[Management of spinal metastases of lung cancer]

Improved UNet Deep Learning Model for Automatic Detection of Lung Cancer Nodules

Uncontrolled cell growth in the two spongy lung organs in the chest is the most prevalent kind of cancer. When cells from the lungs spread to other tissues and organs, this is referred to as metastasis. This work uses image processing, deep learning, and metaheuristics to identify cancer in its early stages. At this point, a new convolutional neural network is constructed. The predator technique has the potential to increase network architecture and accuracy. Deep learning identified lung cancer spinal metastases in as energy consumption increased CT readings for lung cancer bone metastases decreased. Qualified physicians, on the other hand, discovered 71.14 and 74.60 percent of targets with energies of 140 and 60 keV, respectively, whereas the proposed model gives 76.51 and 81.58 percent, respectively. Expert physicians' detection rate was 74.60 percent lower than deep learning's detection rate of 81.58 percent. The proposed method has the highest accuracy, sensitivity, and specificity (93.4, 98.4, and 97.1 percent, respectively), as well as the lowest error rate (1.6 percent). Finally, in lung segmentation, the proposed model outperforms the CNN model. High-intensity energy-spectral CT images are more difficult to segment than low-intensity energy-spectral CT images.

Spinal metastases of bronchopulmonary cancer: Role of spinal surgery and value of prognostic scores (Modified Tokuhashi and Tomita)

INTRODUCTION

Bone metastasis is frequent in bronchopulmonary cancer. We report a series of 52 patients, and analyze indications and the efficacy of surgery.

MATERIALS AND METHODS

We retrospectively studied the records of 52 patients operated on for spinal metastases of bronchopulmonary cancer over a 6-year period from January 2009 to December 2014 in the neurosurgery department of the North Hospital of Marseille, France.

RESULTS

Mean age was 63.6 years; with a sex ratio of 3:1 (M:F). Spinal pain associated with vertebral fracture and spinal cord compression was the most frequent clinical presentation (59.6%). SINS score was ≥7 in 78.9% of cases. Karnofski Performance Status was average in 67.4% of cases. Predicted survival beyond 12 months was zero according to the modified Tokuhashi score. The surgical indication was essentially palliative. Evolution showed regression of pain in 84.6% of cases, and stabilization and improvement in motor deficit in 80.6%. Median postoperative survival was 16 months.

CONCLUSION

Our results highlight the interest of surgery for pain relief, spinal stabilization and improvement in neurological function in patients with spinal metastases of bronchopulmonary cancer, and the unreliability of predictive survival scores.