Citations

OBJECTIVE In this study, the authors aimed to establish a supervised machine learning (ML) model based on multiple tree-based algorithms to predict long-term biochemical outcomes and intervention-free survival (IFS) after endonasal transsphenoidal surgery (ETS) in patients with Cushing’s disease (CD). METHODS The medical records of patients who underwent ETS for CD between 2013 and 2023 were reviewed. Data were collected on the patient’s baseline characteristics, intervention details, histopathology, surgical outcomes, and postoperative endocrine functions. The study’s primary outcome was IFS, and the therapeutic outcomes were labeled as "under control" or "treatment failure," depending on whether additional therapeutic interventions after primary ETS were required. The decision tree and random forest classifiers were trained and tested to predict long-term IFS based on unseen data, using an 80/20 cohort split. RESULTS Data from 150 patients, with a median follow-up period of 56 months, were extracted. In the cohort, 42 (28%) patients required additional intervention for persistent or recurrent CD. Consequently, the IFS rates following ETS alone were 83% at 3 years and 78% at 5 years. Multivariable Cox proportional hazards analysis demonstrated that a smaller tumor diameter that could be detected by MRI (hazard ratio 0.95, 95% CI 0.90–0.99; p = 0.047) was significantly associated with greater IFS. However, the lack of tumor detection on MRI was a poor predictor. The ML-based model using a decision tree model displayed 91% accuracy (95% CI 0.70–0.94, sensitivity 87.0%, specificity 89.0%) in predicting IFS in the unseen test dataset. Random forest analysis revealed that tumor size (mean minimal depth 1.67), Knosp grade (1.75), patient age (1.80), and BMI (1.99) were the four most significant predictors of long-term IFS. CONCLUSIONS The ML algorithm could predict long-term postoperative endocrinological remission in CD with high accuracy, indicating that prognosis may vary not only with previously reported factors such as tumor size, Knosp grade, gross-total resection, and patient age but also with BMI. The decision tree flowchart could potentially stratify patients with CD before ETS, allowing for the selection of personalized treatment options and thereby assisting in determining treatment plans for these patients. This ML model may lead to a deeper understanding of the complex mechanisms of CD by uncovering patterns embedded within the data.

ObjectiveThe use of composite chondromucosal nasal septal flaps (ccNSF) has been demonstrated to be effective in cadaveric studies for the anterior skull base and the orbit. However, their application in the clinical setting remains unexplored. Our study aims to introduce a new method for treating palatal defects using ccNSF. Additionally, we studied the average NSF area and compared it to the average palate area.MethodsWe collected 108 CT scans from the medical records of patients without head and neck pathologies from a tertiary medical institution. We quantified the quadrangular (septal) cartilage and palate areas. Furthermore, we included a clinical case in which we used the ccNSF for the palatal defect reconstruction. This was to compare the mean area between the palate and the septal cartilage.ResultsThe ccNSF covered the palatal defect without any significant complications for the first 9 months of follow‐up. A total of 102 CT scans met the inclusion criteria and were measured. We found that the mean quadrangular cartilage had a length of 2.50 (±0.52) cm, a width of 2.28 (±0.51) cm, and an area of 5.43 (±1.68) cm2. The mean palate length was 2.73 (±0.44) cm, with a width of 3.13 (±0.34) cm, and area of 7.87 (±1.43) cm2.ConclusionsThe ccNSF proved successful in palatal defect reconstruction, resulting in positive outcomes and no major complications until the 9‐month follow‐up. The ccNSF is a useful flap that avoids the use of free flap transfer and its associated morbidities.Level of Evidence4 Laryngoscope, 134:4882–4887, 2024

BACKGROUND AND OBJECTIVES: Epilepsy is considered one of the most prevalent and severe chronic neurological disorders worldwide. Our study aims to analyze the national trends in different treatment modalities for individuals with drug-resistant epilepsy and investigate the outcomes associated with these procedural trends in the United States. METHODS: Using the National Inpatient Sample database from 2010 to 2020, patients with drug-resistant focal epilepsy who underwent laser interstitial thermal therapy (LITT), open surgical resection, vagus nerve stimulation (VNS), or responsive neurostimulation (RNS) were identified. Trend analysis was performed using piecewise joinpoint regression. Propensity score matching was used to compare outcomes between 10 years prepandemic before 2020 and the first peak of the COVID-19 pandemic. RESULTS: This study analyzed a total of 33 969 patients with a diagnosis of drug-resistant epilepsy, with 3343 patients receiving surgical resection (78%), VNS (8.21%), RNS (8%), and LITT (6%). Between 2010 and 2020, there was an increase in the use of invasive electroencephalography monitoring for seizure zone localization ( P = .003). There was an increase in the use of LITT and RNS ( P < .001), while the use of surgical resection and VNS decreased over time ( P < .001). Most of these patients (89%) were treated during the pre-COVID pandemic era (2010-2019), while a minority (11%) underwent treatment during the COVID pandemic (2020). After propensity score matching, the rate of pulmonary complications, postprocedural hematoma formation, and mortality were slightly higher during the pandemic compared with the prepandemic period ( P = .045, P = .033, and P = .026, respectively). CONCLUSION: This study indicates a relative decrease in the use of surgical resections, as a treatment for drug-resistant focal epilepsy. By contrast, newer, minimally invasive surgical approaches including LITT and RNS showed gradual increases in usage.

OBJECTIVE Chordomas are rare tumors that often recur regardless of surgery with negative margins and postoperative radiotherapy. The predictive accuracy of widely used immunohistochemical (IHC) markers in addressing the recurrence of skull base chordomas (SBCs) is yet to be determined. This study aimed to investigate IHC markers in the prediction of recurrence after SBC resection with adjuvant radiation therapy. METHODS The authors reviewed the records of patients who had treatment for SBC between January 2017 and June 2021 across the Mayo Clinic in Minnesota, Florida, and Arizona. Exclusion criteria included patients who had no histopathology or recurrence as an outcome. Histopathological markers included cytokeratin A1/A3 only, epithelial membrane antigen (EMA), S100 protein, pan-cytokeratin, IN1, GATA3, CAM5.2, OSCAR, and chondroid. Information from patient records was abstracted, including treatment, clinical and radiological follow-up duration, demographics, and histopathological factors. Decision tree and random forest classifiers were trained and tested to predict the recurrence based on unseen data using an 80/20 split. RESULTS A total of 38 patients with a diagnosis of SBC who underwent resection (gross-total resection: 42.1%; and subtotal resection: 57.9%) and radiation therapy were extracted from the medical records. The mean patient age was 48.2 (SD 19.6) years; most patients were male (n = 23; 60.5%) and White (n = 36; 94.7%). Pan-cytokeratin was associated with an increased risk of postoperative recurrence (OR 14.67, 95% CI 2.44–88.13; p = 0.00517) after resection and adjuvant radiotherapy. The decision tree analysis found pan-cytokeratin–positive tumors to have a 78% chance of being classified as a recurrence, with an accuracy of 75%. The distribution of minimal depth in the prediction of postoperative recurrence indicates that the most important variables were pan-cytokeratin, followed by cytokeratin A1/A3 and EMA. CONCLUSIONS The authors’ machine learning algorithm identified pan-cytokeratin as the largest contributor to recurrence among other IHC markers after SBC resection. Machine learning may facilitate the prediction of outcomes in rare tumors, such as chordomas.

OBJECTIVE Malignant melanotic nerve sheath tumors are rare tumors characterized by neoplastic melanin-producing Schwann cells. In this study, the authors report their institution’s experience in treating spinal and peripheral malignant melanotic nerve sheath tumors and compare their results with the literature. METHODS Data were collected from 8 patients who underwent surgical treatment for malignant melanotic nerve sheath tumors between 1996 and 2023 at Mayo Clinic and 63 patients from the literature. Time-to-event analyses were performed for the combined group of 71 cases to evaluate the risk of recurrence, metastasis, and death based on tumor location and type of treatment received. Unpaired 2-sample t-tests and Fisher’s exact tests were used to determine statistical significance between groups. RESULTS Between 1996 and 2023, 8 patients with malignant melanotic nerve sheath tumors underwent surgery at the authors’ institution, while 63 patients were identified in the literature. The authors’ patients and those in the literature had the same mean age at diagnosis (43 years). At the authors’ institution, 5 patients (63%) experienced metastasis, 6 patients (75%) experienced long-term recurrence, and 5 patients (62.5%) died. In the literature, most patients (60.3%) were males, with a peak incidence between the 4th and 5th decades of life. Nineteen patients (31.1%) were diagnosed with Carney complex. Nerve root tumors accounted for most presentations (n = 39, 61.9%). Moreover, 24 patients (38.1%) had intradural lesions, with 54.2% (n = 13) being intramedullary and 45.8% (n = 11) extramedullary. Most patients underwent gross-total resection (GTR) (n = 41, 66.1%), followed by subtotal resection (STR) (n = 12, 19.4%), STR with radiation therapy (9.7%), and GTR with radiation therapy (4.8%). Sixteen patients (27.6%) experienced metastasis, 23 (39.7%) experienced recurrence, and 13 (22%) died. Kaplan-Meier analyses showed no significant differences among treatment approaches in terms of recurrence-free, metastasis-free, and overall survival (p > 0.05). Similar results were obtained when looking at the differences with respect to intradural versus nerve root location of the tumor (p > 0.05). CONCLUSIONS Malignant melanotic nerve sheath tumors are rare tumors with a high potential for malignancy. They carry a dismal prognosis, with a pooled local recurrence rate of 42%, distant metastasis rate of 27%, and mortality rate of 26%. The findings from this study suggest a trend favoring the use of GTR alone or STR with radiation therapy over STR alone. Mortality was similar regardless, which highlights the need for the development of effective treatment options to improve survival in patients with melanotic schwannomas.

BACKGROUND AND OBJECTIVES: Nongeneral anesthesia (non-GA) spine surgery is growing in popularity and has facilitated earlier postoperative recovery, reduced cost, and fewer complications compared with spine surgery under general anesthesia (GA). Changes in reimbursement policies have been demonstrated to correlate with clinical practice; however, they have yet to be studied for GA vs non-GA spine procedures. We aimed to investigate trends in physician reimbursement for GA vs non-GA spine surgery in the United States. METHODS: We queried the ACS-NSQIP for GA and non-GA (regional, epidural, spinal, and anesthesia care/intravenous sedation) spine surgeries during 2011–2020. Work relative value units per operative hour (wRVUs/h) were retrieved for decompression or stabilization of the cervical, thoracic, and lumbar spine. Propensity score matching (1:1) was performed using all baseline variables. RESULTS: We included 474 706 patients who underwent spine decompression or stabilization procedures. GA was used in 472 248 operations, whereas 2458 operations were non-GA. The proportion of non-GA spine operations significantly increased during the study period. Operative times ( P < .001) and length of stays ( P < .001) were shorter in non-GA when compared with GA procedures. Non-GA lumbar procedures had significantly higher wRVUs/h when compared with the same procedures performed under GA (decompression; P < .001 and stabilization; P = .039). However, the same could not be said about cervicothoracic procedures. Lumbar decompression surgeries using non-GA witnessed significant yearly increase in wRVUs/h ( P < .01) contrary to GA ( P = .72). Physician reimbursement remained stable for procedures of the cervical or thoracic spine regardless of the anesthesia. CONCLUSION: Non-GA lumbar decompressions and stabilizations are associated with higher and increasing reimbursement trends (wRVUs/h) compared with those under GA. Reimbursement for cervical and thoracic surgeries was equal regardless of the type of anesthesia and being relatively stable during the study period. The adoption of a non-GA technique relative to the GA increased significantly during the study period.

OBJECTIVE Chordomas are slow-growing tumors derived from notochord remnants. Despite margin-negative excision and postoperative radiation therapy, spinal chordomas (SCs) often progress. The potential of immunohistochemical (IHC) markers, such as epithelial membrane antigen (EMA), combined with machine learning algorithms to predict long-term (≥ 12 months) postoperative tumor progression, has been understudied. The authors aimed to identify IHC markers using trained tree-based algorithms to predict long-term (≥ 12 months) postoperative tumor progression. METHODS The authors reviewed the records of patients who underwent resection of SCs between January 2017 and June 2021 across the Mayo Clinic enterprise. Demographics, type of treatment, histopathology, and other relevant clinical factors were abstracted from each patient’s record. Low tumor progression was defined as more than a 94.3-mm3 decrease in the tumor size at the latest radiographic follow-up. Decision trees and random forest classifiers were trained and tested to predict the long-term volumetric progression after an 80/20 data split. RESULTS Sixty-two patients diagnosed with and surgically treated for SC were identified, of whom 31 were found to have a more advanced tumor progression based on the tumor volume change cutoff of 94.3 mm3. The mean age was 54.3 ± 13.8 years, and most patients were male (62.9%) and White (98.4%). The most common treatment modality was subtotal resection with radiation therapy (35.5%), with proton beam therapy being the most common (71%). Most SCs were sacrococcygeal (41.9%), followed by cervical (32.3%). EMA-positive SCs had a postoperative progression risk of 67%. Pancytokeratin-positive SCs had a progression rate of 67%; however, patients with S100 protein–positive SCs had a 54% risk of progression. The accuracy of this model in predicting the progression of unseen test data was 66%. Pancytokeratin (mean minimal depth = 1.57), EMA (mean minimal depth = 1.58), cytokeratin A1/A3 (mean minimal depth = 1.59), and S100 protein (mean minimal depth = 1.6) predicted the long-term volumetric progression. Multiway variable importance plots show the relative importance of the top 10 variables based on three measures of varying significance and their predictive role. CONCLUSIONS These IHC variables with tree-based machine learning tools successfully demonstrate a high capacity to identify a patient’s tumor progression pattern with an accuracy of 66%. Pancytokeratin, EMA, cytokeratin A1/A3, and S100 protein were the IHC drivers of a low tumor progression. This shows the power of machine learning algorithms in analyzing and predicting outcomes of rare conditions in a small sample size.