Brain tumors are a significant cause of neurological disorders and mortality in dogs and cats, with incidence rates of up to 4.5% in dogs and 2.2% in cats, higher than those in humans, where the rate is up to 25.48 per 100,000 people.1–4 Previously, brain tumors were confirmed postmortem, but advances in CT and MRI now allow for accurate detection.5,6 However, imaging alone can make diagnosis challenging, as brain diseases often appear similar.5,7–12 For example, Wolff et al8 found that, when relying solely on MRI without other clinical data, 23 out of 57 cases of meningioma were misdiagnosed as other brain tumors, normal findings, or bacterial infections. Additionally, palliative care without a definitive diagnosis leads to poor prognosis, with a median survival of only 2.3 months due to worsening neurological symptoms.6,13 Thus, a definitive diagnosis through histopathological examination is essential before treatment to determine the best approach, such as surgery, radiation, or chemotherapy and to assess prognosis based on tumor characteristics.10,11,14,15 Sample collection for histopathological examination is conducted via brain biopsy, a common method in human medicine.4,10–12,14,16–20
Brain biopsies are less frequently performed in veterinary medicine than in human medicine due to smaller brain sizes, limited expertise, and economic and ethical concerns.12,21,22 The majority of veterinary brain biopsies employ an open technique with therapeutic surgical resection, which is primarily suitable for surface-level tumors accessible to surgery.18,23 In cases where surgery is not indicated, a minimally invasive closed technique with high precision can be employed, typically using stereotactic guidance.10,11,14,18,23 The frame-based method is the gold standard in human medicine and the most frequently reported in veterinary medicine; however, rigid headframes present limitations, including patient discomfort and reduced flexibility.5,11,14,16,18,24,25
Recent advancements, such as 3-D–printed brain biopsy guides (3D-BBGs) and neuronavigation, have introduced alternative techniques with distinct advantages and disadvantages.10–12,14,15,20 While 3-D–guided biopsies are cost-effective and easy to use, they cannot accommodate trajectory adjustments during the procedure.20,25 In contrast, neuronavigation allows for trajectory modifications but necessitates expensive equipment and additional preparatory steps.12,14,25 Despite the differences in characteristics among these brain biopsy techniques, biopsy accuracy is crucial for diagnosis and safety.10–12,14,15,18,20 Although several studies10–12,14,15,20 have assessed biopsy accuracy by inserting biopsy needles or pins into cadavers using each method, direct comparisons of the accuracy of these methods based on identical criteria remain very limited.
This study aimed to compare the accuracy of 3D-BBGs and neuronavigation in brain biopsies. A skull-brain tumor model (SBTM) was created using 3-D–printing technology to evaluate accuracy. We hypothesized that there would be no significant difference in the accuracy between the 2 methods. We also evaluated whether biopsy needle length and skull shape affect biopsy accuracy.
Methods
Skull-brain tumor model production
Skull model production
Computed topography data and breed information were collected from patients without brain diseases at Gyeongsang National University Animal Medical Center between May 2023 and March 2024. Skull CT data in digital imaging and communications in medicine format were processed using computer image processing and modeling software (3-D Slicer 5.4.0) for skull segmentation with the threshold tool and the creation of an enclosed space using the paint tool.26 Surface smoothing was applied with a smoothing factor of 0.5. The 3-D skull model was exported in stereolithography format. All 3-D editing processes used in this study, including length measurement and design of the SBTM and 3D-BBG, were conducted using computer-aided design (CAD) software (3-DS MAX 2024; Autodesk). To quantify the skull shape, measurements of the 3-D skull model were taken as follows: skull length (prosthion to inion), skull width (maximum zygomatic width), cranial length (nasion to inion), and cranial width (maximum neurocranial width). The skull and cranial indices were calculated as follows: skull index = (skull width/skull length) X 100 and cranial index = (cranial width/cranial length) X 100.27–29 An 18-mm-diameter opening was created on the left calvarium, and a 3-D cap model with a 6-mm hole was designed to cover it (Figure 1). A 10-mm cube marker was added to the posterior of the 3-D skull model to ensure accurate superimposition of the prebiopsy and postbiopsy 3-D SBTMs for evaluating biopsy accuracy. The models were printed using a 3-D printer (Photon M3 Max; Anycubic) and a resin (UV-tough resin; Anycubic). All 3-D printing in this study followed these printing conditions.
Skull-brain tumor model (SBTM). A—A 3-D–reconstructed skull model with an opening (arrow) for a brain tumor model, a 3-D cap model (arrowhead) with holes for injecting agarose gel, and a cube reference marker (asterisk) for superimposing the prebiopsy and postbiopsy 3-D SBTMs for evaluating biopsy accuracy. B—Brain tumor model mold and blue brain tumor models. C—Placement of the brain tumor model in the right piriform lobe of the skull model. D—Completed SBTM. E—Transverse CT image at the level of the piriform lobe of the SBTM identifying the spherical brain tumor model (arrow).
Citation: American Journal of Veterinary Research 86, 2; 10.2460/ajvr.24.10.0301
Brain tumor model production
A brain tumor model mold with a 6-mm-radius spherical cavity and a 4-mm-diameter sprue was designed using CAD software and 3-D printed (Figure 1). The mold was filled with a mixture of 1.5% agarose gel, 1% Evans blue, and 1% barium, which solidified to form a brain tumor model.
Three-dimensional–printed brain biopsy guides production
SBTM was scanned using a CT scanner (Aquilion Lighting 160; Canon Medical System) with a field of view of 140 X 140 mm and a slice thickness of 0.5 mm (Figure 1). The CT data were used to create 3-D reconstructions of the skull and brain tumor models, which were uploaded to the CAD software.30 The 3-D skull and brain tumor models (Figure 2) were aligned so that the tumor center was at coordinates (x = 0, y = 0, z = 0). A sphere with a radius of 1 mm was set as the target point at the center. A cylinder representing the biopsy needle’s path was created from this point to the right calvarium, where the 3D-BBG was attached. Its length, representing the skull-to-target point length, was measured.11 A 5-mm-thick rectangular footprint was created around the cylinder at the right temporalis muscle site. The biopsy needle cylinder was extended by 30 mm, within which 2 additional cylinders (15-mm height and 4- to 6-mm radius) were created. The farthest cylinder was hollowed using the Boolean tool to form a biopsy trajectory guide. The closest cylinder was then removed to create a viewing space for at biopsy site. Supports were added from the 3 corners of the footprint to connect to the farthest cylinder and reinforced with spheres containing small holes for fixation pins. The 3D-BBG was developed based on Shinn et al11 and printed using a previously described method. Initially, the 3D-BBG design process took approximately 5 hours; however, as the design became standardized and familiarity with the CAD software increased, the time required was reduced to about 1 hour. The total biopsy needle length was the sum of the skull-to-target length and 30 mm (the distance from the skull to the end of the 3D-BBG).
A—Example of 3-D–printed brain biopsy guide (3D-BBG) design created with computer-aided design software. The shining cylinder (arrow) represents the path of the brain biopsy needle, with its length corresponding to the total biopsy needle length required for the procedure. B—A 3D-BBG attached to the skull-brain tumor model with Kirschner wires. C—Brain biopsy being performed using a 3D-BBG. Biopsy needle (arrow) mounted on the 3D-BBG with a 3-mL syringe. D—A sample of the brain tumor model (arrow) obtained from the biopsy needle’s sampling window.
Citation: American Journal of Veterinary Research 86, 2; 10.2460/ajvr.24.10.0301
Brain biopsy using 3-D–printed guides
The 3D-BBG was positioned on the right cranium of the SBTM, ensuring contact surfaces matched (Figure 2). The brain biopsy site was identified and marked on the SBTM. Craniotomy was performed using a cutting burr with a 2-mm ball head. Subsequently, the 3D-BBG was repositioned on the SBTM, and 0.8 Kirschner wires were inserted into the fixation pinholes to secure the guide. A stopper was placed on the biopsy needle (Biopsy Needle Kit 9733068; Medtronic) to match the total length of the needle. A 3-mL syringe was attached to the inner cannula hub of the biopsy needle. The inner cannula was rotated by 180° to close the sampling window and then inserted into the SBTM using 3D-BBG until it reached the stopper. Once the biopsy needle reached the target, the inner cannula was rotated by 180° to open the sampling window. Negative pressure was created by aspirating 0.5 mL with a syringe, allowing biopsy of the brain tumor model. The inner cannula was rotated again to close the sampling window, and the biopsy needle was removed from the SBTM. The sampling window was checked for the presence of blue agarose gel to verify the biopsy results.
Brain biopsy using neuronavigation
Electromagnetic (EM) neuronavigation determines the surgical site and tools’ positions by detecting changes in a magnetic field generated by an emitter, allowing real-time visualization during surgery.25 The system includes a neuronavigation cart (StealthStation S8; Medtronic) for planning and display, a patient tracker to synchronize with the 3-D model, an emitter for detecting magnetic field changes, and a tracer pointer for positional information. Five fiducial markers were attached to the SBTM: 1 each on the right frontal bone, parietal bone, and zygomatic arch, and 2 on the left cranium.31 Computed topography scanning was performed as previously described. The patient tracker was attached to the SBTM’s hard palate, and the model was secured to the operating table with tape to prevent movement during the biopsy (Figure 3). The emitter was positioned to detect the area of brain biopsy. The CT file was extracted in the digital imaging and communications in medicine format and uploaded to the neuronavigation system. The fiducial markers and SBTM surface were registered using a tracer pointer to synchronize the system, with registration accuracy maintained at 0.5 mm or less and the registration time did not exceed 5 minutes per SBTM. To verify the biopsy needle tip’s position, the EM stylet (9735428; Medtronic), visualized in the system, was mounted on the biopsy needle’s center cannula and attached to the external trajectory guide, aiming at the right cranium biopsy site.17 Since the EM stylet is 55 mm shorter than the biopsy needle, the virtual trajectory on the planning screen was extended by 55 mm to align the needle tip with the planning point. The virtual trajectory was extended to position the planning point at the center of the brain tumor model. The length of the extended trajectory from the skull to the target point was measured. A craniotomy was performed as previously described. The biopsy needle was advanced under real-time neuronavigation until the planning point aligned with the target. Brain biopsy was conducted following a previously described method, and the sample was checked on a blue agarose gel to verify its success. After the biopsy, the position of the needle in the upper part of the trajectory guide was checked to measure the total biopsy needle length.
A—Registration of fiducial markers with a tracer pointer to synchronize electromagnetic (EM) neuronavigation with the skull-brain tumor model. B—Brain biopsy being performed using EM neuronavigation. Emitter (asterisk) and biopsy needle (white arrow) mounted on the external biopsy trajectory guide (black arrow), along with the EM stylet (arrowhead). C—Neuronavigation planning screen showing the brain biopsy needle’s virtual trajectory (arrows) targeting the center of the brain tumor model, displayed in transverse, sagittal, and dorsal plane CT images, as well as trajectory view. Cd = Caudal. Cr = Cranial. D = Dorsal. Lt = Left. Rt = Right. V = Ventral.
Citation: American Journal of Veterinary Research 86, 2; 10.2460/ajvr.24.10.0301
Accuracy assessment of brain biopsy
This study evaluated the accuracy of brain biopsy by measuring how much the placement of the biopsy needle within the intracranial tumor model deviated from the planned target point, excluding any potential deviations outside the skull boundaries. Brain biopsy accuracy was evaluated by reconstructing the CT data into 3-D models using CAD software.19 After the biopsy, the SBTM was reimaged using CT (Figure 4). Based on the CT data, a postbiopsy 3-D SBTM was reconstructed.
A—Transverse CT image at the level of the piriform lobe of the skull-brain tumor model after brain biopsy showing the visible needle tract (arrow) from the procedure. B—Superimposed red prebiopsy and white postbiopsy 3-D SBTMs based on the cube reference marker for the accuracy assessment of brain biopsy using 3-D–printed brain biopsy guides. The red and white 3-D SBTMs are superimposed, resulting in a pink color. C—Superimposed neuronavigation planning screen image and postbiopsy 3-D SBTM to set the biopsy target point. The biopsy target point is represented by a red sphere, and the neuronavigation planning screen dorsal plane image is rendered transparent for illustration. D—Transverse plane slice of the postbiopsy 3-D SBTM showing the needle tip point represented by a blue sphere at the end of the biopsy needle tract and the biopsy target point represented by a red sphere.
Citation: American Journal of Veterinary Research 86, 2; 10.2460/ajvr.24.10.0301
Three-dimensional–printed brain biopsy guides
For biopsies using 3D-BBG, the postbiopsy 3-D model was uploaded to the CAD software used for 3D-BBG creation. The prebiopsy and postbiopsy 3-D models were superimposed using the cube reference marker from the skull model creation (Figure 4). A 1-mm-radius sphere was placed at the end of the biopsy needle tract in the postbiopsy 3-D brain tumor model to mark the needle tip point, with coordinates recorded as (x', y', z'). For 3D-BBG biopsies, the target point coordinates (x, y, z) were set to (0, 0, 0), representing the center of the tumor model, during the 3D-BBG creation.
Electromagnetic neuronavigation
For EM neuronavigation biopsies, the postbiopsy 3-D model was aligned with the transverse, sagittal, and dorsal planes on the neuronavigation planning screen images (Figure 4). In CAD software, the slice tool cuts the postbiopsy 3-D model into cross-sections matching these planes.30 A 1-mm-radius sphere was created at the intersection of neuronavigation planning points in each plane, with its center as the biopsy target point (x, y, z), representing the center of the tumor model. The needle tip points (x', y', z') were determined using the postbiopsy 3-D model. In both 3D-BBG and EM neuronavigation biopsies, the needle placement error, which indicates how much the needle tip point deviated from the center of the tumor model, was calculated as √[(x-x')2 + (y-y')2 + (z-z')2].11,14,20,25
Statistical analysis
The data were analyzed using SPSS version 27 (IBM Corp). The normality of the needle placement error data was assessed using the Shapiro-Wilk test, and homoscedasticity was evaluated using the Levene test. Needle placement errors between the 3D-BBG and EM neuronavigation groups were analyzed using independent t tests. The relationships between skull-to-target point length, total biopsy needle length, skull index, cranial index, and needle placement error were analyzed using multiple linear regression. Data are presented as medians and ranges. Statistical significance was set at P < .05.
Results
Skull-brain tumor models
Based on the patient CT data, 15 different types of SBTMs were created, with 2 models for each type. The breeds and species of the patients were as follows: Pomeranians (n = 2), Shih Tzus (2), Dalmatian (1), German Shepherd (1), Golden Retriever (1), French Bulldog (1), Bedlington Terrier (1), Welsh Corgis (2), and Dachshund (1), for a total of 12 dogs and 3 Korean short-hair cats. The median body weight was 5.6 kg (range, 3 to 26.8 kg). The median skull index of the SBTMs was 70.19 (range, 49.96 to 93.89), and the median cranial index was 58.53 (range, 45.06 to 79.58).
Brain biopsy accuracy
Brain biopsies were performed on 15 SBTMs in each of the 3D-BBG and EM neuronavigation groups, resulting in 30 biopsies. The median needle placement errors for the total brain biopsy, 3D-BBG, and EM neuronavigation groups are presented (Table 1). The median needle placement error was 0.11 mm smaller in the EM neuronavigation group than in the 3D-BBG group, although the error range was wider in the EM neuronavigation group. No significant difference was found in the brain biopsy needle placement error between the 3D-BBG and EM neuronavigation groups (P = .49).
Descriptive data on needle placement error by brain biopsy groups.
| Total brain biopsy (n = 30) | 3D-BBG (n = 15) | EM neuronavigation (n = 15) | ||||
|---|---|---|---|---|---|---|
| Type | Median | Range | Median | Range | Median | Range |
| Needle placement error (mm) | 1.75 | 0.82–3.16 | 1.79 | 0.94–2.94 | 1.68 | 0.82–3.16 |
3D-BBG = 3-D–printed brain biopsy guide. EM = Electromagnetic.
The median values for the skull-to-target point length, total biopsy needle length, skull index, and cranial index, as well as the P values for their relationships with needle placement errors in each group, are presented (Table 2). The median differences between the 3D-BBG and EM neuronavigation groups were 1.82 mm for the skull-to-target point length and 56 mm for the total biopsy needle length, with a greater difference in the latter. There was no statistically significant relationship between brain biopsy needle placement error using 3D-BBG and the skull-to-target point length (P = .68), total biopsy needle length (P = .64), skull index (P = .21), or cranial index (P = .52). There was no statistically significant relationship between brain biopsy needle placement error using EM neuronavigation and the skull-to-target point length (P = .62), skull index (P = .88), or cranial index (P = .17). However, a statistically significant relationship was found with the total biopsy needle length (P = .03).
Descriptive data, including median values and P values for the skull-to-target point length, total biopsy needle length, skull index, and cranial index.
| 3D-BBG (n = 15) | EM neuronavigation (n = 15) | |||
|---|---|---|---|---|
| Type | Median (range) | Correlation with needle placement error (P value) | Median (range) | Correlation with needle placement error (P value) |
| Skull-to-target point length (mm) | 28.18 (16.00–36.96) | .68 | 30 (17–38) | .62 |
| Total biopsy needle length (mm) | 58 (46–67) | .64 | 114 (95–169) | .03 |
| Skull index | 70.19 (49.96–93.89) | .21 | 70.19 (49.96–93.89) | .88 |
| Cranial index | 58.53 (45.06–79.58) | .52 | 58.53 (45.06–79.58) | .17 |
P values indicate relationships with needle placement errors.
Blue agarose gel samples representing brain tumor models were successfully collected in both the 3D-BBG and EM neuronavigation groups, with postbiopsy CT confirming that all samples were taken from within the tumor model located at the right piriform lobe site (Figure 2).
Discussion
In this study, we performed brain biopsies on SBTMs created using 3-D–printing technology in dogs and cats of various breeds, sizes, and head shapes. We utilized 3D-BBGs and EM neuronavigation for brain biopsies and subsequently measured and analyzed the accuracy of the brain biopsies. Along with the median needle placement errors of 1.79 mm in the 3D-BBG group and 1.68 mm in the EM neuronavigation group, the maximum needle placement error observed in this study, which was 3.16 mm, also is within the previously reported accuracy range of 0.83 to 3.6 mm for mean and median values in stereotactic brain biopsy studies.5,10,11,14,20,21,24,32 As hypothesized, there was no significant difference in the accuracy of brain biopsies between the 3D-BBGs and EM neuronavigation techniques (P = .49).
Previous studies10,11,14,15,20,25 assessing brain biopsy accuracy using cadaveric samples have faced issues such as brain tissue autolysis, compromising the reliability of the results. In this study, we used 3-D–printing technology based on CT images from our database to create SBTMs, offering several advantages. First, it avoids the challenge of sourcing cadavers, allowing biopsies of models with diverse breeds, sizes, and head shapes. Second, based on previous studies33–38 that used skull or brain models for surgical simulation, education, and experimentation, our approach was both ethically acceptable and cost-effective.33–38 Our SBTMs were produced at a cost of 3 to 9 dollars, using resin for the skull and agarose gel for the brain. However, unlike other studies37,38 that included structures, such as vessels and ventricles, we simplified our models to include only the skull, brain parenchyma, and tumor to save cost and time. Future studies should incorporate these structures to better evaluate the accuracy and safety of brain biopsies.
Neuronavigation systems that track and visualize patient and instrument positions in real time are classified into optical and EM neuronavigation.12,14,20,25,39 To the best of our knowledge, this study is the first to evaluate the accuracy of brain biopsies using EM navigation in veterinary medicine. The EM neuronavigation operates by detecting changes in the magnetic field, allowing it to be used from various positions and directions, but it can be interfered with by metallic objects, such as surgical tools or patient implants.39 A clinical advantage of EM neuronavigation is that it does not require rigid head attachments, like reflective markers or pins, necessary for optical neuronavigation systems.12,20,25,39,40 Thus, EM neuronavigation offers the advantage of avoiding the need for additional anesthesia and preventing artifacts during CT scans caused by attachments.39 The absence of rigid head attachments allows for patient head movement during surgery, reducing patient discomfort.40 In this study, soft sticker fiducial markers were used, and EM neuronavigation registration was successfully achieved on the SBTM without restrictions on the model’s positioning.39,40 The median registration error was 0.4 mm (range, 0.3 to 0.5 mm), with accurate registration being completed within a few minutes. EM neuronavigation offers versatility, as it can be used regardless of the patient’s size or position without the need for rigid head attachment. Therefore, in hospitals with resources to acquire this equipment, EM neuronavigation could be a valuable option for performing brain biopsies precisely and safely.
In veterinary medicine, the application of 3-D–printing technology for precision surgeries involving the brain is gaining increasing attention.10,11,15 When applied to veterinary medicine, 3-D–printing technology offers various advantages, including surgical planning using 3-D software, the printing of 3-D models, simulated surgical practice, and the creation of 3-D–printed guides or implants.10,11,15,30 One of the key advantages of 3-D–printing technology is its ability to provide patient-specific customization throughout these processes, as illustrated by the 3D-BBG used in this study.10,11,15,30 The benefits of using the 3D-BBG for brain biopsy include the elimination of costly equipment, such as neuronavigation systems, as the guide can be directly attached to the patient’s skull, conforming to the unique anatomical structures of the attachment site and enabling the procedure to be performed along a predetermined trajectory and depth without the need for marker placement or additional imaging studies.11 While a potential limitation of this method is the inability to adjust the planned trajectory during the procedure, this limitation can be addressed by incorporating multiple alternative pathways into the design of the 3D-BBG.10,11 To perform brain biopsies with 3D-BBG on actual patients, a larger exposure area could be needed than when using neuronavigation to ensure optimal contact between the guide and the bone. In this study, although the absence of skin and muscle eliminated interference from soft tissues, the rounded shape of the skull made it challenging to determine the precise attachment site for the 3D-BBG. Further research is required to ensure that 3D-BBG can be effectively attached in clinical applications to areas lacking anatomically distinct structures, such as the skull. 3D-BBG offers highly precise and patient-specific customization of brain biopsies, and its utility in veterinary medicine is expected to grow significantly with continued advancements in its design and application.
In this study, the difference in the median needle placement error between the 3D-BBG and EM neuronavigation methods was found to be 0.11 mm. The small difference in brain biopsy accuracy between the 2 methods can be attributed to the fact that both methods are based on stereotactic procedures designed using CT data. Positional information from CT data was used in the 3D-BBG method for device creation using CAD software.10,11,15,19,20 In the EM neuronavigation method, this information was employed to visualize positional changes by integrating it with variations in the magnetic field.19,20,40 Additionally, this study employed an artificially constructed SBTM rather than performing brain biopsies on actual patients or cadavers, which may have contributed to the minimal difference in biopsy accuracy between the 2 methods. In a previous study20 comparing the accuracy of brain biopsies using cadavers, the median needle placement error difference between 3D-BBG and neuronavigation was reported to be 0.8 mm, which is 0.69 mm larger than the median difference observed in this study. Therefore, the difference in accuracy between the 2 biopsy methods was smaller in this study compared to previous research. This study demonstrated that both biopsy methods could accurately position the biopsy needle at a stereotactically determined target point during the biopsy planning stage using SBTM, with no significant differences in accuracy observed between the 2 methods (P = .49). Further studies are required to compare the accuracy of these 2 brain biopsy methods under the same conditions.
While previous studies10,14 have reported no statistical correlation between needle placement error and biopsy length, our study found a significant correlation between needle placement error and total biopsy needle length in the EM neuronavigation group. Although consistent results were not observed across both the 3D-BBG group and the EM neuronavigation group, geometric modeling predicts that the error increases as the distance to the target lengthens.14 In the 3D-BBG group, there was no significant relationship between needle placement error and either skull-to-target point length or total biopsy needle length. This was likely because the trajectory guide in the 3D-BBG technique, in which the median total biopsy needle length was 58 mm, was attached directly to the patient’s skull, resulting in a shorter distance from the target. In contrast, the EM neuronavigation technique, in which the median total biopsy needle length is 114 mm, positions the external biopsy trajectory guide farther away from the patient, resulting in a longer distance. Therefore, additional research is needed on the accuracy of brain biopsy in relation to the tumor location and the total length of the biopsy needle.
This study has several limitations. First, the accuracy of brain biopsy was assessed by manually superimposing the images. In the 3D-BBG evaluation, prebiopsy and postbiopsy 3-D SBTMs were overlaid, whereas in the EM neuronavigation assessment, neuronavigation planning images were aligned with postbiopsy 3-D models. Despite efforts to minimize errors by using cube reference markers during SBTM production and conducting assessments with CAD software, some human errors may still be present. Second, this study was not conducted in vivo. Although SBTM has several advantages, it also has limitations. The SBTM was made with 1.5% agarose gel, which is stiffer than real brain tissue, potentially affecting biopsy accuracy.41 Furthermore, since the SBTM does not accurately represent actual intracranial pressure conditions, sample quantity affected by pressure was not assessed. Consequently, sample validation relied solely on the presence of blue agarose gel, as histopathological examination was not possible in this nonliving model. Third, the sample selection criteria were not restricted. Attempts to demonstrate feasibility across various breeds, sizes, and head shapes may have compromised the consistency of the experimental results. Therefore, future studies should focus on selecting patients of specific breeds and head shapes when producing SBTMs for experimentation.
We compared the accuracy of brain biopsy using 3D-BBG and EM neuronavigation in SBTMs of dogs and cats of various breeds, sizes, and head shapes created using 3-D–printing technology. By reconstructing 3-D models from prebiopsy and postbiopsy CT data and analyzing biopsy accuracy using CAD software, we concluded that there was no significant difference in accuracy between 3D-BBG and EM neuronavigation. Therefore, when performing a brain biopsy for the diagnosis of brain tumors, the method can be chosen based on the veterinarian’s preference, the veterinary hospital’s resources, and the patient’s condition.
Acknowledgments
None reported.
Disclosures
The authors have nothing to disclose. No AI-assisted technologies were used in the generation of this manuscript.
Funding
This work was supported by a National Research Foundation of Korea grant, funded by the Korean government (Ministry of Science and Information and Communications Technology; RS-2023–00278989).
References
- 1.↑
Zaki FA, Hurvitz AI. Spontaneous neoplasms of the central nervous system of the cat. J Small Anim Pract. 1976;17(12):773–782. doi:10.1111/j.1748-5827.1976.tb06943.x
- 2.
Song RB, Vite CH, Bradley CW, Cross JR. Postmortem evaluation of 435 cases of intracranial neoplasia in dogs and relationship of neoplasm with breed, age, and body weight. J Vet Intern Med. 2013;27(5):1143–1152. doi:10.1111/jvim.12136
- 3.
de Robles P, Fiest KM, Frolkis AD, et al. The worldwide incidence and prevalence of primary brain tumors: a systematic review and meta-analysis. Neuro Oncol. 2015;17(6):776–783. doi:10.1093/neuonc/nou283
- 4.↑
May JL, Garcia-Mora J, Edwards M, Rossmeisl JH. An illustrated scoping review of the magnetic resonance imaging characteristics of canine and feline brain tumors . Animals (Basel). 2024;14(7):1044. doi:10.3390/ani14071044
- 5.↑
Koblik PD, LeCouteur RA, Higgins RJ, et al. CT-guided brain biopsy using a modified pelorus mark III stereotactic system: experience with 50 dogs. Vet Radiol Ultrasound. 1999;40(5):434–440. doi:10.1111/j.1740-8261.1999.tb00371.x
- 6.↑
Troxel MT, Vite CH, Massicotte C, et al. Magnetic resonance imaging features of feline intracranial neoplasia: retrospective analysis of 46 cats. J Vet Intern Med. 2004;18(2):176–189. doi:10.1111/j.1939-1676.2004.tb00158.x
- 7.↑
Cherubini GB, Mantis P, Martinez TA, Lamb CR, Cappello R. Utility of magnetic resonance imaging for distinguishing neoplastic from non-neoplastic brain lesions in dogs and cats. Vet Radiol Ultrasound. 2005;46(5):384–387. doi:10.1111/j.1740-8261.2005.00069.x
- 8.↑
Wolff CA, Holmes SP, Young BD, et al. Magnetic resonance imaging for the differentiation of neoplastic, inflammatory, and cerebrovascular brain disease in dogs. J Vet Intern Med. 2012;26(3):589–597. doi:10.1111/j.1939-1676.2012.00899.x
- 9.
Young BD, Fosgate GT, Holmes SP, et al. Evaluation of standard magnetic resonance characteristics used to differentiate neoplastic, inflammatory, and vascular brain lesions in dogs. Vet Radiol Ultrasound. 2014;55(4):399–406. doi:10.1111/vru.12137
- 10.↑
Gutmann S, Winkler D, Muller M, et al. Accuracy of a magnetic resonance imaging-based 3D printed stereotactic brain biopsy device in dogs. J Vet Intern Med. 2020;34(2):844–851. doi:10.1111/jvim.15739
- 11.↑
Shinn R, Park C, DeBose K, Hsu FC, Cecere T, Rossmeisl J. Feasibility and accuracy of 3D printed patient-specific skull contoured brain biopsy guides. Vet Surg. 2021;50(5):933–943. doi:10.1111/vsu.13641
- 12.↑
Gutmann S, Tastensen C, Bottcher IC, et al. Clinical use of a new frameless optical neuronavigation system for brain biopsies: 10 cases (2013–2020). J Small Anim Pract. 2022;63(6):468–481. doi:10.1111/jsap.13482
- 13.↑
Rossmeisl JH Jr, Jones JC, Zimmerman KL, Robertson JL. Survival time following hospital discharge in dogs with palliatively treated primary brain tumors. J Am Vet Med Assoc. 2013;242(2):193–198. doi:10.2460/javma.242.2.193
- 14.↑
Chen AV, Wininger FA, Frey S, et al. Description and validation of a magnetic resonance imaging-guided stereotactic brain biopsy device in the dog. Vet Radiol Ultrasound. 2012;53(2):150–156. doi:10.1111/j.1740-8261.2011.01889.x
- 15.↑
Muller M, Winkler D, Mobius R, et al. A concept for a 3D-printed patient-specific stereotaxy platform for brain biopsy–a canine cadaver study. Res Vet Sci. 2019;124:79–84. doi:10.1016/j.rvsc.2019.02.007
- 16.↑
Grimm F, Naros G, Gutenberg A, Keric N, Giese A, Gharabaghi A. Blurring the boundaries between frame-based and frameless stereotaxy: feasibility study for brain biopsies performed with the use of a head-mounted robot. J Neurosurg. 2015;123(3):737–742. doi:10.3171/2014.12.JNS141781
- 17.↑
Spennato P, Ruggiero C, Mirone G, Imperato A, Parlato RS, Cinalli G. Endoscopic needle biopsy of thalamic tumors: technical note. Childs Nerv Syst. 2020;36(11):2835–2840. doi:10.1007/s00381-020-04676-6
- 18.↑
Shores A, Brisson BA. Advanced Techniques in Canine and Feline Neurosurgery. John Wiley & Sons; 2023: 179–189.
- 19.↑
She C, Sun Z, Zhang Z, et al. Noninvasive targeting system with three-dimensionally printed customized device in stereotactic brain biopsy. World Neurosurg. 2024;183:e649–e657. doi:10.1016/j.wneu.2023.12.161
- 20.↑
Shinn RL, Hollingsworth C, Parker RL, Rossmeisl JH, Werre SR. Comparison of stereotactic brain biopsy techniques in dogs: neuronavigation, 3D-printed guides, and neuronavigation with 3D-printed guides. Front Vet Sci. 2024;11:1406928. doi:10.3389/fvets.2024.1406928
- 21.↑
Meneses F, Maiolini A, Forterre F, Oevermann A, Schweizer-Gorgas D. Feasability of a frameless brain biopsy system for companion animals using cone-beam CT-based automated registration. Front Vet Sci. 2021;8:779845. doi:10.3389/fvets.2021.779845
- 22.↑
Adams BS, Marino DJ, Loughin CA, et al. Evaluation of an ultrasound-guided freeze-core biopsy system for canine and feline brain tumors. Front Vet Sci. 2024;11:1284097. doi:10.3389/fvets.2024.1284097
- 23.↑
Miller AD, Miller CR, Rossmeisl JH. Canine primary intracranial cancer: a clinicopathologic and comparative review of glioma, meningioma, and choroid plexus tumors. Front Oncol. 2019;9:1151. doi:10.3389/fonc.2019.01151
- 24.↑
Troxel MT, Vite CH. CT-guided stereotactic brain biopsy using the Kopf stereotactic system. Vet Radiol Ultrasound. 2008;49(5):438–443. doi:10.1111/j.1740-8261.2008.00403.x
- 25.↑
Gutmann S, Heiderhoff M, Mobius R, Siegel T, Flegel T. Application accuracy of a frameless optical neuronavigation system as a guide for craniotomies in dogs. Acta Vet Scand. 2023;65(1):54. doi:10.1186/s13028-023-00720-y
- 26.↑
Fedorov A, Beichel R, Kalpathy-Cramer J, et al. 3D slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging. 2012;30(9):1323–1341. doi:10.1016/j.mri.2012.05.001
- 27.↑
Alpak H, Mutus R, Onar V. Correlation analysis of the skull and long bone measurements of the dog. Ann Anat. 2004;186(4):323–330. doi:10.1016/S0940-9602(04)80050-5
- 28.
Helton WS. Cephalic index and perceived dog trainability. Behav Processes. 2009;82(3):355–358. doi:10.1016/j.beproc.2009.08.004
- 29.↑
Hermanson JW, De Lahunta A. Miller and Evans’ Anatomy of the Dog. Elsevier Health Sciences; 2018: 91–140.
- 30.↑
Roh YH, Cho CW, Ryu CH, Lee JH, Jeong SM, Lee HB. Comparison between novice and experienced surgeons performing corrective osteotomy with patient-specific guides in dogs based on resulting position accuracy. Vet Sci. 2021;8(3):40. doi:10.3390/vetsci8030040
- 31.↑
Mongen MA, Willems PWA. Current accuracy of surface matching compared to adhesive markers in patient-to-image registration. Acta Neurochir (Wien). 2019;161(5):865–870. doi:10.1007/s00701-019-03867-8
- 32.↑
Taylor AR, Cohen ND, Fletcher S, Griffin JF, Levine JM. Application and machine accuracy of a new frameless computed tomography-guided stereotactic brain biopsy system in dogs. Vet Radiol Ultrasound. 2013;54(4):332–342. doi:10.1111/vru.12025
- 33.↑
Naftulin JS, Kimchi EY, Cash SS. Streamlined, inexpensive 3D printing of the brain and skull. PLoS One. 2015;10(8):e0136198. doi:10.1371/journal.pone.0136198
- 34.
Ploch CC, Mansi C, Jayamohan J, Kuhl E. Using 3D printing to create personalized brain models for neurosurgical training and preoperative planning. World Neurosurg. 2016;90:668–674. doi:10.1016/j.wneu.2016.02.081
- 35.
Sidhu DS, Ruth JD, Lambert G, Rossmeisl JH. An easy to produce and economical three-dimensional brain phantom for stereotactic computed tomographic-guided brain biopsy training in the dog. Vet Surg. 2017;46(5):621–630. doi:10.1111/vsu.12657
- 36.
Bainier M, Su A, Redondo RL. 3D printed rodent skin-skull-brain model: a novel animal-free approach for neurosurgical training. PLoS One. 2021;16(6):e0253477. doi:10.1371/journal.pone.0253477
- 37.↑
Dho YS, Lee D, Ha T, et al. Clinical application of patient-specific 3D printing brain tumor model production system for neurosurgery. Sci Rep. 2021;11(1):7005. doi:10.1038/s41598-021-86546-y
- 38.↑
Encarnacion Ramirez M, Ramirez Pena I, Barrientos Castillo RE, et al. Development of a 3D printed brain model with vasculature for neurosurgical procedure visualisation and training. Biomedicines. 2023;11(2):330. doi:10.3390/biomedicines11020330
- 39.↑
Chartrain AG, Kellner CP, Fargen KM, et al. A review and comparison of three neuronavigation systems for minimally invasive intracerebral hemorrhage evacuation. J Neurointerv Surg. 2018;10(1):66–74. doi:10.1136/neurintsurg-2017-013091
- 40.↑
Gomar-Alba M, Guil-Ibanez JJ, Ruiz-Garcia JL, et al. Dynamic workflow proposal for continuous frameless electromagnetic neuronavigation in rigid neuroendoscopy. World Neurosurg. 2024;187:19–28. doi:10.1016/j.wneu.2024.04.008
- 41.↑
Pervin F, Chen WW. Mechanically similar gel simulants for brain tissues. Dynamic Behavior of Materials. 2011;1:9–13. doi:10.1007/978-1-4419-8228-5_3
