Deep learning-based voxel sampling for particle therapy treatment planning.

Objective.Scanned particle therapy often requires complex treatment plans, robust optimization, as well as treatment adaptation. Plan optimization is especially complicated for heavy ions due to the variable relative biological effectiveness. We present a novel deep-learning model to select a subset of voxels in the planning process thus reducing the planning problem size for improved computational efficiency.Approach.Using only a subset of the voxels in target and organs at risk (OARs) we produced high-quality treatment plans, but heuristic selection strategies require manual input. We designed a deep-learning model based onP-Net to obtain an optimal voxel sampling without relying on patient-specific user input. A cohort of 70 head and neck patients that received carbon ion therapy was used for model training (50), validation (10) and testing (10). For training, a total of 12 500 carbon ion plans were optimized, using a highly efficient artificial intelligence (AI) infrastructure implemented into a research treatment planning platform. A custom loss function increased sampling density in underdosed regions, while aiming to reduce the total number of voxels.Main results.On the test dataset, the number of voxels in the optimization could be reduced by 84.8% (median) at <1% median loss in plan quality. When the model was trained to reduce sampling in the target only while keeping all voxels in OARs, a median reduction up to 71.6% was achieved, with 0.5% loss in the plan quality. The optimization time was reduced by a factor of 7.5 for the total AI selection model and a factor of 3.7 for the model with only target selection.Significance.The novel deep-learning voxel sampling technique achieves a significant reduction in computational time with a negligible loss in the plan quality. The reduction in optimization time can be especially useful for future real-time adaptation strategies.

The accuracy of helium ion CT based particle therapy range prediction: an experimental study comparing different particle and x-ray CT modalities.

This work provides a quantitative assessment of helium ion CT (HeCT) for particle therapy treatment planning. For the first time, HeCT based range prediction accuracy in a heterogeneous tissue phantom is presented and compared to single-energy x-ray CT (SECT), dual-energy x-ray CT (DECT) and proton CT (pCT). HeCT and pCT scans were acquired using the US pCT collaboration prototype particle CT scanner at the Heidelberg Ion-Beam Therapy Center. SECT and DECT scans were done with a Siemens Somatom Definition Flash and converted to RSP. A Catphan CTP404 module was used to study the RSP accuracy of HeCT. A custom phantom of 20 cm diameter containing several tissue equivalent plastic cubes was used to assess the spatial resolution of HeCT and compare it to DECT. A clinically realistic heterogeneous tissue phantom was constructed using cranial slices from a pig head placed inside a cylindrical phantom (ø150 mm). A proton beam (84.67 mm range) depth-dose measurement was acquired using a stack of GafchromicTM EBT-XD films in a central dosimetry insert in the phantom. CT scans of the phantom were acquired with each modality, and proton depth-dose estimates were simulated based on the reconstructions. The RSP accuracy of HeCT for the plastic phantom was found to be 0.3 ± 0.1%. The spatial resolution for HeCT of the cube phantom was 5.9 ± 0.4 lp cm-1for central, and 7.6 ± 0.8 lp cm-1for peripheral cubes, comparable to DECT spatial resolution (7.7 ± 0.3 lp cm-1and 7.4 ± 0.2 lp cm-1, respectively). For the pig head, HeCT, SECT, DECT and pCT predicted range accuracy was 0.25%, -1.40%, -0.45% and 0.39%, respectively. In this study, HeCT acquired with a prototype system showed potential for particle therapy treatment planning, offering RSP accuracy, spatial resolution, and range prediction accuracy comparable to that achieved with a commercial DECT scanner. Still, technical improvements of HeCT are needed to enable clinical implementation.

Experimental exploration of a mixed helium/carbon beam for online treatment monitoring in carbon ion beam therapy.

Recently, it has been proposed that a mixed helium/carbon beam could be used for online monitoring in carbon ion beam therapy. Fully stripped, the two ion species exhibit approximately the same mass/charge ratio and hence could potentially be accelerated simultaneously in a synchrotron to the same energy per nucleon. At the same energy per nucleon, helium ions have about three times the range of carbon ions, which could allow for simultaneous use of the carbon ion beam for treatment and the helium ion beam for imaging. In this work, measurements and simulations of PMMA phantoms as well as anthropomorphic phantoms irradiated sequentially with a helium ion and a carbon ion beam at equal energy per nucleon are presented. The range of the primary helium ion beam and the fragment tail of the carbon ion beam exiting the phantoms were detected using a novel range telescope made of thin plastic scintillator sheets read out by a flat-panel CMOS sensor. A 10:1 carbon to helium mixing ratio is used, generating a helium signal well above the carbon fragment background while adding little to the dose delivered to the patient. The range modulation of a narrow air gap of 1 mm thickness in the PMMA phantom that affects less than a quarter of the particles in a pencil beam were detected, demonstrating the achievable relative sensitivity of the presented method. Using two anthropomorphic pelvis phantoms it is shown that small rotations of the phantom as well as simulated bowel gas movements cause detectable changes in the helium/carbon beam exiting the phantom. The future prospects and limitations of the helium/carbon mixing as well as its technical feasibility are discussed.

Network connectivity of motor control in the ageing brain.

Older individuals typically display stronger regional brain activity than younger subjects during motor performance. However, knowledge regarding age-related changes of motor network interactions between brain regions remains scarce. We here investigated the impact of ageing on the interaction of cortical areas during movement selection and initiation using dynamic causal modelling (DCM). We found that age-related psychomotor slowing was accompanied by increases in both regional activity and effective connectivity, especially for 'core' motor coupling targeting primary motor cortex (M1). Interestingly, younger participants within the older group showed strongest connectivity targeting M1, which steadily decreased with advancing age. Conversely, prefrontal influences on the motor system increased with advancing age, and were inversely correlated with reduced parietal influences and core motor coupling. Interestingly, higher net coupling within the prefrontal-premotor-M1 axis predicted faster psychomotor speed in ageing. Hence, as opposed to a uniform age-related decline, our findings are compatible with the idea of different age-related compensatory mechanisms, with an important role of the prefrontal cortex compensating for reduced coupling within the core motor network.

Time-dependent functional role of the contralesional motor cortex after stroke.

After stroke, movements of the paretic hand rely on altered motor network dynamics typically including additional activation of the contralesional primary motor cortex (M1). The functional implications of contralesional M1 recruitment to date remain a matter of debate. We here assessed the role of contralesional M1 in 12 patients recovering from a first-ever stroke using online transcranial magnetic stimulation (TMS): Short bursts of TMS were administered over contralesional M1 or a control site (occipital vertex) while patients performed different motor tasks with their stroke-affected hand. In the early subacute phase (1-2 weeks post-stroke), we observed significant improvements in maximum finger tapping frequency when interfering with contralesional M1, while maximum grip strength and speeded movement initiation remained unaffected. After > 3 months of motor recovery, disruption of contralesional M1 activity did not interfere with performance in any of the three tasks, similar to what we observed in healthy controls. In patients with mild to moderate motor deficits, contralesional M1 has a task- and time-specific negative influence on motor performance of the stroke-affected hand. Our results help to explain previous contradicting findings on the role of contralesional M1 in recovery of function.

Shaping Early Reorganization of Neural Networks Promotes Motor Function after Stroke.

Neural plasticity is a major factor driving cortical reorganization after stroke. We here tested whether repetitively enhancing motor cortex plasticity by means of intermittent theta-burst stimulation (iTBS) prior to physiotherapy might promote recovery of function early after stroke. Functional magnetic resonance imaging (fMRI) was used to elucidate underlying neural mechanisms. Twenty-six hospitalized, first-ever stroke patients (time since stroke: 1-16 days) with hand motor deficits were enrolled in a sham-controlled design and pseudo-randomized into 2 groups. iTBS was administered prior to physiotherapy on 5 consecutive days either over ipsilesional primary motor cortex (M1-stimulation group) or parieto-occipital vertex (control-stimulation group). Hand motor function, cortical excitability, and resting-state fMRI were assessed 1 day prior to the first stimulation and 1 day after the last stimulation. Recovery of grip strength was significantly stronger in the M1-stimulation compared to the control-stimulation group. Higher levels of motor network connectivity were associated with better motor outcome. Consistently, control-stimulated patients featured a decrease in intra- and interhemispheric connectivity of the motor network, which was absent in the M1-stimulation group. Hence, adding iTBS to prime physiotherapy in recovering stroke patients seems to interfere with motor network degradation, possibly reflecting alleviation of post-stroke diaschisis.

Identifying Neuroimaging Markers of Motor Disability in Acute Stroke by Machine Learning Techniques.

Conventional mass-univariate analyses have been previously used to test for group differences in neural signals. However, machine learning algorithms represent a multivariate decoding approach that may help to identify neuroimaging patterns associated with functional impairment in "individual" patients. We investigated whether fMRI allows classification of individual motor impairment after stroke using support vector machines (SVMs). Forty acute stroke patients and 20 control subjects underwent resting-state fMRI. Half of the patients showed significant impairment in hand motor function. Resting-state connectivity was computed by means of whole-brain correlations of seed time-courses in ipsilesional primary motor cortex (M1). Lesion location was identified using diffusion-weighted images. These features were used for linear SVM classification of unseen patients with respect to motor impairment. SVM results were compared with conventional mass-univariate analyses. Resting-state connectivity classified patients with hand motor deficits compared with controls and nonimpaired patients with 82.6-87.6% accuracy. Classification was driven by reduced interhemispheric M1 connectivity and enhanced connectivity between ipsilesional M1 and premotor areas. In contrast, lesion location provided only 50% sensitivity to classify impaired patients. Hence, resting-state fMRI reflects behavioral deficits more accurately than structural MRI. In conclusion, multivariate fMRI analyses offer the potential to serve as markers for endophenotypes of functional impairment.

An unusual presentation of hidradenitis suppurativa: case report and review of the literature.

Hidradenitis suppurativa is a chronic suppurative and cicatricial process of apocrine gland-bearing skin. The clinical course can range from mild to severe. We present a case of a urethral fistula and phimosis occurring secondary to hidradenitis suppurativa, and review the literature.

Laser treatment of urethral condyloma: a five-year experience.

OBJECTIVE: Twenty cases of men treated with the neodymium:yttrium-aluminum-garnet (Nd:YAG) laser for meatal and/or urethral condyloma over five years were reviewed. METHOD: All patients underwent Nd:YAG laser treatment of visible lesions as outpatients under general anesthesia using the visual urethrotome sheath and 0 degree lens. Follow-up urethroscopy was performed at three-month intervals. Cure of the gross disease was defined as negative findings on two sequential follow-up urethroscopies. RESULTS: All patients with gross condylomatous disease were verified to have type 6/11 human papillomavirus. Ninety-five percent had meatal condylomata of which 42 percent had concomitant distal urethral lesions. Thirty percent were cured of gross disease after one treatment, while 40 percent needed two, three, four, or five separate treatments before gross cure was obtained. Thirty percent had insufficient follow-up. Only 2 of the patients experiencing recurrence did so after negative finding on one follow-up urethroscopy. CONCLUSIONS: We believe attempts at cure of gross urethral condylomatous disease should be made because of its unsightliness and symptoms such as split stream and bleeding. Cure of gross disease with the Nd:YAG laser, as evidenced by our results, is possible. However, it may require several treatments. Follow-up urethroscopy is recommended in all patients because of the high incidence of recurrence and concomitant distal urethral involvement in those patients with meatal disease.

The contribution of the different binding sites of the N-methyl-D-aspartate (NMDA) receptor to the expression of behavior.

The effects of competitive (CGP 37849 and CGP 39551) and non-competitive (dizocilpine) N-methyl-D-aspartate (NMDA) antagonists were tested in three animal models (catalepsy, sniffing, locomotion) and, in addition, the modulation of these effects by an agonist of the strychnine-insensitive glycine binding site was investigated. Both competitive and non-competitive NMDA antagonists reduced neuroleptic-induced catalepsy. Weak sniffing was induced by the competitive antagonist but strong sniffing by the non-competitive NMDA antagonist. Due to muscle relaxation the competitive antagonist reduced locomotion, in contrast to stimulation of locomotor activity induced by the non-competitive NMDA antagonist. The glycine agonist (D-cycloserine) potentiated the effects of the non-competitive but antagonized those of the competitive NMDA antagonist.