AIMC Topic: Spinal Neoplasms

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Development of Machine Learning Algorithms for Prediction of 5-Year Spinal Chordoma Survival.

World neurosurgery Aug 8, 2018
BACKGROUND: Chordomas are locally invasive slow-growing tumors that are difficult to study because of the rarity of the tumors and the lack of significant volumes of patients with longitudinal follow-up. As such, there are currently no machine learni...
Age of Onset Spinal Neoplasms Chordoma SEER Program Survival Analysis Tumor Burden Middle Aged United States Bayes Theorem Humans Machine Learning Aged Male Algorithms Female
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Deep convolutional neural network-based segmentation and classification of difficult to define metastatic spinal lesions in 3D CT data.

Medical image analysis Aug 3, 2018
This paper aims to address the segmentation and classification of lytic and sclerotic metastatic lesions that are difficult to define by using spinal 3D Computed Tomography (CT) images obtained from highly pathologically affected cases. As the lesion...
Neural Networks, Computer Tomography, X-Ray Computed Humans Spinal Neoplasms Male Female Middle Aged Imaging, Three-Dimensional Aged Radiographic Image Interpretation, Computer-Assisted Aged, 80 and over
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A multi-resolution approach for spinal metastasis detection using deep Siamese neural networks.

Computers in biology and medicine Mar 27, 2017
Spinal metastasis, a metastatic cancer of the spine, is the most common malignant disease in the spine. In this study, we investigate the feasibility of automated spinal metastasis detection in magnetic resonance imaging (MRI) by using deep learning ...
ROC Curve Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Spinal Neoplasms Aged Male Middle Aged Humans Neural Networks, Computer Female
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Inverse treatment planning for spinal robotic radiosurgery: an international multi-institutional benchmark trial.

Journal of applied clinical medical physics May 8, 2016
Stereotactic radiosurgery (SRS) is the accurate, conformal delivery of high-dose radiation to well-defined targets while minimizing normal structure doses via steep dose gradients. While inverse treatment planning (ITP) with computerized optimization...
Humans Algorithms Robotics Radiotherapy Dosage Benchmarking Radiosurgery Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted International Agencies Spinal Neoplasms
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Improving Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation.

IEEE transactions on medical imaging Sep 28, 2015
Automated computer-aided detection (CADe) has been an important tool in clinical practice and research. State-of-the-art methods often show high sensitivities at the cost of high false-positives (FP) per patient rates. We design a two-tiered coarse-t...
Spinal Neoplasms Lymph Nodes Aged Radiographic Image Interpretation, Computer-Assisted Colonic Polyps Young Adult Databases, Factual Adult Tomography, X-Ray Computed Female Humans Male Neural Networks, Computer Middle Aged Machine Learning Adolescent Child
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Zero-shot segmentation of spinal vertebrae with metastatic lesions: an analysis of Meta's Segment Anything Model 2 and factors affecting learning free segmentation.

Neurosurgical focus Jul 1, 2025
OBJECTIVE: Accurate vertebral segmentation is an important step in imaging analysis pipelines for diagnosis and subsequent treatment of spinal metastases. Segmenting these metastases is especially challenging given their radiological heterogeneity. C...
Humans Tomography, X-Ray Computed Middle Aged Deep Learning Female Spine Aged Spinal Neoplasms Male
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A prospectively deployed deep learning-enabled automated quality assurance tool for oncological palliative spine radiation therapy.

The Lancet. Digital health Jan 1, 2025
BACKGROUND: Palliative spine radiation therapy is prone to treatment at the wrong anatomic level. We developed a fully automated deep learning-based spine-targeting quality assurance system (DL-SpiQA) for detecting treatment at the wrong anatomic lev...
Palliative Care Spinal Neoplasms Algorithms Prospective Studies Spine Retrospective Studies Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care Male Deep Learning Tomography, X-Ray Computed Humans Female
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Predicting 90-Day and 1-Year Mortality in Spinal Metastatic Disease: Development and Internal Validation.

Neurosurgery Oct 1, 2019
BACKGROUND: Increasing prevalence of metastatic disease has been accompanied by increasing rates of surgical intervention. Current tools have poor to fair predictive performance for intermediate (90-d) and long-term (1-yr) mortality.
Humans Retrospective Studies Female Reproducibility of Results Aged Neural Networks, Computer Machine Learning Algorithms Time Factors Predictive Value of Tests Survival Rate Male Spinal Neoplasms Middle Aged
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Development of Machine Learning Algorithms for Prediction of 30-Day Mortality After Surgery for Spinal Metastasis.

Neurosurgery Jul 1, 2019
BACKGROUND: Preoperative prognostication of short-term postoperative mortality in patients with spinal metastatic disease can improve shared decision making around end-of-life care.
Neurosurgical Procedures Spinal Neoplasms Clinical Decision Rules Female Male Middle Aged Algorithms Prognosis Humans Machine Learning
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