Incidence and imaging characteristics of difficult to detect retrospectively identified brain metastases in patients receiving repeat courses of stereotactic radiosurgery.

PURPOSE: During stereotactic radiosurgery (SRS) planning for brain metastases (BM), brain MRIs are reviewed to select appropriate targets based on radiographic characteristics. Some BM are difficult to detect and/or definitively identify and may go untreated initially, only to become apparent on future imaging. We hypothesized that in patients receiving multiple courses of SRS, reviewing the initial planning MRI would reveal early evidence of lesions that developed into metastases requiring SRS. METHODS: Patients undergoing two or more courses of SRS to BM within 6 months between 2016 and 2018 were included in this single-institution, retrospective study. Brain MRIs from the initial course were reviewed for lesions at the same location as subsequently treated metastases; if present, this lesion was classified as a "retrospectively identified metastasis" or RIM. RIMs were subcategorized as meeting or not meeting diagnostic imaging criteria for BM (+ DC or -DC, respectively). RESULTS: Among 683 patients undergoing 923 SRS courses, 98 patients met inclusion criteria. There were 115 repeat courses of SRS, with 345 treated metastases in the subsequent course, 128 of which were associated with RIMs found in a prior MRI. 58% of RIMs were + DC. 17 (15%) of subsequent courses consisted solely of metastases associated with + DC RIMs. CONCLUSION: Radiographic evidence of brain metastases requiring future treatment was occasionally present on brain MRIs from prior SRS treatments. Most RIMs were + DC, and some subsequent SRS courses treated only + DC RIMs. These findings suggest enhanced BM detection might enable earlier treatment and reduce the need for additional SRS.

How dimensions can guide surgical planning and training: a systematic review of Kambin's triangle.

OBJECTIVE: The authors sought to analyze the current literature to determine dimensional trends across the lumbar levels of Kambin's triangle, clarify the role of imaging techniques for preoperative planning, and understand the effect of inclusion of the superior articular process (SAP). This compiled knowledge of the triangle is needed to perform successful procedures, reduce nerve root injuries, and help guide surgeons in training. METHODS: The authors performed a search of multiple databases using combinations of keywords: Kambin's triangle, size, measurement, safe triangle, and bony triangle. Articles were included if their main findings included measurement of Kambin's triangle. The PubMed, Scopus, Ovid, Cochrane, Embase, and Medline databases were systematically searched for English-language articles with no time frame restrictions through July 2022. RESULTS: Eight studies comprising 132 patients or cadavers were included in the study. The mean ± SD age was 66.69 ± 9.6 years, and 53% of patients were male. Overall, the size of Kambin's triangle increased in area moving down vertebral levels, with L5-S1 being the largest (133.59 ± 4.36 mm2). This trend followed a linear regression model when SAP was kept (p = 0.008) and removed (p = 0.003). There was also a considerable increase in the size of Kambin's triangle if the SAP was removed. CONCLUSIONS: Here, the authors have provided the first reported systematic review of the literature of Kambin's triangle, its measurements at each lumbar level, and key areas of debate related to the definition of the working safe zone. These findings indicate that CT is heavily utilized for imaging of the safe zone, the area of Kambin's triangle tends to increase caudally, and variation exists between patients. Future studies should focus on using advanced imaging techniques for preoperative planning and establishing guidelines for surgeons.

Implementation of Clinical Artificial Intelligence in Radiology: Who Decides and How?

As the role of artificial intelligence (AI) in clinical practice evolves, governance structures oversee the implementation, maintenance, and monitoring of clinical AI algorithms to enhance quality, manage resources, and ensure patient safety. In this article, a framework is established for the infrastructure required for clinical AI implementation and presents a road map for governance. The road map answers four key questions: Who decides which tools to implement? What factors should be considered when assessing an application for implementation? How should applications be implemented in clinical practice? Finally, how should tools be monitored and maintained after clinical implementation? Among the many challenges for the implementation of AI in clinical practice, devising flexible governance structures that can quickly adapt to a changing environment will be essential to ensure quality patient care and practice improvement objectives.

Effects of age and sex on the distribution and symmetry of lumbar spinal and neural foraminal stenosis: a natural language processing analysis of 43,255 lumbar MRI reports.

PURPOSE: The purpose of this study is to investigate relationship of patient age and sex to patterns of degenerative spinal stenosis on lumbar MRI (LMRI), rated as moderate or greater by a spine radiologist, using natural language processing (NLP) tools. METHODS: In this retrospective, IRB-approved study, LMRI reports acquired from 2007 to 2017 at a single institution were parsed with a rules-based natural language processing (NLP) algorithm for free-text descriptors of spinal canal stenosis (SCS) and neural foraminal stenosis (NFS) at each of six spinal levels (T12-S1) and categorized according to a 6-point grading scale. Demographic differences in the anatomic distribution of moderate (grade 3) or greater SCS and NFS were calculated by sex, and age and within-group differences for NFS symmetry (left vs. right) were calculated as odds ratios. RESULTS: Forty-three thousand two hundred fifty-five LMRI reports (34,947 unique patients, mean age = 54.7; sex = 54.9% women) interpreted by 152 radiologists were studied. Prevalence of significant SCS and NFS increased caudally from T12-L1 to L4-5 though less at L5-S1. NFS was asymmetrically more prevalent on the left at L2-L3 and L5-S1 (p < 0.001). SCS and NFS were more prevalent in men and SCS increased with age at all levels, but the effect size of age was largest at T12-L3. Younger patients (< 50 years) had relatively higher NFS prevalence at L5-S1. CONCLUSION: NLP can identify patterns of lumbar spine degeneration through analysis of a large corpus of radiologist interpretations. Demographic differences in stenosis prevalence shed light on the natural history and pathogenesis of LSDD.

The Composite Severity Score for Lumbar Spine MRI: a Metric of Cumulative Degenerative Disease Predicts Time Spent on Interpretation and Reporting.

Conventional measures of radiologist efficiency, such as the relative value unit, fail to account for variations in the complexity and difficulty of a given study. For lumbar spine MRI (LMRI), an ideal performance metric should account for the global severity of lumbar degenerative disease (LSDD) which may influence reporting time (RT), thereby affecting clinical productivity. This study aims to derive a global LSDD metric and estimate its effect on RT. A 10-year archive of LMRI reports comprising 13,388 exams was reviewed. Objective reporting timestamps were used to calculate RT. A natural language processing (NLP) tool was used to extract radiologist-assigned stenosis severity using a 6-point scale (0 = "normal" to 5 = "severe") at each lumbar level. The composite severity score (CSS) was calculated as the sum of each of 18 stenosis grades. The predictive values of CSS, sex, age, radiologist identity, and referring service on RT were examined with multiple regression models. The NLP tool accurately classified LSDD in 94.8% of cases in a validation set. The CSS increased with patient age and differed between men and women. In a univariable model, CSS was a significant predictor of mean RT (R2 = 0.38, p < 0.001) and independent predictor of mean RT (p < 0.001) controlling for patient sex, patient age, service location, and interpreting radiologist. The predictive strength of CSS was stronger for the low CSS range (CSS = 0-25, R2 = 0.83, p < 0.001) compared to higher CSS values (CSS > 25, R2 = 0.15, p = 0.05). Individual radiologist study volume was negatively correlated with mean RT (Pearson's R = - 0.35, p < 0.001). The composite severity score predicts radiologist reporting efficiency in LMRI, providing a quantitative measure of case complexity which may be useful for workflow planning and performance evaluation.

A Conference-Friendly, Hands-on Introduction to Deep Learning for Radiology Trainees.

Artificial or augmented intelligence, machine learning, and deep learning will be an increasingly important part of clinical practice for the next generation of radiologists. It is therefore critical that radiology residents develop a practical understanding of deep learning in medical imaging. Certain aspects of deep learning are not intuitive and may be better understood through hands-on experience; however, the technical requirements for setting up a programming and computing environment for deep learning can pose a high barrier to entry for individuals with limited experience in computer programming and limited access to GPU-accelerated computing. To address these concerns, we implemented an introductory module for deep learning in medical imaging within a self-contained, web-hosted development environment. Our initial experience established the feasibility of guiding radiology trainees through the module within a 45-min period typical of educational conferences.

Dual-Energy CT to Differentiate Small Foci of Intracranial Hemorrhage from Calcium.

Background Diagnostic uncertainty in CT of possible intracranial hemorrhage requires short-interval follow-up imaging, resulting in reduced efficiency of care and higher costs. Purpose To quantify the diagnostic performance of dual-energy CT versus simulated single-energy CT in the differentiation of small foci of intracranial hemorrhage from calcium. Materials and Methods Images from consecutive unenhanced dual-energy CT of the head in patients from a single emergency department obtained from December 2014 to April 2016 were reviewed retrospectively for hyperattenuating intracranial foci. Ground truth was established from reference standard comparison CT or MRI. Foci were divided into development and test sets. Development set foci regions of interest were used to derive candidate CT attenuation thresholds for virtual noncalcium (VNCa) and calcium images. Test set foci were used for threshold validation, and diagnostic performance and confidence were evaluated for two readers blinded to final diagnosis. Statistical comparisons were made with exact binomial tests or repeated-measures analysis of variance. Results The study included 137 patients (65 years ± 17; 70 men) with 146 foci. Foci were divided into a development set (n = 105) and a test set (n = 41). Quantitative analysis of the development set produced candidate thresholds of 44 HU for VNCa images and 7 HU for calcium-only images, yielding diagnostic accuracies for the test set of 88% (36 of 41 foci; 95% confidence interval [CI]: 78%, 98%) and 95% (39 of 41 foci; 95% CI: 88%, 100%), respectively. Dual-energy CT improved reader accuracy from 90% (reader 1, 37 of 41 foci; 95% CI: 81%, 99%) and 93% (reader 2, 38 of 41 foci; 95% CI: 85%, 100%) to 100% (both readers, 41 of 41 foci; 95% CI: 100%, 100%). Diagnostic confidence (classifications rated as "certain") increased from 71% (29 of 41 foci; 95% CI: 57%, 85%) to 90% (37 of 41 foci; 95% CI: 81%, 99%) for reader 1 (P = .019) and from 46% (19 of 41 foci; 95% CI: 31%, 62%) to 85% (35 of 41 foci; 95% CI: 75%, 96%) for reader 2 (P = .0001). Conclusion Dual-energy CT showed high diagnostic performance in the differentiation of small foci of intracranial hemorrhage from calcium and improved diagnostic accuracy and confidence in the initial evaluation of suspected hemorrhage. © RSNA, 2019 See also the editorial by Kotsenas in this issue.

The "connecting vessel" sign: an imaging biomarker to differentiate ruptured infected (mycotic) intracranial aneurysm mimicking the CTA spot sign.

PURPOSE: Infected (mycotic) intracranial aneurysms (IIA) are a prevalent source of morbidity in patients with systemic infection. Unlike saccular aneurysms, ruptured IIA frequently presents with intracerebral hemorrhage (ICH), and the appearance of ruptured IIA on CTA overlaps with the CTA "Spot Sign" (SS), an imaging finding in non-infectious, spontaneous ICH. The purpose of this study was to investigate the imaging and clinical features which may differentiate these two entities on CTA for which treatment strategies differ substantially. METHODS: In an IRB-approved, retrospective case series, we compared 14 patients with confirmed IIA and 14 patients with positive SS due to other non-infectious etiology (SS(+) ICH). Clinical history, laboratory studies, and CTA reports and images were reviewed to define imaging characteristics of IIA and SS(+) ICH, including the diagnostic criteria for SS used in clinical trials. RESULTS: A total of 7/14 patients (50.0%) diagnosed with IIA had ICH at presentation. Of these, 3/7 patients (42.9%) with ruptured IIA and ICH met diagnostic imaging criteria of SS. The remaining 4/7 patients did not meet criteria due to presence of a connecting vessel. Compared with SS(+) ICH of non-infectious etiology, patients with ruptured IIA were younger (40.7 vs. 66.4 years) and had higher rates of IVDU and bacteremia (p < 0.01) and lower rates of hypertension (p < 0.01). Hematoma volume was similar in both groups, but lobar location was more frequent in ruptured IIA (p = 0.06). Mortality at 1 year from diagnosis was equally high in both groups (42.9%). CONCLUSION: This study characterizes ruptured IIA as an imaging mimic of SS and provides a framework for differentiating these lesions, allowing prompt diagnosis and appropriate treatment.

Non-traumatic subdural hemorrhage: beware of ruptured intracranial aneurysm.

Acute subdural hemorrhage (SDH) is commonly encountered by emergency radiologists in the setting of trauma. When history or imaging evidence of trauma is absent, the differential diagnosis for SDH should be expanded. Intracranial aneurysm rupture is a rare and underrecognized cause of SDH which may present without concurrent subarachnoid hemorrhage. The mechanism of aneurysmal SDH is controversial, but understanding the anatomic microenvironment of the aneurysm provides insight and clarifies aneurysm features predisposing to subdural compartment rupture. Aneurysmal SDH is a neurosurgical emergency and its treatment strategies differ from traumatic SDH. Outcomes are poor if treatment is delayed; thus, radiologists play a central role in recognizing this uncommon but potentially devastating complication of aneurysm rupture. The goal of this article is to familiarize radiologists with clinical and imaging characteristics of aneurysmal SDH and review pertinent anatomy, risk factors, and potential etiologies. Aneurysmal rupture can easily be overlooked in the routine workup of atraumatic SDH, and radiologists must know when to recommend vascular imaging to avoid the catastrophic consequences of a missed diagnosis.

BCNU wafer placement with temozolomide (TMZ) in the immediate postoperative period after tumor resection followed by radiation therapy with TMZ in patients with newly diagnosed high grade glioma: final results of a prospective, multi-institutional, phase II trial.

Temozolomide (TMZ) and BCNU have demonstrated anti-glioma synergism in preclinical models. We report final data from a prospective, multi-institutional study of BCNU wafers and early TMZ followed by radiation therapy with TMZ in patients with newly diagnosed malignant glioma. 65 patients were consented in 4 institutions, and 46 patients (43 GBM, 3 AA) were eligible for analysis. After resection and BCNU wafer placement, TMZ began on day four postoperatively. Radiation and TMZ (RT/TMZ) were then administered, followed by monthly TMZ at 200 mg/m2 for the first 26 patients, which was reduced to 150 mg/m2 for the remaining 20 patients. Non-hematologic toxicities were minimal. Nine of 27 patients (33 %) who received 200 mg/m2 TMZ, but only 1 of 20 (5 %) who received 150 mg/m2, experienced grade 3/4 thrombocytopenia. Median progression free survival (PFS) and overall survival (OS) period was 8.5 and 18 months, respectively. The 1-year OS rate was 76 %, which is a significant improvement compared with the historical control 1-year OS rate of 59 % (p = 0.023). However, there was no difference in 1-year OS compared with standard RT/TMZ (p = 0.12) or BCNU wafer followed by RT/TMZ (p = 0.87) in post hoc analyses. Early post-operative TMZ can be safely administered with BCNU wafers following resection of malignant glioma at the 150 mg/m2 dose level. Although there was an OS benefit compared to historical control, there was no indication of benefit for BCNU wafers and early TMZ in addition to standard RT/TMZ or early TMZ in addition to regimens of BCNU wafers followed by RT/TMZ.

Automated selection of abdominal MRI series using a DICOM metadata classifier and selective use of a pixel-based classifier.

Accurate, automated MRI series identification is important for many applications, including display ("hanging") protocols, machine learning, and radiomics. The use of the series description or a pixel-based classifier each has limitations. We demonstrate a combined approach utilizing a DICOM metadata-based classifier and selective use of a pixel-based classifier to identify abdominal MRI series. The metadata classifier was assessed alone as Group metadata and combined with selective use of the pixel-based classifier for predictions with less than 70% certainty (Group combined). The overall accuracy (mean and 95% confidence intervals) for Groups metadata and combined on the test dataset were 0.870 CI (0.824,0.912) and 0.930 CI (0.893,0.963), respectively. With this combined metadata and pixel-based approach, we demonstrate accurate classification of 95% or greater for all pre-contrast MRI series and improved performance for some post-contrast series.

Using Augmented Reality Technology to Optimize Transfacet Lumbar Interbody Fusion: A Case Report.

The transfacet minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) is a novel approach available for the management of lumbar spondylolisthesis. It avoids the need to manipulate either of the exiting or traversing nerve roots, both protected by the bony boundaries of the approach. With the advancement in operative technologies such as navigation, mapping, segmentation, and augmented reality (AR), surgeons are prompted to utilize these technologies to enhance their surgical outcomes. A 36-year-old male patient was complaining of chronic progressive lower back pain. He was found to have grade 2 L4/5 spondylolisthesis. We studied the feasibility of a trans-Kambin or a transfacet MIS-TLIF, and decided to proceed with the latter given the wider corridor it provides. Preoperative trajectory planning and level segmentation in addition to intraoperative navigation and image merging were all utilized to provide an AR model to guide us through the surgery. The use of AR can build on the safety and learning of novel surgical approaches to spine pathologies. However, larger high-quality studies are needed to further objectively analyze its impact on surgical outcomes and to expand on its application.

Ethosuximide reduces ethanol withdrawal-mediated disruptions in sleep-related EEG patterns.

BACKGROUND: Chronic ethanol (EtOH) leads to disruptions in resting electroencephalogram (EEG) activity and in sleep patterns that can persist into the withdrawal period. These disruptions have been suggested to be predictors of relapse. The thalamus is a key structure involved in both normal brain oscillations, such as sleep-related oscillations, and abnormal rhythms found in disorders such as epilepsy and Parkinson's disease. Previously, we have shown progressive changes in mouse thalamic T-type Ca channels during chronic intermittent EtOH exposures that occurred in parallel with alterations in theta (4 to 8 Hz) EEG patterns. METHODS: Two groups of 8-week-old male C57BL/6 mice were implanted with wireless EEG/electromyogram (EMG) telemetry and subjected to 4 weeks of chronic, intermittent EtOH vapor exposure and withdrawal. During the week after the final withdrawal, mice were administered ethosuximide (ETX; 200 mg/kg) or saline. EEG data were analyzed via discrete Fourier transform, and sleep-scored for further analysis. RESULTS: Chronic intermittent EtOH exposure produced changes in the diurnal rhythms of the delta (0.5 to 4 Hz) and theta bands that persisted into a subsequent week of sustained withdrawal. These disruptions were restored with the T-channel blocker ETX. Repeated EtOH exposures preferentially increased the relative proportion of lower frequency power (delta and theta), whereas higher frequencies (8 to 24 Hz) were decreased. The EtOH-induced decreases in relative power for the higher frequencies continued into the sustained withdrawal week for both groups. Increases in absolute delta and theta power were observed in averaged nonrapid eye movement and rapid eye movement sleep spectral data during withdrawal in ETX-treated animals, suggesting increased sleep intensity. CONCLUSIONS: These results suggest that persistent alterations in delta and theta EEG rhythms during withdrawal from chronic intermittent EtOH exposure can be ameliorated with ETX and that this treatment might also increase sleep intensity during withdrawal.

Duke Liver Dataset: A Publicly Available Liver MRI Dataset with Liver Segmentation Masks and Series Labels.

The Duke Liver Dataset contains 2146 abdominal MRI series from 105 patients, including a majority with cirrhotic features, and 310 image series with corresponding manually segmented liver masks.

A Deep Learning-Based Computer Aided Detection (CAD) System for Difficult-to-Detect Brain Metastases.

PURPOSE: We sought to develop a computer-aided detection (CAD) system that optimally augments human performance, excelling especially at identifying small inconspicuous brain metastases (BMs), by training a convolutional neural network on a unique magnetic resonance imaging (MRI) data set containing subtle BMs that were not detected prospectively during routine clinical care. METHODS AND MATERIALS: Patients receiving stereotactic radiosurgery (SRS) for BMs at our institution from 2016 to 2018 without prior brain-directed therapy or small cell histology were eligible. For patients who underwent 2 consecutive courses of SRS, treatment planning MRIs from their initial course were reviewed for radiographic evidence of an emerging metastasis at the same location as metastases treated in their second SRS course. If present, these previously unidentified lesions were contoured and categorized as retrospectively identified metastases (RIMs). RIMs were further subcategorized according to whether they did (+DC) or did not (-DC) meet diagnostic imaging-based criteria to definitively classify them as metastases based upon their appearance in the initial MRI alone. Prospectively identified metastases (PIMs) from these patients, and from patients who only underwent a single course of SRS, were also included. An open-source convolutional neural network architecture was adapted and trained to detect both RIMs and PIMs on thin-slice, contrast-enhanced, spoiled gradient echo MRIs. Patients were randomized into 5 groups: 4 for training/cross-validation and 1 for testing. RESULTS: One hundred thirty-five patients with 563 metastases, including 72 RIMS, met criteria. For the test group, CAD sensitivity was 94% for PIMs, 80% for +DC RIMs, and 79% for PIMs and +DC RIMs with diameter <3 mm, with a median of 2 false positives per patient and a Dice coefficient of 0.79. CONCLUSIONS: Our CAD model, trained on a novel data set and using a single common MR sequence, demonstrated high sensitivity and specificity overall, outperforming published CAD results for small metastases and RIMs - the lesion types most in need of human performance augmentation.

Systematic Analysis of Common Factors Impacting Deep Learning Model Generalizability in Liver Segmentation.

Purpose: To investigate the effect of training data type on generalizability of deep learning liver segmentation models. Materials and Methods: This Health Insurance Portability and Accountability Act-compliant retrospective study included 860 MRI and CT abdominal scans obtained between February 2013 and March 2018 and 210 volumes from public datasets. Five single-source models were trained on 100 scans each of T1-weighted fat-suppressed portal venous (dynportal), T1-weighted fat-suppressed precontrast (dynpre), proton density opposed-phase (opposed), single-shot fast spin-echo (ssfse), and T1-weighted non-fat-suppressed (t1nfs) sequence types. A sixth multisource (DeepAll) model was trained on 100 scans consisting of 20 randomly selected scans from each of the five source domains. All models were tested against 18 target domains from unseen vendors, MRI types, and modality (CT). The Dice-Sørensen coefficient (DSC) was used to quantify similarity between manual and model segmentations. Results: Single-source model performance did not degrade significantly against unseen vendor data. Models trained on T1-weighted dynamic data generally performed well on other T1-weighted dynamic data (DSC = 0.848 ± 0.183 [SD]). The opposed model generalized moderately well to all unseen MRI types (DSC = 0.703 ± 0.229). The ssfse model failed to generalize well to any other MRI type (DSC = 0.089 ± 0.153). Dynamic and opposed models generalized moderately well to CT data (DSC = 0.744 ± 0.206), whereas other single-source models performed poorly (DSC = 0.181 ± 0.192). The DeepAll model generalized well across vendor, modality, and MRI type and against externally sourced data. Conclusion: Domain shift in liver segmentation appears to be tied to variations in soft-tissue contrast and can be effectively bridged with diversification of soft-tissue representation in training data.Keywords: Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms, Supervised Learning, CT, MRI, Liver Segmentation Supplemental material is available for this article. © RSNA, 2023.

Novel Merging of CT and MRI to Allow for Safe Navigation into Kambin's Triangle for Percutaneous Lumbar Interbody Fusion-Initial Case Series Investigating Safety and Efficacy.

BACKGROUND: For percutaneous lumbar fusion (percLIF), magnetic resonance imaging and computed tomography are critical to defining surgical corridors. Currently, these scans are performed separately, and surgeons then use fluoroscopy or neuromonitoring to guide instruments through Kambin's triangle. However, anatomic variations and intraoperative positional changes are possible, meaning that safely accessing Kambin's triangle remains a challenge because nerveroot visualization without endoscopes has not been thoroughly described. OBJECTIVE: To overcome the known challenges of percLIF and reduce the likelihood of iatrogenic injuries by showing real-time locations of neural and bony anatomy. METHODS: The authors demonstrate an intraoperative navigational platform that applies nerve root segmentation and image fusion to assist with percLIF. Five patients from a single institution were included. RESULTS: Of the 5 patients, the mean age was 71 ± 8 years and 3 patients (60%) were female. One patient had general anesthesia while the remaining 4 patients underwent awake surgery with spinal anesthesia. The mean area for the L4-L5 Kambin's triangle was 76.1 ± 14.5 mm 2 . A case example is shown where the side of approach was based on the fact that Kambin's triangle was larger on one side compared with the other. The mean operative time was 170 ± 17 minutes, the mean blood loss was 32 ± 16 mL, and the mean hospital length of stay was 19.6 ± 8.3 hours. No patients developed postoperative complications. CONCLUSION: This case series demonstrates the successful and safe application of nerve segmentation using magnetic resonance imaging/computed tomography fusion to perform percLIF and provide positive patient outcomes.

Two-Year Clinical and Radiographic Outcomes for Percutaneous Lumbar Interbody Fusion With an Expandable Titanium Cage Through Kambin's Triangle Without Facetectomy.

BACKGROUND: There has been heightened interest in performing percutaneous lumbar interbody fusions (percLIFs) through Kambin's triangle, an anatomic corridor allowing entrance into the disc space. However, due to its novelty, there are limited data regarding the long-term benefits of this procedure. Our objective was to determine the long-term efficacy and durability of the percutaneous insertion of an expandable titanium cage through Kambin's triangle without facetectomy. METHODS: A retrospective review of patients undergoing percLIF via Kambin's triangle using an expandable titanium cage was performed. Demographics, visual analog scale (VAS) scores, Oswestry Disability Index (ODI), radiographic measurements, perioperative variables, and complications were recorded. VAS, ODI, and radiographic measurements were compared with baseline using the generalized estimating equations assuming normally distributed data. Fusion was assessed with computed tomography (CT) at 1 and 2 years after the procedure. RESULTS: A total of 49 patients were included. Spondylolisthesis, lumbar lordosis (LL), sacral slope, pelvic tilt, and anterior/posterior disc space height were all significantly improved postoperatively at each time point of 3, 6, 12, and 24 months (P < 0.001). Pelvic incidence-LL mismatch decreased significantly at each follow-up (P < 0.001) with a mean reduction of 4° by 24 months. VAS back scores reduced by >2 points at the 6, 12, and 24 month follow-ups. ODI scores reduced by >15 points at the 12- and 24-month follow-ups. Of the patients who had 1- and 2-year CT images, fusion rates at those time points were 94.4% (17/18) and 87.5% (7/8), respectively. The mean annual rate of surgically significant adjacent segment disease was 2.74% through an average follow-up of 2.74 years. CONCLUSION: These results highlight that percLIF, a procedure done without an endoscope or facetectomy, can be performed using an expandable titanium cage through Kambin's triangle with excellent radiographic and clinical results. CLINICAL RELEVANCE: percLIF via Kambin's triangle is a safe and succesful procedure with long-term improvements in both clinical and radiographic outcomes.

Novel Approach to Percutaneous Lumbar Surgeries via Kambin's Triangle-Radiographic and Surgical Planning Analysis with Nerve Segmentation Technology.

OBJECTIVE: While Kambin's Triangle has become an ever more important anatomic window given its proximity to the exiting nerve root, there have been limited studies examining the effect of disease on the corridor. Our goal was to better understand how pathology can affect Kambin's Triangle, thereby altering the laterality of approach for percutaneous lumbar interbody fusion (percLIF). METHODS: The authors performed a single-center retrospective review of patients evaluated for percLIF. The areas of Kambin's Triangle were measured without and with nerve segmentation. For the latter, the lumbosacral nerve roots on 3-dimensional T2 magnetic resonance imaging were manually segmented. Next, the borders of Kambin's Triangle were delineated, ensuring no overlap between the area and nerve above. RESULTS: Fifteen patients (67.5 ± 9.7 years, 46.7% female) were retrospectively reviewed. We measured 150 Kambin's Triangles. The mean areas from L1-S1 were 50.0 ± 12.3 mm2, 73.8 ± 12.5 mm2, 83.8 ± 12.2 mm2, 88.5 ± 19.0 mm2, and 116 ± 29.3 mm2, respectively. When pathology was present, the areas significantly decreased at L4-L5 (P = 0.046) and L5-S1 (P = 0.049). Higher spondylolisthesis and smaller posterior disk heights were linked with decreased areas via linear regression analysis (P < 0.05). When nerve segmentation was used, the areas were significantly smaller from L1-L5 (P < 0.05). Among 11 patients who underwent surgery, none suffered from postoperative neuropathies. CONCLUSIONS: These results illustrate the feasibility of preoperatively segmenting lumbosacral nerves and measuring Kambin's Triangle to help guide surgical planning and determine the ideal laterality of approach for percLIF.