TdDS-UNet: top-down deeply supervised U-Net for the delineation of 3D colorectal cancer.

Automatically delineating colorectal cancers with fuzzy boundaries from 3D images is a challenging task, but the problem of fuzzy boundary delineation in existing deep learning-based methods have not been investigated in depth. Here, an encoder-decoder-based U-shaped network (U-Net) based on top-down deep supervision (TdDS) was designed to accurately and automatically delineate the fuzzy boundaries of colorectal cancer. TdDS refines the semantic targets of the upper and lower stages by mapping ground truths that are more consistent with the stage properties than upsampling deep supervision. This stage-specific approach can guide the model to learn a coarse-to-fine delineation process and improve the delineation accuracy of fuzzy boundaries by gradually shrinking the boundaries. Experimental results showed that TdDS is more customizable and plays a role similar to the attentional mechanism, and it can further improve the capability of the model to delineate colorectal cancer contours. A total of 103, 12, and 29 3D pelvic magnetic resonance imaging volumes were used for training, validation, and testing, respectively. The comparative results indicate that the proposed method exhibits the best comprehensive performance, with a dice similarity coefficient (DSC) of 0.805 ± 0.053 and a hausdorff distance (HD) of 9.28 ± 5.14 voxels. In the delineation performance analysis section also showed that 44.49% of the delineation results are satisfactory and do not require revisions. This study can provide new technical support for the delineation of 3D colorectal cancer. Our method is open source, and the code is available athttps://github.com/odindis/TdDS/tree/main.

Establishment and validation of novel MRI radiomic feature-based prognostic models to predict progression-free survival in locally advanced rectal cancer.

In locally advanced rectal cancer (LARC), an improved ability to predict prognosis before and after treatment is needed for individualized treatment. We aimed to utilize pre- and post-treatment clinical predictors and baseline magnetic resonance imaging (MRI) radiomic features for establishing prognostic models to predict progression-free survival (PFS) in patients with LARC. Patients with LARC diagnosed between March 2014 and May 2016 were included in this retrospective study. A radiomic signature based on extracted MRI features and clinical prognostic models based on clinical features were constructed in the training cohort to predict 3-year PFS. C-indices were used to evaluate the predictive accuracies of the radiomic signature, clinical prognostic models, and integrated prognostic model (iPostM). In total, 166 consecutive patients were included (110 vs. 56 for training vs. validation). Eleven radiomic features were filtered out to construct the radiomic signature, which was significantly related to PFS. The MRI feature-derived radiomic signature exhibited better prognostic performance than the clinical prognostic models (P = 0.007 vs. 0.077). Then, we proposed an iPostM that combined the radiomic signature with tumor regression grade. The iPostM achieved the highest C-indices in the training and validation cohorts (0.942 and 0.752, respectively), outperforming other models in predicting PFS (all P < 0.05). Decision curve analysis and survival curves of the validation cohort verified that iPostM demonstrated the best performance and facilitated risk stratification. Therefore, iPostM provided the most reliable prognostic prediction for PFS in patients with LARC.

Nodal grouping in nasopharyngeal carcinoma: prognostic significance, N classification, and a marker for the identification of candidates for induction chemotherapy.

OBJECTIVES: This study aimed to evaluate the value of nodal grouping (NG), defined as the presence of at least three contiguous lymph nodes (LNs) within one LN region, in staging and management of patients with non-metastatic nasopharyngeal carcinoma (NPC). METHODS: MR images were reviewed to evaluate LN variables, including NG. The Kaplan-Meier method and multivariate Cox regression models evaluated the association between the variables and survival. Harrell's concordance index (C-index) was used to measure the performance of prognostic models. The outcome of induction chemotherapy (IC) in patients with and without NG was compared using matched-pair analysis. RESULTS: In 1224 patients enrolled, NG was found to be an independent prognostic factor for overall survival (OS), progression-free survival (PFS), distant metastasis-free survival (DMFS), and regional recurrence-free survival. The hazard ratio and 95% confidence interval (CI) of NG for OS (3.86, 2.09-7.12) were higher than those of stage N2 (3.54, 1.89-6.70). On upgrading patients with NG from stages N1 to N2, the revised N staging yielded a higher C-index compared to the American Joint Committee on Cancer system in predicting PFS (0.664 vs. 0.658, p = 0.022) and DMFS (0.699 vs. 0.690, p = 0.005). Results of the matched-pair analysis revealed that for patients with NG in stages N1 and N2, IC was correlated with improved OS (p = 0.022), PFS (p = 0.007), and DMFS (p = 0.021). CONCLUSIONS: NG is a significant prognostic factor for patients with NPC. Patients with NG may be upgraded from stages N1 to N2. NG was also a marker for identifying patients who would benefit from IC. KEY POINTS: • Nodal grouping, defined as the presence of at least three contiguous LNs within one LN region on MRI, was identified as a significant prognostic factor. • In patients with nasopharyngeal carcinoma, nodal grouping may influence lymph node staging. • Nodal grouping was a marker for identifying patients who may benefit from induction chemotherapy.

Paraplegia by acute cervical disc protrusion after lumbar spine surgery.

Non-traumatic paraplegia caused by herniation of the cervical intervertebral disc is an uncommon postoperative complication. A patient with claudication and radiculopathy was scheduled for lumbar laminectomy due to spinal stenosis. Postoperatively, numbness below T6 was found in his both legs of the patient. MRI showed a protruded intervertebral disc between C6 and C7. Despite urgent disectomy, the patient's lower extremities remained paralyzed without significant improvement for 3 months. Loss of muscle support during general anesthesia, excessive neck extension during endotracheal intubation and positioning, as well as bucking and agitation are believed as triggering factors for the protrusion of the cervical disc. We suggest that a complete history taking and physical examination be accomplished in patients scheduled for lumbar spine surgery in order to exclude coexisting cervical spine disorders. In addition, skillful endotracheal intubation and careful neck positioning are mandatory for patients receiving surgery in the prone position.

Airway obstruction by a metastatic mediastinal tumor during anesthesia.

A case of low back pain syndrome was diagnosed due to spinal metastasis with unknown primary origin. During anesthesia for surgical stabilization, unexpected airway obstruction occurred after endotracheal intubation. Fiber-optic bronchoscopic examination showed narrowing of the trachea and main bronchi caused by extrinsic compression. After administration of neostigmine to reverse neuromuscular blockade, the patient resumed spontaneous breath. Airway obstruction was relieved thereafter. The extrinsic lesion was diagnosed as mediastinal lung cancer. The mechanism and management of this airway compromise caused by mediastinal tumor is discussed.