive MRI-guided radiofrequency interstitial thermal ablation of abdominal tumors: clinical trial for evaluation of safety and feasibility. J Magn Reson Imag 1998; 8:40 – 7. Mueller-Lisse UG, Thoma M, Faber S, et al. Coagulative interstitial laser-induced thermotherapy of benign prostatic hyperplasia: online imaging with a T2-weighted fast spin – echo MR sequence-experience in six patients. Radiology 1999;210:373 – 9. Kahn T, Harth T, Bettag M, et al. Preliminary experience with the application of gadolinium-DTPA before MR imaging-guided laser-induced interstitial thermotherapy of brain tumors. J Magn Reson Imag 1997;7:226 – 9. Anzai Y, Lufkin RB, Hirschowitz S, Farahani K, Castro DJ. MR imaging-histopathologic correlation of thermal injuries induced with interstitial Nd:YAG laser irradiation in the chronic model. J Magn Reson Imag 1992;2:671 – 8. Morocz IA, Hynynen K, Gudbjartsson H, Peled S, Colucci V, Jolesz FA. Brain edema development after MRI-guided focused ultrasound treatment. J Magn Reson Imag 1998;8:136 – 42. Chen L, Bouley D, Yuh E, D’Arceuil H, Butts K. Study of focused ultrasound tissue damage using MRI and histology. J Magn Reson Imag 1999;10: 146 – 53. Fry WJ, Fry FJ. Fundamental neurological research and human neurosurgery using intense ultrasound. IRE Trans Med Electron 1960;ME-7:166 – 81. Heimburger RF. Ultrasound augmentation of central nervous system tumor therapy. Indiana Med 1985;78: 469 – 76.

F.A. Jolesz et al / Neuroimag Clin N Am 12 (2002) 665–683 [65] Guthkelch AN, Carter LP, Cassady JR, et al. Treatment of malignant brain tumors with focused ultrasound hyperthermia and radiation: results of a phase I trial. J Neuro-Oncol 1991;10:271 – 84. [66] Sun J, Hynynen K. Focusing of ultrasound through a human skull: a numerical study. J Acoust Soc Am 1998;104:1705 – 15. [67] Sun J, Hynynen K. The potential of transskull ultrasound therapy and surgery using the maximum available skull surface area. J Acoust Soc Am 1998;104: 2519 – 27. [68] Hynynen K, Jolesz FA. Demonstration of potential noninvasive ultrasound brain therapy through intact skull. Ultrasound Med Biol 1998;24:275 – 83. [69] Hynynen K, Sun J. Trans-skull ultrasound therapy: the feasibility of using image derived skull thickness information to correct the phase distortion. IEEE Trans Ultrason Ferroelectr Freq Contr 1998;46: 752 – 5. [70] Clement GT, White J, Hynynen K. Investigation of a large-area phased array for focused ultrasound surgery through the skull. Phys Med Biol 2000;45: 1071 – 83. [71] Delon-Martin C, Vogt C, Chigner E, Guers C, Chapelon JY, Cathignol D. Venous thrombosis generation by means of high-intensity focused ultrasound. Ultrasound Med Biol 1995;21:113 – 9. [72] Hynynen K, Colucci V, Chung A, Jolesz FA. Noninvasive artery occlusion using MRI guided focused ultrasound. Ultrasound Med Biol 1996;22:1071 – 7. [73] Vaezy S, Martin R, Yaziji H, et al. Hemostasis of punctured blood vessels using high-intensity focused ultrasound. Ultrasound Med Biol 1998;24:903 – 10. [74] Hynynen K, McDannold N, Vykhodtseva N, Jolesz FA. Noninvasive MR imaging-guided focal opening of the blood-brain barrier in rabbits. Radiology 2001; 220:640 – 6. [75] Deacon T, Schumacher J, Dinsmore J, et al. Histological evidence of fetal pig neural cell survival after transplantation into a patient with Parkinson’s disease. Nat Med 1997;3:350 – 3. [76] Porter TR, LeVeen RF, Fox R, Kricsfeld A, Xie F.

[77]

[78]

[79]

[80]

[81]

[82]

[83]

[84]

[85]

683

Thrombolytic enhancement with perfluorocarbon exposed sonicated dextrose albumin microbubbles. Am Heart J 1996;132:964 – 8. Greenleaf WJ, Bolander ME, Sarkar G, Goldring MB, Greenleaf JF. Artificial cavitation nuclei significantly enhance acoustically induced cell transfection. Ultrasound Med Biol 1998;24:587 – 95. Roux F-E, Ibarrola D, Tremoulet M, Lazorthes Y, Henry P, Sol J-C. Berry I methodological and technical issues for integrating functional magnetic resonance imaging data in a neuronavigational system. Neurosurgery 2001;49:1145 – 57. Mattay VS, Weinberger WR. Organization of the human motor system as studied by functional magnetic resonance imaging. Eur J Radiol 1999;30:105 – 14. Nimski C, Ganslandt O, Kober H, Moeller M, Ulmer S, Tomandl B, et al. Integration of functional magnetic resonance imaging supported by magnetoencephalography in functional neuronavigation. Neurosurgery 1999;44:1249 – 56. Liu H, Hall WA, Martin AJ, Truwit CL. Biopsy needle tip artifact in MR-guided neurosurgery. J Magn Reson Imag 2001;13:16 – 22. Schulder M, Fontana P, Lavenhar MA, Carmel PW. The relationship of imaging techniques to the accuracy of frameless stereotaxy. Stereotact Funct Neurosurg 1999;72:136 – 41. Nimsky C, Ganslandt O, Cerny S, Hastreiter P, Greiner G, Fahlbusch G. Quantification of, visualization of, and compensation for brain shift using intraoperative magnetic resonance imaging. Neurosurg 2000;47:1070. Landi A, Marina R, DeGrandi C, et al. Accuracy of stereotactic localisation with magnetic resonance compared to CT scan: experimental findings. Acta Neurochir 2001;143:593 – 601. Zhao L, Saiviroonporn P, Yoo SS, Zientara GP, Jolesz FA, Panych LP. Real-time adaptive MRI. International Society for Magnetic Resonance in Medicine (ISMRM) 1998;1962.