Evaluation of a nnU-Net type automated clinical volumetric tumor segmentation tool for diffuse low-grade glioma follow-up.

BACKGROUND AND PURPOSE: Diffuse low-grade gliomas (DLGG) are characterized by a slow and continuous growth and always evolve towards an aggressive grade. Accurate prediction of the malignant transformation is essential as it requires immediate therapeutic intervention. One of its most precise predictors is the velocity of diameter expansion (VDE). Currently, the VDE is estimated either by linear measurements or by manual delineation of the DLGG on T2 FLAIR acquisitions. However, because of the DLGG's infiltrative nature and its blurred contours, manual measures are challenging and variable, even for experts. Therefore we propose an automated segmentation algorithm using a 2D nnU-Net, to 1) gain time and 2) standardize VDE assessment. MATERIALS AND METHODS: The 2D nnU-Net was trained on 318 acquisitions (T2 FLAIR & 3DT1 longitudinal follow-up of 30 patients, including pre- & post-surgery acquisitions, different scanners, vendors, imaging parameters…). Automated vs. manual segmentation performance was evaluated on 167 acquisitions, and its clinical interest was validated by quantifying the amount of manual correction required after automated segmentation of 98 novel acquisitions. RESULTS: Automated segmentation showed a good performance with a mean Dice Similarity Coefficient (DSC) of 0.82±0.13 with manual segmentation and a substantial concordance between VDE calculations. Major manual corrections (i.e., DSC<0.7) were necessary only in 3/98 cases and 81% of the cases had a DSC>0.9. CONCLUSION: The proposed automated segmentation algorithm can successfully segment DLGG on highly variable MRI data. Although manual corrections are sometimes necessary, it provides a reliable, standardized and time-winning support for VDE extraction to asses DLGG growth.

Biomechanical and Neuromuscular Performance Requirements of Horizontal Deceleration: A Review with Implications for Random Intermittent Multi-Directional Sports.

Rapid horizontal accelerations and decelerations are crucial events enabling the changes of velocity and direction integral to sports involving random intermittent multi-directional movements. However, relative to horizontal acceleration, there have been considerably fewer scientific investigations into the biomechanical and neuromuscular demands of horizontal deceleration and the qualities underpinning horizontal deceleration performance. Accordingly, the aims of this review article are to: (1) conduct an evidence-based review of the biomechanical demands of horizontal deceleration and (2) identify biomechanical and neuromuscular performance determinants of horizontal deceleration, with the aim of outlining relevant performance implications for random intermittent multi-directional sports. We highlight that horizontal decelerations have a unique ground reaction force profile, characterised by high-impact peak forces and loading rates. The highest magnitude of these forces occurs during the early stance phase (< 50 ms) and is shown to be up to 2.7 times greater than those seen during the first steps of a maximal horizontal acceleration. As such, inability for either limb to tolerate these forces may result in a diminished ability to brake, subsequently reducing deceleration capacity, and increasing vulnerability to excessive forces that could heighten injury risk and severity of muscle damage. Two factors are highlighted as especially important for enhancing horizontal deceleration ability: (1) braking force control and (2) braking force attenuation. Whilst various eccentric strength qualities have been reported to be important for achieving these purposes, the potential importance of concentric, isometric and reactive strength, in addition to an enhanced technical ability to apply braking force is also highlighted. Last, the review provides recommended research directions to enhance future understanding of horizontal deceleration ability.