A novel voxel based homogeneity index: Rationale and clinical implications for whole-brain radiation therapy

A homogeneity index (HI) measures the uniformity of a dose distribution within a given target volume. Traditional HIs only use a limited number of dose–volume histogram data-points for calculation. A voxel-based homogeneity index (VHI) is proposed which utilizes the entire information of the three-dimensional dose distribution. We compared the VHI with existing HIs and analyzed if VHI results were associated with treatment outcomes in patients who underwent therapeutic WBRT.

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Knowledge transfer for surgical activity prediction

Abstract

Purpose

Lack of annotated training data hinders automatic recognition and prediction of surgical activities necessary for situation-aware operating rooms. We propose using knowledge transfer to compensate for data deficit and improve prediction.

Methods

We used two approaches to extract and transfer surgical process knowledge. First, we encoded semantic information about surgical terms using word embedding. Secondly, we passed knowledge between different clinical datasets of neurosurgical procedures using transfer learning.

Results

The combination of two methods provided 22% improvement of activity prediction. We also made several pertinent observations about surgical practices based on the results of the performed transfer.

Conclusion

Word embedding boosts learning process. Transfer learning was shown to be more effective than a simple combination of data, especially for less similar procedures.

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Role of interventional radiology in the management of musculoskeletal soft-tissue lesions

Abstract

The lesions of the soft tissues are rare and extremely heterogeneous; even if the surgical treatment is usually the standard therapy, the role of the interventional radiology (IR) in this field is growing up for multiple reasons. First, because the imaging alone usually is not able to ensure a definitive diagnosis, IR has a basic role in the staging: the percutaneous biopsy is infact an irreplaceable step. Moreover, biopsy is necessary not only for histologic evaluations but also for the biochemical and molecular studies. Furthermore, the proved safety and effectiveness of IR in a multiple oncologial applications prompt a wider use also in this field.

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Relationship between interstitial lung disease and oesophageal dilatation on chest high-resolution computed tomography in patients with systemic sclerosis: a cross-sectional study

Abstract

Objectives

Oesophageal dilatation (OD) has been implicated in the pathogenesis of interstitial lung disease (ILD) in systemic sclerosis (SSc). The aims of this study were to explore the association of the OD and SSc-ILD on chest high-resolution computed tomography (HRCT), and to establish a cutoff point for the OD suggestive for the presence of a significant lung involvement.

Methods

The widest oesophageal diameter (WOD) was obtained on axial HRCT images. The parenchymal abnormalities on HRCT were coded and scored according to Warrick method. Patient-centred measures, pulmonary function tests and the single breath carbon monoxide diffusing capacity of the lung (DLco) were also obtained. Multivariate regression analysis was performed to identify factors associated with oesophageal diameter.

Results

126 subjects with SSc were included. The mean (± SD) WOD was 13.5 (± 4.2) mm, and in 76 (60.3%) participants WOD was ≥ 11 mm. SSc patients with ILD had larger oesophageal diameters than those without lung disease (19.4 vs. 14.1 mm, p < 0.001). We observed a high correlation between WOD and gastro-oesophageal reflux disease questionnaire (GerdQ) (r = 0.886, p < 0.001), Borg score (r = 0.705, p < 0.001), and Warrick score (r = 0.614, p < 0.001). WOD negatively correlated with DLco (r = − 0.508, p < 0.001). Multivariate analysis demonstrated positive associations between WOD and GerdQ (p < 0.0001), Borg score (p < 0.0005), and total Warrick score (p = 0.019).

Conclusion

An increased oesophageal diameter (> 11 mm) on chest HRCT is associated with pulmonary and oesophageal symptoms, more severe ILD, and lower DLco.

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Could 68-Ga PSMA PET/CT become a new tool in the decision-making strategy of prostate cancer patients with biochemical recurrence of PSA after radical prostatectomy? A preliminary, monocentric series

Abstract

Aim

To evaluate the impact of gallium68 PSMA-11 (HBED-CC)-PET/CT on decision-making strategy of patients with relapsing prostate cancer (PC) presenting a second biochemical relapse after radical prostatectomy (RP) and salvage RT or salvage androgen deprivation therapy (ADT).

Materials and methods

40 patients were retrospectively analyzed. All of them had received prostatectomy. Thirteen out of 40 were addressed to gallium68 PSMA-11 (HBED-CC)-PET/CT for a biochemical relapse after RP, 14/40 after a salvage RT and 13/40 after salvage or adjuvant ADT. The PSA level ranged between 0.1 and 1.62 ng/ml (median value: 0.51 ng/ml). We studied the impact on the decision-making process of a multidisciplinary tumor board of additional data obtained from gallium68 PSMA-11 (HBED-CC)-PET/CT.

Results

Thirty-one out of 40 evaluated patients showed positive findings at gallium68 PSMA-11 (HBED-CC)-PET/CT (77.5%). Of them, five were positive in the prostatic bed, nine in the pelvic nodes, twelve in nodes outside the pelvis and eight at bone level. Nine patients presented two different sites of relapse (22.5%). Gallium68 PSMA-11 (HBED-CC)-PET/CT data changed the therapeutic approach in 28 patients (70%).

Conclusions

Gallium68 PSMA-11 (HBED-CC)-PET/CT can be a useful tool in the restaging of post-RP, RT or ADT patients presenting biochemical relapse of PC and it could change the decision-making process in up of 70% of these patients. Prospective, larger series are needed to establish the correct role of this very promising tool in the staging and therapeutic approach of PC patients.

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Effective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction

Abstract

Purpose

Probe-based confocal laser endomicroscopy (pCLE) is a recent imaging modality that allows performing in vivo optical biopsies. The design of pCLE hardware, and its reliance on an optical fibre bundle, fundamentally limits the image quality with a few tens of thousands fibres, each acting as the equivalent of a single-pixel detector, assembled into a single fibre bundle. Video registration techniques can be used to estimate high-resolution (HR) images by exploiting the temporal information contained in a sequence of low-resolution (LR) images. However, the alignment of LR frames, required for the fusion, is computationally demanding and prone to artefacts.

Methods

In this work, we propose a novel synthetic data generation approach to train exemplar-based Deep Neural Networks (DNNs). HR pCLE images with enhanced quality are recovered by the models trained on pairs of estimated HR images (generated by the video registration algorithm) and realistic synthetic LR images. Performance of three different state-of-the-art DNNs techniques were analysed on a Smart Atlas database of 8806 images from 238 pCLE video sequences. The results were validated through an extensive image quality assessment that takes into account different quality scores, including a Mean Opinion Score (MOS).

Results

Results indicate that the proposed solution produces an effective improvement in the quality of the obtained reconstructed image.

Conclusion

The proposed training strategy and associated DNNs allows us to perform convincing super-resolution of pCLE images.

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Approach to 1st Year in Radiology Residency

Sharing a short video to welcome and orient Post graduates who have opted for Radiology this year through NEETPG in India.

Famous Radiology Blog https://ift.tt/1MM2hKr TeleRad Providers at https://ift.tt/1NgppuI Mail us at sales@teleradproviders.com

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