Analytic calculations and synthetic shapes for validation of quantitative contour comparison software.

A high level of variability in reported values was observed in a recent survey of contour similarity measures (CSMs) calculation tools. Such variations in the output measurements prevent meaningful comparison between studies. The purpose of this study was to develop a dataset with analytically calculated gold standard values to facilitate standardization and ensure accuracy of CSM implementations. The dataset was generated in the Digital Imaging and Communications in Medicine (DICOM) format. Both the dataset and the software used for its generation are made publicly available to encourage robust testing of CSM implementations for accuracy, improving consistency between different implementations.

Advancing the treatment of localized prostate cancer with MR-guided radiotherapy.

External beam radiotherapy (EBRT) is an important cornerstone in the treatment of localized prostate cancer. Current image-guided radiotherapy (IGRT) techniques allow for more accurate and precise delivery of radiation treatment by the use of imaging before each fraction. Magnetic resonance guided radiotherapy (MRgRT) is the next step in IGRT with hybrid systems combining linear accelerators with MRI-scanners. With MRgRT, it is possible to visualize pelvic anatomy in great detail and subsequently perform replanning of the radiation dose distribution before each radiotherapy fraction. This technique has the potential to increase the therapeutic window of EBRT, by improved normal tissue sparing due to margin reduction and more accurate target dose delivery. This is particularly promising for prostate cancer, with its biology lending itself to ultra-hypofractionation, reducing radiotherapy treatment to as little as five fractions. Also, recent studies have shown that focal dose escalation to the intraprostatic tumor to high ablative doses can substantially increase disease-free survival. In this article, we discuss these unique opportunities as well as the potential future benefits of MRgRT in prostate cancer treatment.

Multicenter comparison of measures for quantitative evaluation of contouring in radiotherapy.

Background and Purpose: A wide range of quantitative measures are available to facilitate clinical implementation of auto-contouring software, on-going Quality Assurance (QA) and interobserver contouring variation studies. This study aimed to assess the variation in output when applying different implementations of the measures to the same data in order to investigate how consistently such measures are defined and implemented in radiation oncology. Materials and Methods: A survey was conducted to assess if there were any differences in definitions of contouring measures or their implementations that would lead to variation in reported results between institutions. This took two forms: a set of computed tomography (CT) image data with "Test" and "Reference" contours was distributed for participants to process using their preferred tools and report results, and a questionnaire regarding the definition of measures and their implementation was completed by the participants. Results: Thirteen participants completed the survey and submitted results, with one commercial and twelve in-house solutions represented. Excluding outliers, variations of up to 50% in Dice Similarity Coefficient (DSC), 50% in 3D Hausdorff Distance (HD), and 200% in Average Distance (AD) were observed between the participant submitted results. Collaborative investigation with participants revealed a large number of bugs in implementation, confounding the understanding of intentional implementation choices. Conclusion: Care must be taken when comparing quantitative results between different studies. There is a need for a dataset with clearly defined measures and ground truth for validation of such tools prior to their use.

Implementation of MR-linac and proton therapy in two radiotherapy departments in The Netherlands: Recommendations based on lessons learned.

Recently, two new treatment techniques, i.e. proton therapy and MR-linac based radiotherapy (RT), have been introduced in Dutch RT centres with major impact on daily practice. The content and context of these techniques are frequently described in scientific literature while little is reported about the implementation phase. This process is complex due to a variety of aspects, such as the involvement of multiple stakeholders, significant unpredictability in the start-up phase, the impact of the learning curve, standard operating procedures under development, new catchment areas, and extensive training programs. Insight about implementation in daily care is utterly important for clinics that are about to introduce these new technologies in order to prevent that every centre needs to reinvent the wheel. This position paper gives an overview of the implementation of proton therapy and MR-linac based RT in two large academic RT centres in the Netherlands, i.e. Maastro and Radboudumc respectively. With this paper we aim to report our lessons learned, in order to facilitate other RT centres that consider introducing these and other new techniques in their departments.

External validation of deep learning-based contouring of head and neck organs at risk.

BACKGROUND AND PURPOSE: Head and neck (HN) radiotherapy can benefit from automatic delineation of tumor and surrounding organs because of the complex anatomy and the regular need for adaptation. The aim of this study was to assess the performance of a commercially available deep learning contouring (DLC) model on an external validation set. MATERIALS AND METHODS: The CT-based DLC model, trained at the University Medical Center Groningen (UMCG), was applied to an independent set of 58 patients from the Radboud University Medical Center (RUMC). DLC results were compared to the RUMC manual reference using the Dice similarity coefficient (DSC) and 95th percentile of Hausdorff distance (HD95). Craniocaudal spatial information was added by calculating binned measures. In addition, a qualitative evaluation compared the acceptance of manual and DLC contours in both groups of observers. RESULTS: Good correspondence was shown for the mandible (DSC 0.90; HD95 3.6 mm). Performance was reasonable for the glandular OARs, brainstem and oral cavity (DSC 0.78-0.85, HD95 3.7-7.3 mm). The other aerodigestive tract OARs showed only moderate agreement (DSC 0.53-0.65, HD95 around 9 mm). The binned measures displayed the largest deviations caudally and/or cranially. CONCLUSIONS: This study demonstrates that the DLC model can provide a reasonable starting point for delineation when applied to an independent patient cohort. The qualitative evaluation did not reveal large differences in the interpretation of contouring guidelines between RUMC and UMCG observers.

Ursodeoxycholic acid in advanced polycystic liver disease: A phase 2 multicenter randomized controlled trial.

BACKGROUND & AIMS: Ursodeoxycholic acid (UDCA) inhibits proliferation of polycystic human cholangiocytes in vitro and hepatic cystogenesis in a rat model of polycystic liver disease (PLD) in vivo. Our aim was to test whether UDCA may beneficially affect liver volume in patients with advanced PLD. METHODS: We conducted an international, multicenter, randomized controlled trial in symptomatic PLD patients from three tertiary referral centers. Patients with PLD and total liver volume (TLV) ⩾2500ml were randomly assigned to UDCA treatment (15-20mg/kg/day) for 24weeks, or to no treatment. Primary endpoint was proportional change in TLV. Secondary endpoints were change in symptoms and health-related quality of life. We performed a post-hoc analysis of the effect of UDCA on liver cyst volume (LCV). RESULTS: We included 34 patients and were able to assess primary endpoint in 32 patients, 16 with autosomal dominant polycystic kidney disease (ADPKD) and 16 with autosomal dominant polycystic liver disease (ADPLD). Proportional TLV increased by 4.6±7.7% (mean TLV increased from 6697ml to 6954ml) after 24weeks of UDCA treatment compared to 3.1±3.8% (mean TLV increased from 5512ml to 5724ml) in the control group (p=0.493). LCV was not different after 24weeks between controls and UDCA treated patients (p=0.848). However, UDCA inhibited LCV growth in ADPKD patients compared to ADPKD controls (p=0.049). CONCLUSIONS: UDCA administration for 24weeks did not reduce TLV in advanced PLD, but UDCA reduced LCV growth in ADPKD patients. Future studies might explore whether ADPKD and ADPLD patients respond differently to UDCA treatment. LAY SUMMARY: Current therapies for polycystic liver disease are invasive and have high recurrence risks. Our trial showed that the drug, ursodeoxycholic acid, was not able to reduce liver volume in patients with polycystic liver disease. However, a subgroup analysis in patients that have kidney cysts as well showed that liver cyst volume growth was reduced in patients who received ursodeoxycholic acid in comparison to patients who received no treatment. Trial registration number https://www.clinicaltrials.gov/: NCT02021110. EudraCT Number https://www.clinicaltrialsregister.eu/: 2013-003207-19.

Structural and resting state functional connectivity of the subthalamic nucleus: identification of motor STN parts and the hyperdirect pathway.

Deep brain stimulation (DBS) for Parkinson's disease often alleviates the motor symptoms, but causes cognitive and emotional side effects in a substantial number of cases. Identification of the motor part of the subthalamic nucleus (STN) as part of the presurgical workup could minimize these adverse effects. In this study, we assessed the STN's connectivity to motor, associative, and limbic brain areas, based on structural and functional connectivity analysis of volunteer data. For the structural connectivity, we used streamline counts derived from HARDI fiber tracking. The resulting tracks supported the existence of the so-called "hyperdirect" pathway in humans. Furthermore, we determined the connectivity of each STN voxel with the motor cortical areas. Functional connectivity was calculated based on functional MRI, as the correlation of the signal within a given brain voxel with the signal in the STN. Also, the signal per STN voxel was explained in terms of the correlation with motor or limbic brain seed ROI areas. Both right and left STN ROIs appeared to be structurally and functionally connected to brain areas that are part of the motor, associative, and limbic circuit. Furthermore, this study enabled us to assess the level of segregation of the STN motor part, which is relevant for the planning of STN DBS procedures.

Magnetic resonance imaging techniques for visualization of the subthalamic nucleus.

The authors reviewed 70 publications on MR imaging-based targeting techniques for identifying the subthalamic nucleus (STN) for deep brain stimulation in patients with Parkinson disease. Of these 70 publications, 33 presented quantitatively validated results. There is still no consensus on which targeting technique to use for surgery planning; methods vary greatly between centers. Some groups apply indirect methods involving anatomical landmarks, or atlases incorporating anatomical or functional data. Others perform direct visualization on MR imaging, using T2-weighted spin echo or inversion recovery protocols. The combined studies do not offer a straightforward conclusion on the best targeting protocol. Indirect methods are not patient specific, leading to varying results between cases. On the other hand, direct targeting on MR imaging suffers from lack of contrast within the subthalamic region, resulting in a poor delineation of the STN. These deficiencies result in a need for intraoperative adaptation of the original target based on test stimulation with or without microelectrode recording. It is expected that future advances in MR imaging technology will lead to improvements in direct targeting. The use of new MR imaging modalities such as diffusion MR imaging might even lead to the specific identification of the different functional parts of the STN, such as the dorsolateral sensorimotor part, the target for deep brain stimulation.

A Sobolev norm based distance measure for HARDI clustering: a feasibility study on phantom and real data.

Dissimilarity measures for DTI clustering are abundant. However, for HARDI, the L2 norm has up to now been one of only few practically feasible measures. In this paper we propose a new measure, that not only compares the amplitude of diffusion profiles, but also rewards coincidence of the extrema. We tested this on phantom and real brain data. In both cases, our measure significantly outperformed the L2 norm.

In vivo high-resolution structural imaging of large arteries in small rodents using two-photon laser scanning microscopy.

In vivo (molecular) imaging of the vessel wall of large arteries at subcellular resolution is crucial for unraveling vascular pathophysiology. We previously showed the applicability of two-photon laser scanning microscopy (TPLSM) in mounted arteries ex vivo. However, in vivo TPLSM has thus far suffered from in-frame and between-frame motion artifacts due to arterial movement with cardiac and respiratory activity. Now, motion artifacts are suppressed by accelerated image acquisition triggered on cardiac and respiratory activity. In vivo TPLSM is performed on rat renal and mouse carotid arteries, both surgically exposed and labeled fluorescently (cell nuclei, elastin, and collagen). The use of short acquisition times consistently limit in-frame motion artifacts. Additionally, triggered imaging reduces between-frame artifacts. Indeed, structures in the vessel wall (cell nuclei, elastic laminae) can be imaged at subcellular resolution. In mechanically damaged carotid arteries, even the subendothelial collagen sheet (approximately 1 microm) is visualized using collagen-targeted quantum dots. We demonstrate stable in vivo imaging of large arteries at subcellular resolution using TPLSM triggered on cardiac and respiratory cycles. This creates great opportunities for studying (diseased) arteries in vivo or immediate validation of in vivo molecular imaging techniques such as magnetic resonance imaging (MRI), ultrasound, and positron emission tomography (PET).

Automatic trajectory planning for deep brain stimulation: a feasibility study.

DBS for Parkinson's disease involves an extensive planning to find a suitable electrode implantation path to the selected target. We have investigated the feasibility of improving the conventional planning with an automatic calculation of possible paths in 3D. This requires the segmentation of anatomical structures. Subsequently, the paths are calculated and visualized. After selection of a suitable path, the settings for the stereotactic frame are determined. A qualitative evaluation has shown that automatic avoidance of critical structures is feasible. The participating neurosurgeons estimate the time gain to be around 30 minutes.

Automatic IVUS segmentation of atherosclerotic plaque with stop & go snake.

Since the upturn of intravascular ultrasound (IVUS) as an imaging technique for the coronary artery system, much research has been done to simplify the complicated analysis of the resulting images. In this study, an attempt to develop an automatic tissue characterization algorithm for IVUS images was done. The first step was the extraction of texture features. The resulting feature space was used for classification, constructing a likelihood map to represent different coronary plaques. The information in this map was organized using a recently developed geodesic snake formulation, the so-called Stop & Go snake. The novelty of our study lies in this last step, as it was the first time to apply the Stop & Go snake to segment IVUS images.