The two identification methods gave different bacterial profiles, while both methods were sufficient to identify the most prevalent LAB in salted Chinese cabbage samples. The quantitative feature of the culture-dependent identification method would make it preferable for studying and monitoring LAB viability in kimchi at each fermentation stage. The availability of the culture-independent identification method to identify a broader bacterial profile, including non-LAB, would make it a more effective tool for controlling contamination of undesirable bacteria during kimchi fermentation.

BACKGROUND.The purpose of the study was to evaluate the growth kinetics of metastatic brain tumors during chemotherapy and to analyze growth rates and volumetric doubling time of metastatic brain tumors in patients with nonsmall cell lung cancer (NSCLC) with tumor regrowth.METHODS.NSCLC patients with minimally symptomatic brain metastases who were not treated previously were enrolled. Serial magnetic resonance images (MRI) of 30 metastatic brain tumors in 19 patients were reviewed. Tumor growth rates and volumetric tumor doubling time of tumor regrowth were estimated. All patients were treated with front‐line chemotherapy until disease progression.RESULTS.The median tumor growth rate was 12.10 mm3/day (interquartile range [IQR], 3.09‐36.75). The volume percentage increase/day was 1.67 (IQR, 0.69‐4.59). The median volumetric tumor doubling time was 58.48 days (IQR, 32.33‐98.48).CONCLUSIONS.These findings may help optimize patient management during follow‐up. Study results indicated that brain MRI should be obtained at a minimum of 2‐month intervals to screen for metastatic brain tumors. Cancer 2008. © 2008 American Cancer Society.

Study Design. Retrospective observational study. Objective. To demonstrate the clinical usefulness of deep learning by identifying previous spinal implants through application of deep learning. Summary of Background Data. Deep learning has recently been actively applied to medical images. However, despite many attempts to apply deep learning to medical images, the application has rarely been successful. We aimed to demonstrate the effectiveness and usefulness of deep learning in the medical field. The goal of this study was to demonstrate the clinical usefulness of deep learning by identifying previous spinal implants through application of deep learning. Methods. For deep learning algorithm development, radiographs were retrospectively obtained from clinical cases in which the patients had lumbar spine one-segment instrument surgery. A total of 2894 lumbar spine anteroposterior (AP: 1446 cases) and lateral (1448 cases) radiographs were collected. Labeling work was conducted for five different implants. We conducted experiments using three deep learning algorithms. The traditional deep neural network model built by coding the transfer learning algorithm, Google AutoML, and Apple Create ML. Recall (sensitivity) and precision (specificity) were measured after training. Results. Overall, each model performed well in identifying each pedicle screw implant. In conventional transfer learning, AP radiography showed 97.0% precision and 96.7% recall. Lateral radiography showed 98.7% precision and 98.2% recall. In Google AutoML, AP radiography showed 91.4% precision and 87.4% recall; lateral radiography showed 97.9% precision and 98.4% recall. In Apple Create ML, AP radiography showed 76.0% precision and 73.0% recall; lateral radiography showed 89.0% precision and 87.0% recall. In all deep learning algorithms, precision and recall were higher in lateral than in AP radiography. Conclusion. The deep learning application is effective for spinal implant identification. This demonstrates that clinicians can use ML-based deep learning applications to improve clinical practice and patient care. Level of Evidence: 3

Developing new surgical instruments is challenging. While making surgical instruments could be a good field of application for 3D printers, attempts to do so have proven limited. We designed a new endoscope-assisted spine surgery system, and using a 3D printer, attempted to create a complex surgical instrument and to evaluate the feasibility thereof. Developing the new surgical instruments using a 3D printer consisted of two parts: one part was the creation of a prototype instrument, and the other was the production of a patient model. We designed a new endoscope-assisted spine surgery system with a cannula for the endoscope and working instruments and extra cannula that could be easily added. Using custom-made patient-specific 3D models, we conducted discectomies for paramedian and foraminal discs with both the newly designed spine surgery system and conventional tubular surgery. The new spine surgery system had an extra portal that can be well bonded in by a magnetic connector and greatly expanded the range of access for instruments without unnecessary bone destruction. In foraminal discectomy, the newly designed spine surgery system showed less facet resection, compared to conventional surgery. We were able to develop and demonstrate the usefulness of a new endoscope-assisted spine surgery system relying on 3D printing technology. Using the extra portal, the usability of endoscope-assisted surgery could be greatly increased. We suggest that 3D printing technology can be very useful for the realization and evaluation of complex surgical instrument systems.

Degenerative lumbar foraminal stenosis is relatively common condition in which the circumferential narrowing of the space available for the nerve root leads to back pain and radicular symptoms. The preferred surgical treatment to relieve the compression of the nerve root has not been established yet. Recently, several reports have shown good clinical outcomes in patients who underwent biportal endoscopic decompression for the treatment of degenerative lumbar foraminal stenosis. The floating-type biportal endoscopic technique could be used with various surgical instruments without docking in the narrowed foramen, unlike the full-endoscopic technique. Multiple sites can be accessed with more freedom in the approaching angle through triangulation and portal switching. We reviewed articles to understand putative outcome factors and discuss the appropriate indications for biportal endoscopic foraminal decompression. Lumbar lordosis, degenerative lumbar scoliosis, height of the posterior intervertebral disc and level of procedure were all related to clinical outcomes. The best indications and contraindications to the endoscopic foraminal decompression still depends on the surgeon's skill level and evolving experience. However, we could suggest that biportal endoscopic spinal surgery is supposed to be an alternative treatment for foraminal decompression preserving motion and stability, and decreasing the need for fusion surgery in various lumbar degenerative disease.