Retrospective Use of Breathing Motion Compensation Technology (MCT) Enhances Vessel Detection Software Performance

Feasibility of a Prototype Image Reconstruction Algorithm for Motion Correction in Interventional Cone-Beam CT Scans

RATIONALE AND OBJECTIVES

Assess the feasibility of a prototype image reconstruction algorithm in correcting motion artifacts in cone-beam computed tomography (CBCT) scans of interventional instruments in the lung.

MATERIALS AND METHODS

First, phantom experiments were performed to assess the algorithm, using the Xsight lung phantom with custom inserts containing straight or curved catheters. During scanning, the inserts moved in a continuous sinusoidal or breath-hold mimicking pattern, with varying amplitudes and frequencies. Subsequently, the algorithm was applied to CBCT data from navigation bronchoscopy procedures. The algorithm's performance was assessed quantitatively via edge-sharpness measurements and qualitatively by three specialists.

RESULTS

In the phantom study, the algorithm improved sharpness in 13 out of 14 continuous sinusoidal motion and five out of seven breath-hold mimicking scans, with more significant effects at larger motion amplitudes. Analysis of 27 clinical scans showed that the motion corrected reconstructions had significantly sharper edges than standard reconstructions (2.81 (2.24-6.46) vs. 2.80 (2.16-4.75), p = 0.003). These results were consistent with the qualitative assessment, which showed higher scores in the sharpness of bronchoscope-tissue interface and catheter-tissue interface in the motion-corrected reconstructions. However, the tumor demarcation ratings were inconsistent between raters, and the overall image quality of the new reconstructions was rated lower.

CONCLUSION

Our findings suggest that applying the new prototype algorithm for motion correction in CBCT images is feasible. The algorithm improved the sharpness of medical instruments in CBCT scans obtained during diagnostic navigation bronchoscopy procedures, which was demonstrated both quantitatively and qualitatively.

Semiautomatic Cone-Beam Computed Tomography Virtual Hepatic Volumetry for Intra-Arterial Therapies

PURPOSE

To evaluate a software simulating the perfused liver volume from virtual selected embolization points on proximal enhanced cone-beam computed tomography (CT) liver angiography data set using selective cone-beam CT as a reference standard.

MATERIALS AND METHODS

Seventy-eight selective/proximal cone-beam CT couples in 46 patients referred for intra-arterial liver treatment at 2 recruiting centers were retrospectively included. A reference selective volume (RSV) was calculated from the selective cone-beam CT by manual segmentation and was used as a reference standard. The virtual perfusion volume (VPV) was then obtained using Liver ASSIST Virtual Parenchyma software on proximal cone-beam CT angiography using the same injection point as for selective cone-beam CT. RSV and VPV were then compared as absolute, relative, and signed volumetric errors (ABS_Err, RV_Err, and SV_Err, respectively), whereas their spatial correspondence was assessed using the Dice similarity coefficient.

RESULTS

The software was technically successful in automatically computing VPV in 74 of 78 (94.8%) cases. In the 74 analyzed couples, the median RSV was not significantly different from the median VPV (394 mL [196-640 mL] and 391 mL [192-620 mL], respectively; P = .435). The median ABS_Err, RV_Err, SV_Err, and Dice similarity coefficient were 40.9 mL (19.9-97.7 mL), 12.8% (5%-22%), 9.9 mL (-49.0 to 40.4 mL), and 80% (76%-84%), respectively. No significant ABS_Err, RV_Err, SV_Err, and Dice similarity coefficient differences were found between the 2 centers (P = .574, P = .612, P = .416, and P = .674, respectively).

CONCLUSIONS

Perfusion hepatic volumes simulated on proximal enhanced cone-beam CT using the virtual parenchyma software are numerically and spatially similar to those manually obtained on selective cone-beam CT.

Precision Imaging Guidance in the Era of Precision Oncology: An Update of Imaging Tools for Interventional Procedures

Interventional oncology (IO) procedures have become extremely popular in interventional radiology (IR) and play an essential role in the diagnosis, treatment, and supportive care of oncologic patients through new and safe procedures. IR procedures can be divided into two main groups: vascular and non-vascular. Vascular approaches are mainly based on embolization and concomitant injection of chemotherapeutics directly into the tumor-feeding vessels. Percutaneous approaches are a type of non-vascular procedures and include percutaneous image-guided biopsies and different ablation techniques with radiofrequency, microwaves, cryoablation, and focused ultrasound. The use of these techniques requires precise imaging pretreatment planning and guidance that can be provided through different imaging techniques: ultrasound, computed tomography, cone-beam computed tomography, and magnetic resonance. These imaging modalities can be used alone or in combination, thanks to fusion imaging, to further improve the confidence of the operators and the efficacy and safety of the procedures. This article aims is to provide an overview of the available IO procedures based on clinical imaging guidance to develop a targeted and optimal approach to cancer patients.

Application of Digital Image Based on Machine Learning in Media Art Design

In digital media art, expressive force is an important art form of media. This paper studies digital images that have the same effect when applied to media art. The research object is media art images, and the application effect of the proposed algorithm is related to the media art images. The development of digital image technology has brought revolutionary changes to traditional media art expression techniques. In this paper, a partial-pixel interpolation technique based on convolutional neural network is proposed. Supervised training of convolutional neural networks requires predetermining the input and target output of the network, namely, integer image and fractional image in this paper. To solve the problem that the subpixel sample cannot be obtained, this paper first analyzes the imaging principle of digital image and proposes a subpixel sample generation algorithm based on Gaussian low-pass filter and polyphase sampling. From the perspective of rate distortion optimization, the purpose of pixel motion compensation is to improve the accuracy of interframe prediction. Therefore, this paper defines pixel motion compensation as an interframe regression problem, that is, the mapping process of the reference image integral pixel sample to the current image sample to be encoded. In this paper, a generalized partial-pixel interpolation model is proposed for bidirectional prediction. The partial-pixel interpolation of bidirectional prediction is regarded as a binary regression model; that is, the integral pixel reference block in two directions is mapped to the current block to be coded. It further studies how to apply the trained digital images to media art design more flexibly and efficiently.