Two‐stage ionoacoustic range verification leveraging Monte Carlo and acoustic simulations to stably account for tissue inhomogeneity and accelerator–specific time structure – A simulation study

Patch, S. K.; Hoff, D. E. M.; Webb, Tyler; Sobotka, L. G.; Zhao, Tianyu

doi:10.1002/mp.12681

Cited by 21 publications

(18 citation statements)

References 43 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…68 By projecting the cumulatively-integrated pressure waves measured at a few detectors, a beam-forming reconstruction has also been used. 69 Although the Bragg peak distance is close to that predicted by the zero cross-over point between compression and rarefaction peaks, there is no universally correct arrival time definition; the Bragg peak asymmetry imprints itself on the acoustic wave in a complicated way that depends on detector position. 62 Depending on the used arrival time definition, an offset might be required.…”

Section: B Recent Workmentioning

confidence: 82%

“…A number of methods have been used, including measuring the arrival time from the compression peak, the midpoint between compression peak and rarefaction trough, deconvolving the proton pulse, and measuring from the earliest appearance of the pressure wave . By projecting the cumulatively‐integrated pressure waves measured at a few detectors, a beam‐forming reconstruction has also been used . Although the Bragg peak distance is close to that predicted by the zero cross‐over point between compression and rarefaction peaks, there is no universally correct arrival time definition; the Bragg peak asymmetry imprints itself on the acoustic wave in a complicated way that depends on detector position .…”

Section: Proton Therapy Range Verificationmentioning

confidence: 99%

“…Of these, the speed of sound dependence appears to be the most challenging hurdle for accurate range verification because the time‐of‐flight calculation requires knowledge of the speed of sound. To understand the effects of heterogeneity, CT‐based k‐Wave simulations have been performed that assign the Grüneisen coefficient and speed of sound to each voxel based on the tissue type, as determined by Hounsfield Unit value . Simulations by Patch et al.…”

Section: Proton Therapy Range Verificationmentioning

confidence: 99%

“…predict that accurate range verification is achievable during a clinical prostate treatment using a transrectal probe. By comparing the measured acoustic wave arrival times to a precalculated simulated dataset, local heterogeneity‐induced variations could be corrected to give <2 mm errors in range calculation accuracy . Another set of simulations compared the acoustic propagation of the same initial pressure distribution over homogeneous water and heterogeneous liver and prostate sites, as shown in Fig.…”

Section: Proton Therapy Range Verificationmentioning

confidence: 99%

“…paper — can offer an elegant means to overcome the issue of local heterogeneities. Although no multielement, low frequency arrays have yet been used in the context of acoustic‐based proton range verification, triangulation with as few as 3–5 detectors is expected to improve SNR and minimize errors introduced by heterogeneous tissue …”

Section: Proton Therapy Range Verificationmentioning

confidence: 99%

See 4 more Smart Citations

Ionizing radiation‐induced acoustics for radiotherapy and diagnostic radiology applications

et al. 2018

View full text Add to dashboard Cite

Acoustic waves are induced via the thermoacoustic effect in objects exposed to a pulsed beam of ionizing radiation. This phenomenon has interesting potential applications in both radiotherapy dosimetry and treatment guidance as well as low-dose radiological imaging. After initial work in the field in the 1980s and early 1990s, little research was done until 2013 when interest was rejuvenated, spurred on by technological advances in ultrasound transducers and the increasing complexity of radiotherapy delivery systems. Since then, many studies have been conducted and published applying ionizing radiation-induced acoustic principles into three primary research areas: Linear accelerator photon beam dosimetry, proton therapy range verification, and radiological imaging. This review article introduces the theoretical background behind ionizing radiation-induced acoustic waves, summarizes recent advances in the field, and provides an outlook on how the detection of ionizing radiationinduced acoustic waves can be used for relative and in vivo dosimetry in photon therapy, localization of the Bragg peak in proton therapy, and as a low-dose medical imaging modality. Future prospects and challenges for the clinical implementation of these techniques are discussed.

show abstract

Section: B Recent Workmentioning

confidence: 82%

Section: Proton Therapy Range Verificationmentioning

confidence: 99%

Section: Proton Therapy Range Verificationmentioning

confidence: 99%

Section: Proton Therapy Range Verificationmentioning

confidence: 99%

Section: Proton Therapy Range Verificationmentioning

confidence: 99%

See 3 more Smart Citations

Ionizing radiation‐induced acoustics for radiotherapy and diagnostic radiology applications

et al. 2018

View full text Add to dashboard Cite

show abstract

In vivo range verification in particle therapy

2018

View full text Add to dashboard Cite

Exploitation of the full potential offered by ion beams in clinical practice is still hampered by several sources of treatment uncertainties, particularly related to limitations of our ability to locate the position of the Bragg peak in the tumour. To this end, several efforts are ongoing to improve the characterization of patient position, anatomy and tissue stopping power properties prior to treatment, as well as to enable in-vivo verification of the actual dose delivery, or at least beam range, during or shortly after treatment. This contribution critically reviews methods under development or clinical testing for verification of ion therapy, based on pre-treatment range and tissue probing as well as detection of secondary emissions or physiological changes during and after treatment, trying to disentangle approaches of general applicability from those more specific to certain anatomical locations. Moreover, it discusses future directions, which could benefit from integration of multiple modalities or address novel exploitation of the measurable signals for biologically adapted therapy.

show abstract

Thermoacoustic range verification in the presence of acoustic heterogeneity and soundspeed errors – Robustness relative to ultrasound image of underlying anatomy

2018

Self Cite

View full text Add to dashboard Cite

Purpose: To demonstrate robustness of thermooacoustic range verification to acoustic heterogeneity and discrepancies between assumed and true propagation speed, i.e., soundspeed errors. Methods: A beam sweeper was used to deliver 250 ns pulses that deposited 0.26 Gy of 16 MeV protons and 2.3 Gy of 60 MeV helium ions into water and oil targets, respectively. Thermoacoustic signals were detected by a 96-channel ultrasound array with a 1-4 MHz sensitivity band (À6 dB), bandpass filtered and backprojected to create thermoacoustic images in the plane of the ultrasound array. The same soundspeed and transducer array were used to estimate range and generate the ultrasound images onto which Bragg peak locations were overlaid. An air-gap phantom that displaced the Bragg peak by 6.5 mm demonstrated accuracy. Robustness to soundspeed errors was demonstrated in a waterbath as the assumed propagation speed scanner setting was altered by AE5%. Tissue-mimicking gelatin and a bone sample were introduced to demonstrate robustness to acoustic heterogeneity relative to ultrasound images of the underlying morphology. Results: Single ion pulse measurements sufficed during the helium run, but signal averaging was required for protons. Range and entry point into the target were estimated from data collected by transducers placed at least 6 cm distal to the Bragg peak. When ultrasound images depicted the airtarget interface where the beam enters, estimates of the entry point agreed with ultrasound images and range estimates agreed with Monte Carlo simulations to within 300 lm, even when thermoacoustic emissions traveled through a strongly scattering bone sample. Estimated Bragg peak locations were translated 6.5 mm by the air-gap phantom and correctly identified scenarios when the beam stopped inside the bone. Conclusions: Soundspeed errors dilate and acoustic heterogeneities deform ultrasound images. When thermoacoustic receivers are co-located with the ultrasound imaging array, the same transformations shift thermoacoustic range estimates. Therefore, thermoacoustic range verification is robust relative to ultrasound images of underlying anatomy. When the treatment target is visible in ultrasound, e.g., prostate, online thermoacoustic range estimates could verify that the treatment spot is inside the target.

show abstract

Two‐stage ionoacoustic range verification leveraging Monte Carlo and acoustic simulations to stably account for tissue inhomogeneity and accelerator–specific time structure – A simulation study

Cited by 21 publications

References 43 publications

Ionizing radiation‐induced acoustics for radiotherapy and diagnostic radiology applications

Ionizing radiation‐induced acoustics for radiotherapy and diagnostic radiology applications

In vivo range verification in particle therapy

Thermoacoustic range verification in the presence of acoustic heterogeneity and soundspeed errors – Robustness relative to ultrasound image of underlying anatomy

Contact Info

Product

Resources

About