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To investigate the hypothesis that the outer boundary of the hyperintense region observed in hyperacute (several minutes post-ablation) T2 and gadolinium contrast-enhanced (CE) T1-weighted magnetic resonance (MR) lesion images is an accurate predictor of eventual cell death from radiofrequency (RF) thermal ablation.
Materials and Methods
A low-field, open MR imaging system was used to guide an ablation electrode into a thigh muscle of five rabbits and acquire in vivo T2 and CE T1-weighted MR volumes. Ablation occurred by applying RF current for two minutes with the electrode's temperature maintained at 90° ± 2°C. After fixation, we sliced and photographed the tissue at 3 mm intervals, using a specially designed apparatus, to obtain a volume of tissue images. Digital images of hematoxylin and eosin (H&E) and Masson trichrome–stained histologic samples were obtained, and distinct regions of tissue damage were labeled using a video microscopy system. After the MR and histology images were aligned using a three-dimensional registration method, we compared tissue damage boundaries identified in histology with boundaries marked in MR images.
The lesions have distinct zones of tissue damage histologically: a central zone of necrotic cells surrounded by an outer zone with cells that appeared non-viable and associated with marked interstitial edema. In 14 histology images from five lesions, the inner and outer boundaries of the outer zone were compared with the boundaries of a hyperintense rim that surrounds a central hypointense region in the T2 and CE T1-weighted MR images. For T2 and CE T1-weighted MR images, respectively, the mean absolute distance was 1.04 ± 0.30 mm (mean ± SD) and 1.00 ± 0.34 mm for the inner boundaries, and 0.96 ± 0.34 mm and 0.94 ± 0.44 mm for the outer boundaries. The mean absolute distances for T2 and CE T1-weighted MR images were not sufficiently different to achieve statistical significance (P = 0.745, 0.818, for the inner and outer boundary, respectively).
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SOLID TUMORS AND other pathologies can be treated using radiofrequency (RF) thermal ablation under interventional magnetic resonance (MR) image guidance (1–5). MR imaging (MRI) has several advantages, including the lack of ionizing radiation, excellent soft tissue discrimination, sensitivity to blood flow and temperature, and multiplanar capabilities (6, 7). In addition, MRI appears to be superior to ultrasound or x-ray computed tomography for monitoring the effects of RF thermal ablation treatments (8, 9). The major contribution of MRI is its potential to monitor the zone of thermal tissue destruction during the procedure. To monitor an ablation procedure, MRI can intermittently acquire temperature images during heating and structural lesion images during and after heating. We investigated this unique ability to evaluate treatment by comparing hyperacute (several minutes post-ablation) MR lesion images to tissue damage as seen histologically. The ability of these MR images to accurately predict the region of eventual cell death would allow complete destruction of the disease tissue volume, including margin, while avoiding the destruction of nearby normal tissue of critical importance.
If one can prove that the hyperacute MR signal accurately reflects tissue damage and destruction, MR can be used to confidently evaluate the progress of treatment minutes after heating. This will enable one to adjust the size and shape of the treated region, through additional heating or displacement of the RF electrode to a new location, so as to ensure coverage of the pathology. The ability to monitor therapy will enable one to extend the method to the safe destruction of tumor adjacent to vital structures that might be damaged by heating, such as the gall bladder, bowel, and especially the brain, where collateral damage must be minimized.
Our careful correlation of hyperacute MR lesion images with the corresponding tissue response has several advantages. First, this could allow for a better understanding of mechanism responsible for the MR signal changes, particularly the hypointense center and hyperintense rim. These MR signals changes could be due to different zones of tissue damage or different zones of increased extracellular space. Second, our analysis may allow for a more complete understanding of the tissue response at the margin of the lesion. Third, this would allow one to compare the mechanism and pattern of tissue destruction of RF ablation to other ablation techniques such as laser and focused ultrasound, where similar MR lesion appearances are observed. Finally, this correlation could better explain the macroscopic tissue color changes, which were used by others to assess tissue damage (10–14).
There have been some inconsistent findings with regard to tissue damage at the margin of MR images of thermal lesions acquired minutes after treatment. Some studies suggested that a central region of low MR signal corresponds to the region of tissue damage (10–13). Analysis was typically done using geometric measurements without spatial alignment of histology with MR lesion images. For example, in normal rabbit liver, Lee et al (10) manually measured diameters of the central hypointense region in T2-weighted and gadolinium contrast-enhanced (CE) T1-weighted MR thermal lesions, and measured diameters of a central region of color change in sectioned fresh tissue. In six lesions, the diameters agreed within 2 mm. Other studies of ablation showed that a hyperintense rim in MR may become necrotic (14–16). Merkle et al (14) compared the diameters of a region occupied by the union of the central zone and surrounding hyperintense zone in T2 and CE T1-weighted MR lesion images with diameters of coagulation seen in fixed macroscopic tissue slices without any correction for tissue shrinkage or comparison to histology. These diameters typically matched within 2 mm. From these studies, there is evidence that MR thermal lesion images reflect tissue damage. However, the inconsistencies in the literature indicate the challenge of reliably identifying cell death from color changes in macroscopic tissue sections and from morphologic changes in hematoxylin and eosin (H&E) stained histology immediately after ablation. Another potential source of discrepancy is the limitation of diameter measurements for nonsymmetrical lesion boundaries obtained when ablation is not symmetrical or when the image or tissue slice is not perpendicular to the long axis of a radially symmetric lesion. A careful regional correlation requires the alignment of histology to MR images, and reliable methods to accurately determine the extent of tissue damage. Our studies carefully examine the relationship between cell damage and MR images on a voxel-by-voxel basis.
The purpose of this investigation was to test the hypothesis that the outer boundary of the hyperintense region observed in hyperacute T2 and gadolinium CE T1-weighted spin echo (SE) MR lesion images is an accurate predictor of eventual cell death from RF thermal ablation. The focus on T2 and CE T1-weighted SE MR images, as compared to other MR imaging sequences, is motivated by earlier reports that describe the MR appearance of RF-induced thermal lesions in various organs (9, 11–14) and based on the clinical experience of radiologists developing and performing interventional MRI RF ablation procedures at our institution (authors J.S.L. and S.G.N.). In addition, prior studies have already reported a consistent MRI appearance of thermal ablation zones using various imaging parameters (such as echo time) for both T2 and CE T1-weighted SE sequences (9, 11–14, 17, 18).
To investigate this hypothesis, we will use several specially designed experimental and registration techniques so as to enable alignment of MR lesion images with histologic images showing tissue damage and destruction. The special experimental methods are next described.
MATERIALS AND METHODS
The comparison of in vivo MR thermal lesion images to the tissue response required both experimental and registration methods as described in more detail below. Briefly, experimental methods included RF thermal ablation of a rabbit thigh model, post-ablation MRI, tissue slicing and photographing, and histologic processing and imaging. It was extremely important to minimize tissue deformation and destruction during the dissection and slicing processes for accurate registration. Using the tissue photographs as a reference, we aligned histology and MR images with two registration methods. First, the MR volume was aligned to the volume of tissue photographs by performing a three-dimensional fiducial needle registration. Second, we aligned the histology images with the tissue photographs using a two-dimensional warping registration. To correlate MR images with the tissue response, we segmented tissue damage boundaries in histology images, and compared them to segmented lesion boundaries in registered MR images.
RF Ablation in Rabbit Thigh Model and MRI
Following a protocol approved by the Institutional Animal Care and Use Committee, we anesthetized five New Zealand White rabbits (3.0–3.5 kg) with a 2 mL intramuscular (IM) injection of a cocktail (0.6 mL/kg), a combination of ketamine (0.26 mL/kg), xylazine (0.26 mL/kg), and acepromazine (0.08 mL/kg) (each manufactured by Phoenix Scientific, St. Joseph, MO), and maintained the anesthesia with IM injections every 20–40 minutes that alternated between 0.5 mL of ketamine (0.15 mL/kg) and 1 mL of cocktail (0.3 mL/kg). After shaving each animal's abdomen and left thigh, we placed the rabbits in the prone position within the gantry of a clinical 0.2-T C-arm MRI system (Siemens MAGNETOM OPEN, Erlangen, Germany). The legs of each rabbit were secured to a customized Plexiglas support, which prevented movement of thighs. After positioning two 8 × 12 cm wire mesh grounding pads coated with conductive gel (Aquasonic 100: Parker Laboratories, Orange, NJ) on each rabbit's abdomen, we placed the thighs within a 12 cm diameter multi-turn solenoid, receive-only coil.
Under MR guidance, we inserted an MR-compatible 17-G titanium RF electrode with a 10 mm exposed tip (Radionics, Burlington, MA) percutaneously into the thigh muscle. Before ablation, we acquired an MR image volume of the thigh. A T2-weighted turbo SE sequence (TR-3362 msec, TE-68 msec, number of signals averaged (NSA)-8) was applied that gives 256 × 256 × 9 voxels over a 180 × 180 × 27-mm field of view (FOV) to yield 0.70 × 0.70 × 3.0-mm voxels oriented to give the highest resolution for slices approximately perpendicular to the RF electrode. Lesion formation was achieved by increasing the local tissue temperature with resistive heating by delivering RF electric current between the electrode tip and ground pads. We applied RF energy for two minutes using a 100 W RF generator operating at 500 kHz (RFG-3C; Radionics, Burlington, MA). The tip of the RF electrode was maintained at a temperature of 90° ± 2°C using a thermistor within the electrode tip. Immediately after ablation, a 22-G × 1 inch IV catheter (Terumo Medical Corporation, Elkton, MD) was inserted in a dorsal ear vein in each rabbit. To align the MR and tissue images as described below, fiducial needles were included that can be seen in the MR images, and leave a hole that can be found in the excised tissue. At least two MR-compatible 22-G, 10 cm fiducial needles (E-Z-EM, Westbury, NY) were inserted into the thigh near the thermal lesion with one fiducial approximately parallel and the other fiducial approximately at an angle of 45° to the RF electrode. The RF electrode was removed from the thigh before imaging to prevent MR image artifacts. It is to be noted in this context that the small centrally located MR susceptibility artifact of the electrode does not obstruct the boundary of the lesion, and the electrode is not removed from the tissue during clinical MRI-guided RF ablation procedures, in which the electrode is commonly repositioned to ensure that the thermal ablation zone encompasses the entire targeted tumor along with a safety margin (9).
Approximately 10 minutes after ablation, we acquired MRI volumes of the thigh. A T2-weighted turbo SE sequence was applied with the same parameters and orientation as the pre-ablation image acquisition described above. We also applied a T1-weighted SE sequence with (TR-624 msec, TE-26 msec, NSA-6) that gives 256 × 256 × 9 voxels over a 180 × 180 × 27 mm FOV to yield 0.70 × 0.70 × 3.0 mm voxels oriented the same as the T2-weighted sequence. At least five minutes before acquiring the T1-weighted SE images, we administered an IV injection of gadolinium contrast medium (0.2 mmol/kg gadopentate dimeglumine; Berlex Laboratories, Wayne, NJ). The rabbits were killed approximately 45 minutes after the ablation using a barbiturate overdose technique via IV administration of 0.1 mL/pound of pentobarbital sodium (Euthasol, 390 mg/mL; Diamond Animal Health Inc., Des Moines, IA).
Images from several versions of T2 and CE T1-weighted SE sequences were acquired and evaluated so as to optimize the acquisition for rabbit thigh ablation experiments. For each SE sequence, subjective image comparisons of the thermal lesion were made by interventional-MRI radiologists (authors J.S.L. and S.G.N.) with regard to contrast, image signal-to-noise ratio (SNR), and spatial resolution. Because prior reports have documented a consistent overall MRI appearance of the thermal ablation zones (9, 11–14, 17, 18), independent of the specific pulse sequence parameters, we used one set of acquisition parameters so as to achieve consistency and reproducibility.
We took care to prevent significant thigh muscle deformation. The entire pelvis and back limbs of the rabbits were harvested with the skin removed, and fixed in 10% formalin for two to three days. The formalin was refrigerated at approximately 6°C to prevent deterioration of the tissue before fixation. To improve the penetration of the formalin, we then removed the thighs, which contained the fiducial needles, from the bone and fixed them for an additional 10–12 days.
During dissection of the thighs, we minimized tissue deformation while maintaining the orientation of fiducial needles used for registration. To dissect each thigh, we first cut the muscle with a scalpel at the distal and proximal ends of the femur bone. We then removed the muscle directly off the bone without disturbing the fiducial needles. Because we dissected a tissue volume (typically 8 × 6 × 6 cm) significantly larger than the centrally located volume containing the lesion and fiducial needles (typically 4 × 3 × 3 cm), tissue warping was minimized within the volume of interest. In addition, we inserted the RF electrode under MRI guidance to create a lesion with its boundary a few centimeters from the femur to minimize deformation during dissection. We also used MRI guidance to position the fiducial needles immediately adjacent (typically within 1 cm) to the thermal lesion boundary to minimize the volume of interest. After the thigh was removed, we acquired histologic samples and registered them to the MR images using the method described in subsequent sections.
Tissue Slicing and Acquisition of Calibrated Tissue Images
We obtained 3 mm tissue slices by using a specially designed apparatus that included a tissue platform, digital camera (DSC-D770, Sony, Japan), and a linear displacement device (Rack and Pinion Slide; Edmund Scientific, Barrington, NJ) for accurate stepping of the platform in small increments. To orient the specimen and reduce deformation during slicing, we embedded the thigh, which contained the fiducial needles as described above, into tissue embedding wax (50–54°C Parablast X-tra; Oxford Labware, St. Louis, MO). By orienting both planes perpendicular to a fiducial needle, we ensured the tissue-slicing plane and the plane of the MR image slices were approximately parallel. This minimizes image blurring of the re-sliced images when there is out-of-plane tilting with respect to the thick MR image slices. We sliced the specimen with a 12.8-inch autopsy knife (Tissue-Tek Accu-Edge Semi-Disposable Autopsy Knife System; Sakura Finetek, Japan) using vertical supports of the apparatus as a guide. We photographed the tissue block face, advanced the platform by 3 mm, and sliced the tissue, repeating the process until the specimen was traversed. The tips of the fiducial needles were exposed at the tissue block face for easy identification in each photograph, and stepped back slightly beyond the plane of the next tissue slice. We calibrated these macroscopic tissue images using a ruler in the plane of the tissue slice. The tissue images yield square pixels that were typically 0.17 mm on a side. We embedded the tissue slices in paraffin and obtained H&E and Masson trichrome (MT) stained histologic sections mounted on glass microscope slides.
Acquisition of Histology Images
Histology slides were digitized using a video microcopy system that consisted of a light microscope (BX60; Olympus, Japan), video camera (DXC-390; Sony, Japan), position encoded motorized stage (ProScan; Prior Scientific, Rockland, MA), and controller software (Image-Pro with Scope-Pro; Media Cybernetics, Silver Spring, MD). To obtain an image of the entire slide, we used a software function that drove the motorized stage, acquired a series of photographs, and seamlessly combined the photographs to form one large tiled image with pixels that were typically 5.21 μm on a side. By reducing the tiled image to 10% of its original size, we created a smaller map image on which we marked the locations of tissue damage boundaries.
Segmentation of Tissue Damage Boundaries in Histology
To compare the thermal lesion appearance in MR images with the tissue response, we manually segmented (marked) boundaries of tissue damage identified in histology. Under the supervision of a pathologist (author M.F.), we established criteria to identify cell damage. Tissue damage was based on changes in cell morphology and stain color on H&E and MT stained sections. In addition, we evaluated cell damage based on the loss of muscle's naturally occurring birefringence, which has been shown to be a reliable indicator of irreversible cell damage (19, 20). Birefringence properties were determined in MT stained sections under polarized light. Both an inner and outer tissue damage boundary was marked for each MT stained section. The inner boundary separated a central region (zone H1) characterized by muscle cells with shrunken nuclei, contraction band necrosis/coagulative myocytolysis, and complete loss of birefringence from a well demarcated region (zone H2) with similar histologic changes but only a partial loss of birefringence. We also marked an outer tissue damage boundary that divided a conspicuous region (zone H3) characterized by cells that appeared necrotic, were shrunken and fragmented, and were associated with distinct interstitial edema from adjacent normal tissue (zone H4). Hence, we marked the inner and outer boundary of a region occupied by the union of two zones (zone H2+H3).
A single observer manually marked the two tissue damage boundaries using a previously developed video microscopy system and a software-scripting program written in Image-Pro and Scope-Pro (21). The observer had experience examining histology without knowledge of MR lesion boundaries. With a digitally imposed crosshair at the center of a live video window, the operator panned around the slide under joystick control and identified boundaries of interest. While locating boundaries, the operator could switch microscope objectives to acquire images at higher or lower magnification levels. On each boundary, we identified 15–30 points by centering the crosshair over each point of interest and clicking a graphic user interface button to acquire the stage coordinates. Each boundary point was marked at the appropriate location on the map image with a colored graphic overlay. The end result of this marking process was a map image with two tissue damage boundaries that can be compared with lesion boundaries seen in MR images.
Registration of MR and Histology Images
A previously developed three-dimensional registration method was used to align the histologic and in vivo MR image data (21). Briefly, we used the macroscopic tissue images as the reference and registered histology and MR images to them with two different computer alignment steps. First, the MR volume was aligned to the volume of tissue images by registering the fiducial needles placed near the lesion (22). Second, we registered the histology images with the tissue images using a two-dimensional warping technique that aligned internal features and the outside boundary of histology and tissue images (21). The above steps allowed us to match a pixel in a histology image with an interpolated sample from the in vivo MR image volume. This registration method was previously validated (21), and the accuracy determined from displacement of needle fiducials was estimated to be 1.32 mm ± 0.39 mm (mean ± SD).
Segmentation of Lesion Boundaries in MR Images
To compare the histologic tissue damage boundaries with lesion appearance in MR, we manually segmented MR lesion images. Both the inner and outer boundaries of the lesion's hyperintense rim were segmented for each CE T1 and T2-weighted MR image volume. The investigators established criteria for boundaries under the supervision of a radiologist (author J.S.L.) specializing in interventional MRI RF ablation. Before actual segmentation, observers segmented a training set consisting of images similar to the experimental data. Training set results were compared among all investigators and further training performed until consistent results were obtained.
Two of the authors (M.S.B. and R.S.L.) independently performed the segmentation using a freehand region of interest (ROI) tool in Analyze 3.1 (Analyze Direct, Lenexa, KS) image analysis software. These observers had experience looking at MR images without knowledge of histology boundaries. Important software features included the ability to look at adjacent MR image slices simultaneously and a ROI editing tool. The observers followed a strict protocol. All segmentation was performed on the same workstation in a darkened room. We perceptually linearized the display using Optical (ColorVision Optical, Rochester, NY) and validated with a step wedge image. By adjusting the vertical and horizontal controls of the display, we obtained square pixels with 0.2 mm edge length. Window and level settings for each image set were fixed before segmentation such that the qualitative contrast between the inner and outer lesion zones was maximized. The T2-weighted MR images acquired before ablation could be viewed simultaneously on our display and were utilized to visualize background features such as fat and connective tissue so as to appropriately eliminate these structures from the segmented lesions. Each observer was blinded from the results of the other observer. To minimize bias, T2 and CE T1-weighted images for a given rabbit were never segmented during the same day.
Following segmentation, the ROI boundary coordinates were exported and analyzed using MATLAB 6.1 (Mathworks, Natick, MA). Each segmented point was assigned a three-dimensional coordinate, in millimeter dimensions, based on the voxel dimensions. The set of boundaries was utilized for subsequent comparison with tissue damage boundaries from histology.
Boundary Comparison of MR to Tissue Response
To evaluate the ability of MR images to predict tissue response, we used software programs written in MATLAB to directly compare the manually segmented boundaries from MR and histology images. Each boundary coordinate was assigned a two-dimensional coordinate, in millimeters, based on the pixel size. For each tissue slice, an automatic algorithm determined equally spaced points, 0.25 mm apart, along a spline interpolated along the histology boundary. For each such point, the algorithm found the closest point along a continuous spline interpolated from the corresponding MR boundary. A signed two-dimensional Euclidean distance between each point pair was determined such that if the MR point is closer to center of lesion than the histology point, the distance is negative, else it is positive. This allowed us to determine if one boundary was interior or exterior to the other.
To examine the effect of MR segmentation error on any discrepancy between tissue damage and MR lesion boundaries, we compared the interobserver variability of the two observers' MR boundaries to the difference between MR and histology boundaries. The MR and histology boundaries were used to calculate the Williams index (WI), a ratio of the average absolute distance between multiobserver MR boundaries to the average absolute distance between the multiobserver MR boundaries and histology boundaries (23). A WI of 1.0 implies the difference between histology and MR boundaries is not more than the disagreement among the MR observers themselves.
Statistical analysis was performed with the two-sample t-test. A P-value <0.05 was considered to indicate a statistically significant difference.
In Fig. 1, we show typical in vivo MR lesion images acquired approximately 45 minutes post-ablation. The plane of the MR image was oriented approximately perpendicular to the RF electrode. These MR images reveal a significant change of the MR signal in the vicinity of the RF current source. The characteristic elliptical appearance for both T2 and CE T1-weighted MR images has a central core, hereafter called zone M1, surrounded by a hyperintense margin (zone M2). Beyond zone M2, the MR signal is isointense to surrounding muscle (zone M3). Other experiments gave similar results.
In Fig. 2, histology images of a thigh muscle from a rabbit sacrificed approximately 45 minutes post-ablation are shown. The histologic samples were obtained approximately perpendicular to the RF needle. Surrounding the RF needle track, a distinct thermal lesion can be seen. In Fig. 2, rows H1, H2, H3, and H4 show images of four distinct histologic zones.
In the central region of the lesion (zone H1), the architecture of the skeletal muscle appears intact, with a size, shape, and distribution of cells similar to normal skeletal muscle. However, in the majority of cells, the cell nuclei are smaller and somewhat pyknotic, and the cytoplasm shows evidence of contraction band necrosis (focal band-like coagulation of contractile elements) or coagulative myocytolysis (granular myofibrillar degeneration). The cytoplasm of the skeletal muscle cells is eosinophilic (pink) like that of normal skeletal muscle cells on H&E stain, but is metachromatic rather than red on MT stain. Often the ratio of cells with coagulative myocytolysis to those with contraction band necrosis increased with increasing distance from the RF needle track. Under polarized light, the cells are dark due to significant loss of birefringence.
Further from the lesion center, there is a well demarcated transition zone (zone H2) with both metachromatic and red cells on MT stain, and more extracellular space than normal muscle. The cells show evidence of contraction band necrosis or coagulative myocytolysis. Under polarized light, there are both dark and bright muscle cells due to a partial loss of birefringence.
Surrounding zone H2, there is distinct region (zone H3) that is significantly paler than zones H1 and H2 on both H&E and MT stains. However, in many cases, the skeletal muscle cells themselves are more hypereosinophilic (darker pink/red on H&E and MT stains) than normal skeletal muscle cells. These hypereosinophilic cells appear necrotic, lack nuclei, are shrunken and distorted with a wavy or fragmented appearance, and are associated with marked interstitial edema. We sometimes found pools of red blood cells indicative of hemorrhage. Under polarized light, there are both dark and bright cells due to a partial loss of birefringence. No inflammatory cells are seen in either zone H1, H2, or H3. Blood vessels appear intact in all three zones. It should be noted that zone H2+H3 (union of zone H2 and H3) has more extracellular space than normal muscle and partial loss of birefringence.
This tissue response is very sharply delimited against adjacent normal muscle tissue (zone H4). The normal cells appear bright under polarized light because they are completely birefringent. Results were remarkably similar in other experiments.
In Fig. 3, we copied the inner and outer boundary of H2+H3 identified manually in MT stained histologic samples to the registered T2 and CE T1-weighted MR images. These histology boundaries matched features well in the MR images. Zone H2+H3 was well aligned with the hyperintense rim in both T2 and CE T1-weighted MR images. Results were remarkably similar across several adjoining tissue slices.
To further analyze this, we quantitatively compared the boundaries of M2 with H2+H3. In Fig. 4, the two-dimensional signed distance for the inner and outer boundaries was plotted as a function of distance along the boundary of H2+H3. We used the boundary of H2+H3 as the reference and measured distances to corresponding points along the boundary of M2. Results are shown for M2 boundaries marked by two observers. Collapsing over both tissue slices and observers for the inner and outer boundaries respectively, the mean absolute distance was 1.06 ± 0.34 mm (mean ± SD) and 0.51 ± 0.08 mm for T2-weighted MR images, and 0.77 ± 0.14 mm and 0.47 ± 0.21 mm for CE T1-weighted MR images. These values compare favorably to the in-plane MR voxel dimension (0.70 mm) and slice thickness (3.00 mm). This is good evidence that the boundaries of M2 for T2 and CE T1-weighted MR images can accurately predict the boundaries of H2+H3.
Using registered image data from all five lesions, we determined the discrepancy between the boundaries of M2 and H2+H3. In Fig. 5, we plotted the mean signed and absolute distance for inner and outer boundaries as a function of the MR observers. Collapsing over both MR observer boundaries for the inner and outer boundaries, respectively, the mean signed distance was not significantly different from zero (P = 0.456, 0.142) for T2 and (0.326, 0.053) for CE T1-weighted MR images, indicating insufficient bias between corresponding boundaries. For the inner and outer boundaries, respectively, the mean absolute distance was 1.04 ± 0.30 mm (mean ± SD) and 0.96 ± 0.34 mm for T2 and 1.00 ± 0.34 mm and 0.94 ± 0.44 mm for CE T1-weighted images, which compares favorably to the in-plane MR voxel dimension (0.70 mm) and slice thickness (3.00 mm). Averaging the two M2 observer distances for each slice, we determined that the mean absolute distances for T2-weighted MR images were not significantly different from those for CE T1-weighted images (P = 0.745, 0.818) for the inner and outer boundaries, respectively.
To examine the effect of MR segmentation error on the small discrepancy between histology and MR boundaries, we compared the interobserver variability of the two observers' M2 boundaries to the difference between M2 and H2+H3 boundaries. We calculated the ratio of the average absolute distance between the two observers' M2 boundaries to the average absolute distance between the M2 and H2+H3 boundaries (WI). In Table 1, we show the average absolute distance between H2+H3 and two observers' M2 boundaries (HOD), average absolute distance between the two observers' M2 boundaries (IOD), WI, and 95% confidence interval (CI). A CI with an upper limit greater than 1.0 indicates that there is as much variability between H2+H3 and M2 boundaries as there is between the two observers' M2 boundaries (23). Because each upper limit of the CI was less than 1.0, there is greater agreement between the observers' M2 boundaries than between H2+H3 and M2 boundaries. Upper limit CI values between 0.57 and 0.80 indicate that the variability between H2+H3 and M2 boundaries is about twice the variability of the observers' M2 boundaries. This is good evidence that the MR boundary segmentation error accounts for approximately one half of the discrepancy between MR and histology boundaries.
Table 1. Comparison of Interobserver Variability of Two Observers' M2 Boundaries to Difference Between M2 and H2 + H3 Boundaries
HOD = histology to observer difference, IOD = interobserver difference, WI = IOD/HOD, 95% CI = 95% confidence interval of the WI.
Our results suggest that it is possible for hyperacute T2 and CE T1-weighted MR lesion images to predict the tissue response to RF ablation. That is, we determined that zone M2 from MR and the region occupied by the union of two zones seen in histology, H2+H3, matched very well. Other regions, M1 and H1, and M3 and H4, also necessarily correspond. Features of our method, such as three-dimensional registration of in vivo MR images to histology images, accurate segmentation of tissue damage boundaries on tiled images of large-format histology slides, and reliable assays to determine tissue damage, such as polarized light assessment of muscle birefringence, are important steps to accurately correlate the tissue response to in vivo MR thermal lesions images.
It is believed that histology zones H1, H2, and H3 correspond to the region of eventual cell death. Although the exact determination of cell viability is challenging, the presence of contraction band necrosis and coagulative myocytolysis, and a loss of birefringence suggest that the cells within zones H1 and H2 are non-viable. Zone H3 is clearly non-viable due to the fragmentation of the cells. Upon thermal injury, a loss of birefringence occurs due to the disarray of the regular matrix of the actin and myosin molecules, and this has been previously shown to correspond to a region of eventual necrosis (19, 20). We recognize that the birefringence assay for cellular viability is unique to muscle tissue. In addition, although necrotic changes specific to muscle were reported, the MR thermal lesion appearance and resulting general coagulative changes due to thermal treatment are common to many tissues (9, 11, 13, 17). We are also performing studies with animals killed several days post-ablation, which should unequivocally reveal the complete extent of tissue necrosis in histology.
It appears likely that the contraction band necrosis and coagulative myocytolysis we describe in RF ablation of skeletal muscle is due to muscular hypercontraction in response to an influx of calcium ions as a result of thermal injury, rather than to direct thermal coagulation. As hypercontracted skeletal muscle cells may be more rigid than their normal counterparts, it is also possible that the cellular distortion/fragmentation and edema seen in the zone H3 of the lesions may be due to mechanical stress from the surrounding normal skeletal muscle cells (24).
It is possible that the MR and histology boundaries match exactly and the small differences are less than our ability to measure for a variety of reasons. First, the mean absolute differences (typically 1.0 mm) compare favorably to the MR in-plane voxel width (0.70 mm) and thickness (3.00 mm). Probably because of the partial volume effect, there is uncertainty of at least one voxel width as to where to visually place the edge. This manual MR segmentation uncertainty must limit the study resolution. The WI values are consistent with this observation; they indicate that the variability between histology and MR boundaries is about twice the variability of the two observers' MR boundaries. Thus, the MR segmentation error possibly accounts for approximately one-half of the discrepancy between MR and histology boundaries.
Second, registration errors arise from both the alignment of the MR volume with the tissue sections and the warping of histologic sections to the tissue sections. By comparing needle fiducial locations, it was previously determined that the error of the entire registration procedure is random, not systematic, across specimens (21). The registration method worked reliably after several challenges, such as warping of the tissue due to movement and tearing of the tissue during dissection and tissue slicing, were overcome with experience. The three-dimensional registration method also compensated for slight tissue shrinking due to fixation by using a uniform scale parameter in the needle registration. For these thigh muscle experiments, shrinkage was typically 5%, a value consistent with previous studies (25), which showed a mean shrinkage of 2.3% for muscle tissue. In addition, a potential source of local distortion might occur with any tissue swelling due to edema. However, such swelling should occur before insertion of the needle fiducials, and any regional distortion should be consistent across the image data. Although we have done much to limit registration error, it must account for a considerable amount of the discrepancy between boundaries.
Third, we note that although registration was performed in three-dimensions, boundary distance calculations were performed on a two-dimensional basis due to the slice nature of histologic sections. This approach tends to overestimate distances because the closest point along an MR boundary for a given point along a histology boundary may be slightly out of plane.
Fourth, the in-plane resolution of the registered histologic images (0.17 mm pixel width) was approximately four times that of the acquired MR slices (0.70 mm voxel width). This allows partial volume effects that effectively blur several histologic pixels into a single MR voxel. In addition, the three-dimensional registration and reslicing procedure may further reduce the effective in-plane MR resolution through out-of-plane tilting. However, this effect was minimized by acquiring both histologic and MR data approximately perpendicular to the RF electrode path.
Given the above considerations, the small detected differences between corresponding histology and MR boundaries are likely insignificant. Hence, the MR signal probably accurately identifies regions of tissue destruction.
A comparison of MR and tissue response a few minutes after RF thermal ablation showed that the central zone M1 and the hyperintense region, zone M2, closely correspond to the region of dead or irreversibly damaged cells in histology. These results are consistent with previous studies that investigated the correlation of MRI and histology following focused ultrasound (15) and laser thermal ablations (16). Using experimental approaches that carefully acquired MR and tissue images in the same plane, and cell-viability staining techniques, these studies suggested that zone M1 corresponds to the necrotic region, and zone M2 will probably become necrotic. However, other investigations that used geometric measurements without alignment of histology to MR images, indicated that only zone M1 correlates with the region of tissue damage (10, 13). These findings indicate that an accurate regional correlation requires reliable methods to determine tissue damage, such as polarized light assessment of muscle damage, and alignment of histology to MR images.
We have determined that the hyperintense rim, zone M2, in the hyperacute CE T1 and T2-weighted MR images is likely due to increased water from extracellular edema. In histology images, we reliably located a distinct region, zone H2+H3, of increased extracellular space, which strongly indicates edema. Because zone H2+H3 corresponds to zone M2, this is good evidence that edema probably accounts for the hyperintense rim in the MR images. These results are consistent with previous studies that describe tissue damage after RF ablation (11, 26). These studies observed in histology a zone of edema characterized by vacuolation of the neuropil in brain tissue and a zone of small microhemorrhages, but they did not include MR correlation. Our study showed that a region of distinct increased extracellular space, zone H2+H3, that we believe is a region of edematous necrosis, probably gives rise to the hyperintense rim in MR.
It is advantageous to know that the hyperacute MR signal accurately reflects tissue damage and destruction. First, the hyperacute signal can provide feedback soon after ablation as to whether the thermal lesion adequately covers the pathology. This can be used to assess the need for additional ablation sites. Second, feedback can show when the thermal lesion is sufficient, eliminating the need for a large over-treated margin. As a result, it might be possible to safely apply RF ablation procedures near vital structures that might be damaged by heating, such as the gall bladder, bowel, and neurovascular structures. Third, MR temperature images can be correlated with MR structural anatomic images, thus enabling us to develop a mathematical thermal damage model. Fourth, this could eliminate the complicated task of aligning histology images with in vivo MR images for future ablation studies. Finally, because there was no statistically significant difference between the hyperintense rim boundaries for hyperacute T2 and CE T1-weighted MR images, perhaps only T2-weighted MR images need to be obtained for reliable monitoring. This would avoid the cost, potential allergic reactions, and timing issues for uptake and clearance associated with a contrast agent, and the time needed for multiple imaging acquisitions.
In our ablation experiments, we used a rabbit skeletal muscle model to investigate the relationship between MR lesion images and the tissue response. Other ablation studies in liver and brain support our findings (15, 16), and remarkably similar MR lesion appearances were observed in a various tissues, including tumor (9, 11–14, 17, 18). We performed thermal ablations on normal rather than tumor tissue. We contend that such studies are applicable to tumor ablation therapy because it is clinically desirable to treat the tumor plus a margin of normal tissue (9). Despite the good arguments for general applicability of our results, the experiments should be repeated in other tissue types and tumor.
We conclude that our three-dimensional methodology can be used to accurately map tissue response to MR thermal lesion images. Observations strongly suggest that in hyperacute T2 and CE T1-weighted MR images of RF ablated rabbit thigh muscle, the outer boundary of the hyperintense rim corresponds to the region of eventual cell necrosis within a distance comparable to our ability to measure. This is good evidence that MR thermal lesion images can be used during RF ablation treatments to accurately localize the zone of irreversible tissue damage at the lesion margin.
The authors thank Perrin Cheung, BS, for assistance with rabbit ablation experiments and acquisition of histology images, and Miyuki Breen, BS, for assistance with statistical analysis. M.S.B. is supported, in part, by an NIH training grant. R.S.L. is supported by a Whitaker Foundation graduate fellowship and the CWRU Medical Scientist Training Program.