Absolute alignment of breathing states using image similarity derivatives

Eck, Kai; Bredno, Joerg; Stehlé, Thomas

doi:10.1117/12.595313

Cited by 14 publications

(10 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2). This is consistent with previous findings from correlation‐based image processing techniques (31‐34) . All processing was performed using custom MATLAB software.…”

Section: Methodssupporting

confidence: 87%

Evaluation of 4D CT acquisition methods designed to reduce artifacts

Castillo

et al. 2015

J Applied Clin Med Phys

View full text Add to dashboard Cite

Four-dimensional computed tomography (4D CT) is used to account for respiratory motion in radiation treatment planning, but artifacts resulting from the acquisition and postprocessing limit its accuracy. We investigated the efficacy of three experimental 4D CT acquisition methods to reduce artifacts in a prospective institutional review board approved study. Eighteen thoracic patients scheduled to undergo radiation therapy received standard clinical 4D CT scans followed by each of the alternative 4D CT acquisitions: 1) data oversampling, 2) beam gating with breathing irregularities, and 3) rescanning the clinical acquisition acquired during irregular breathing. Relative values of a validated correlation-based artifact metric (CM) determined the best acquisition method per patient. Each 4D CT was processed by an extended phase sorting approach that optimizes the quantitative artifact metric (CM sorting). The clinical acquisitions were also postprocessed by phase sorting for artifact comparison of our current clinical implementation with the experimental methods. The oversampling acquisition achieved the lowest artifact presence among all acquisitions, achieving a 27% reduction from the current clinical 4D CT implementation (95% confidence interval = 34–20). The rescan method presented a significantly higher artifact presence from the clinical acquisition (37%; p < 0.002), the gating acquisition (26%; p < 0.005), and the oversampling acquisition (31%; p < 0.001), while the data lacked evidence of a significant difference between the clinical, gating, and oversampling methods. The oversampling acquisition reduced artifact presence from the current clinical 4D CT implementation to the largest degree and provided the simplest and most reproducible implementation. The rescan acquisition increased artifact presence significantly, compared to all acquisitions, and suffered from combination of data from independent scans over which large internal anatomic shifts occurred.

show abstract

“…2). This is consistent with previous findings from correlation‐based image processing techniques (31‐34) . All processing was performed using custom MATLAB software.…”

Section: Methodssupporting

confidence: 87%

Evaluation of 4D CT acquisition methods designed to reduce artifacts

Castillo

et al. 2015

J Applied Clin Med Phys

View full text Add to dashboard Cite

show abstract

“…Similarity between reconstructed images, e.g. using normalised cross correlation can be used [23], [24]. This technique needs special treatment of outlier breathing cycles.…”

Section: Introductionmentioning

confidence: 99%

Device-less gating for PET/CT using PCA

Thielemans¹,

Rathore²,

Engbrant³

et al. 2011

2011 IEEE Nuclear Science Symposium Conference Record

107

118

View full text Add to dashboard Cite

Movement degrades image quality in PET/CT. The first step in correcting for movement is to gate the data into dif ferent motion states. The gating is usually based on information from external devices, such as the chest position for respiratory movement, or an ECG signal for cardiac gating. Various groups have proposed methods to extract a gating signal out of the PET and/or CT data. Most of these methods are slow or require prior information (and associated tuning of parameters). Here we propose and evaluate a method that uses a well-known technique for data analysis called Principal Component Analysis (PCA). We test the method on clinical PET list mode data and CINE CT images to extract a gating signal. We show good correlation with the chest position as measured by the Varian RPM system. Total processing time for PET data is less than half a minute of which most is 10 related. I. IN TRODUCTIONIn many cases in medical imaging, motion is unavoid able. For example, in diagnostic PET, acquisition duration is currently roughly 2 minutes per bed position. Respiratory motion in patients during PET acquisition leads to blurring in the resulting (static) PET images. This may in turn lead to lower detectability of tumours, inaccurate SUV calculation, and incorrect tum or planning volumes in radiation therapy [1], [2], [3], [4]. The first step towards reducing the amount of motion in the images normally involves the use of respiratory gating [5] which results in a 4-D data set, in which multiple gates containing data from the various respiratory states, are usually individually reconstructed. This is then potentially followed by motion correction.In other applications, the different motion states are of interest, for instance in cardiac studies to find the ejection fraction [6] and/or wall motion [7], or in radio-therapy [8].The gating is usually based on information from exter nal devices, such as a spyrometer or the chest position for respiratory movement, or an ECG signal for cardiac gating. Due to the extra cost and patient management associated to the additional device, but also because of some evidence of hysteresis between the internal movement and external device [9], [10], [11], various groups have proposed methods to extract a gating signal out of the PET, SPECT and/or CT data. Many groups compute the centre-of-mass (COM) in an ROI and use this as an indicator of motion, mostly of respiration, for instance in PET [12], [13] and cardiac SPECT [14]. Filtering allows separation of a respiratory and cardiac signal in cardiac PET [15] and cone-beam CINECT [16]. These methods need a high contrast region that can be tracked over time.For PET data, Visvikis et at.[17] placed an ROI over edges of boundaries (using non-attenuation corrected images) and studied the Time Activity Curve (TACs). A characteristic frequency was derived via the Fourier Transform (FT) which then allowed finding amplitude and phase images. This method worked well on phantom data with periodic movement but was not evaluated for patients. Schleyer ...

show abstract

“…The spectral phase masking methods have also be applied in the image domain to cine CT images, and could potentially be used as a surrogate for PET. Additionally, dimensionality reduction techniques should also be applicable to CT. Methods for retrospective stacking in cine CT could also be exploited to use CT gate as a surrogate for PET. However, the CT acquisition in a PET/CT scan is generally shorter than the PET acquisition, in which case a CT‐derived surrogate would not be available for the entire PET scan.…”

Section: Technologies and Techniquesmentioning

confidence: 99%

PET motion correction in context of integrated PET/MR: Current techniques, limitations, and future projections

et al. 2017

View full text Add to dashboard Cite

Patient motion is an important consideration in modern PET image reconstruction. Advances in PET technology mean motion has an increasingly important influence on resulting image quality. Motion-induced artifacts can have adverse effects on clinical outcomes, including missed diagnoses and oversized radiotherapy treatment volumes. This review aims to summarize the wide variety of motion correction techniques available in PET and combined PET/CT and PET/MR, with a focus on the latter. A general framework for the motion correction of PET images is presented, consisting of acquisition, modeling, and correction stages. Methods for measuring, modeling, and correcting motion and associated artifacts, both in literature and commercially available, are presented, and their relative merits are contrasted. Identified limitations of current methods include modeling of aperiodic and/or unpredictable motion, attaining adequate temporal resolution for motion correction in dynamic kinetic modeling acquisitions, and maintaining availability of the MR in PET/MR scans for diagnostic acquisitions. Finally, avenues for future investigation are discussed, with a focus on improvements that could improve PET image quality, and that are practical in the clinical environment.

show abstract

Absolute alignment of breathing states using image similarity derivatives

Cited by 14 publications

References 10 publications

Evaluation of 4D CT acquisition methods designed to reduce artifacts

Evaluation of 4D CT acquisition methods designed to reduce artifacts

Device-less gating for PET/CT using PCA

PET motion correction in context of integrated PET/MR: Current techniques, limitations, and future projections

Contact Info

Product

Resources

About