GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    WEPL ASSESSMENT VIA FLAT PANEL PROTON RADIOGRAPHY WITH A PATIENT SPECIFIC IMAGING FIELD
    Elsevier BV ; 2022
    In:  Physica Medica Vol. 104 ( 2022-12), p. S109-
    Details
    In: Physica Medica, Elsevier BV, Vol. 104 ( 2022-12), p. S109-
    Type of Medium: Online Resource
    ISSN: 1120-1797
    URL: Article
    DOI: 10.1016/S1120-1797(22)02374-2
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 1122650-X
    detail.hit.zdb_id: 2110535-2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    Comparison of CBCT based synthetic CT methods suitable for proton dose calculations in adaptive proton therapy
    IOP Publishing ; 2020
    In:  Physics in Medicine & Biology Vol. 65, No. 9 ( 2020-05-07), p. 095002-
    Details
    In: Physics in Medicine & Biology, IOP Publishing, Vol. 65, No. 9 ( 2020-05-07), p. 095002-
    Abstract: In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation decisions. Image quality deficiencies though, hamper dose calculation accuracy and make corrections of CBCTs a necessity. This study compared three methods to correct CBCTs and create synthetic CTs that are suitable for proton dose calculations. CBCTs, planning CTs and repeated CTs (rCT) from 33 H & N cancer patients were used to compare a deep convolutional neural network (DCNN), deformable image registration (DIR) and an analytical image-based correction method (AIC) for synthetic CT (sCT) generation. Image quality of sCTs was evaluated by comparison with a same-day rCT, using mean absolute error (MAE), mean error (ME), Dice similarity coefficient (DSC), structural non-uniformity (SNU) and signal/contrast-to-noise ratios (SNR/CNR) as metrics. Dosimetric accuracy was investigated in an intracranial setting by performing gamma analysis and calculating range shifts. Neural network-based sCTs resulted in the lowest MAE and ME (37/2 HU) and the highest DSC (0.96). While DIR and AIC generated images with a MAE of 44/77 HU, a ME of −8/1 HU and a DSC of 0.94/0.90. Gamma and range shift analysis showed almost no dosimetric difference between DCNN and DIR based sCTs. The lower image quality of AIC based sCTs affected dosimetric accuracy and resulted in lower pass ratios and higher range shifts. Patient-specific differences highlighted the advantages and disadvantages of each method. For the set of patients, the DCNN created synthetic CTs with the highest image quality. Accurate proton dose calculations were achieved by both DCNN and DIR based sCTs. The AIC method resulted in lower image quality and dose calculation accuracy was reduced compared to the other methods.
    Type of Medium: Online Resource
    ISSN: 0031-9155 , 1361-6560
    URL: Article
    DOI: 10.1088/1361-6560/ab7d54
    RVK:
    WA 15000
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2020
    detail.hit.zdb_id: 1473501-5
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 3
    Online Resource
    Online Resource
    Technical Note: First report on an in vivo range probing quality control procedure for scanned proton beam therapy in head and neck cancer patients
    Wiley ; 2021
    In:  Medical Physics Vol. 48, No. 3 ( 2021-03), p. 1372-1380
    Details
    In: Medical Physics, Wiley, Vol. 48, No. 3 ( 2021-03), p. 1372-1380
    Abstract: The capability of proton therapy to provide highly conformal dose distributions is impaired by range uncertainties. The aim of this work is to apply range probing (RP), a form of a proton radiography‐based quality control (QC) procedure for range accuracy assessment in head and neck cancer (HNC) patients in a clinical setting. Methods and Materials This study included seven HNC patients. RP acquisition was performed using a multi‐layer ionization chamber (MLIC). Per patient, two RP frames were acquired within the first two weeks of treatment, on days when a repeated CT scan was obtained. Per RP frame, integral depth dose (IDD) curves of 81 spots around the treatment isocenter were acquired. Range errors are determined as a discrepancy between calculated IDDs in the treatment planning system and measured residual ranges by the MLIC. Range errors are presented relative to the water equivalent path length of individual proton spots. In addition to reporting results for complete measurement frames, an analysis, excluding range error contributions due to anatomical changes, is presented. Results Discrepancies between measured and calculated ranges are smaller when performing RP calculations on the day‐specific patient anatomy rather than the planning CT. The patient‐specific range evaluation shows an agreement between calculated and measured ranges for spots in anatomically consistent areas within 3% (1.5 standard deviation). Conclusions The results of an RP‐based QC procedure implemented in the clinical practice for HNC patients have been demonstrated. The agreement of measured and simulated proton ranges confirms the 3% uncertainty margin for robust optimization. Anatomical variations show a predominant effect on range accuracy, motivating efforts towards the implementation of adaptive radiotherapy.
    Type of Medium: Online Resource
    ISSN: 0094-2405 , 2473-4209
    URL: Issue
    URL: Article
    DOI: 10.1002/mp.v48.3
    DOI: 10.1002/mp.14713
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 1466421-5
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 4
    Online Resource
    Online Resource
    Optimizing calibration settings for accurate water equivalent path length assessment using flat panel proton radiography
    IOP Publishing ; 2021
    In:  Physics in Medicine & Biology Vol. 66, No. 21 ( 2021-11-07), p. 21NT02-
    Details
    In: Physics in Medicine & Biology, IOP Publishing, Vol. 66, No. 21 ( 2021-11-07), p. 21NT02-
    Abstract: Objective: Proton range uncertainties can compromise the effectiveness of proton therapy treatments. Water equivalent path length (WEPL) assessment by flat panel detector proton radiography (FP-PR) can provide means of range uncertainty detection. Since WEPL accuracy intrinsically relies on the FP-PR calibration parameters, the purpose of this study is to establish an optimal calibration procedure that ensures high accuracy of WEPL measurements. To that end, several calibration settings were investigated. Approach: FP-PR calibration datasets were obtained simulating PR fields with different proton energies, directed towards water-equivalent material slabs of increasing thickness. The parameters investigated were the spacing between energy layers (Δ E ) and the increment in thickness of the water-equivalent material slabs (Δ X ) used for calibration. 30 calibrations were simulated, as a result of combining Δ E  = 9, 7, 5, 3, 1 MeV and Δ X  = 10, 8, 5, 3, 2, 1 mm. FP-PRs through a CIRS electron density phantom were simulated, and WEPL images corresponding to each calibration were obtained. Ground truth WEPL values were provided by range probing multi-layer ionization chamber simulations on each insert of the phantom. Relative WEPL errors between FP-PR simulations and ground truth were calculated for each insert. Mean relative WEPL errors and standard deviations across all inserts were computed for WEPL images obtained with each calibration. Main results: Large mean and standard deviations were found in WEPL images obtained with large Δ E values (Δ E  = 9 or 7 MeV), for any Δ X . WEPL images obtained with Δ E  ≤ 5 MeV and Δ X  ≤ 5 mm resulted in a WEPL accuracy with mean values within ±0.5% and standard deviations around 1%. Significance: An optimal FP calibration in the framework of this study was established, characterized by 3 MeV ≤ Δ E  ≤ 5 MeV and 2 mm ≤ Δ X  ≤ 5 mm. Within these boundaries, highly accurate WEPL acquisitions using FP-PR are feasible and practical, holding the potential to assist future online range verification quality control procedures.
    Type of Medium: Online Resource
    ISSN: 0031-9155 , 1361-6560
    URL: Article
    DOI: 10.1088/1361-6560/ac2c4f
    RVK:
    WA 15000
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2021
    detail.hit.zdb_id: 1473501-5
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 5
    Online Resource
    Online Resource
    Comparison of the suitability of CBCT- and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients
    IOP Publishing ; 2020
    In:  Physics in Medicine & Biology Vol. 65, No. 23 ( 2020-12-07), p. 235036-
    Details
    In: Physics in Medicine & Biology, IOP Publishing, Vol. 65, No. 23 ( 2020-12-07), p. 235036-
    Abstract: Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep convolutional neural networks. In this study, we compared sCTs based on CBCTs and MRs for head and neck (H & N) cancer patients in terms of image quality and proton dose calculation accuracy. A dataset of 27 H & N-patients, treated with proton therapy (PT), containing planning CTs (pCTs), repeat CTs, CBCTs and MRs were used to train two neural networks to convert either CBCTs or MRs into sCTs. Image quality was quantified by calculating mean absolute error (MAE), mean error (ME) and Dice similarity coefficient (DSC) for bones. The dose evaluation consisted of a systematic non-clinical analysis and a clinical recalculation of actually used proton treatment plans. Gamma analysis was performed for non-clinical and clinical treatment plans. For clinical treatment plans also dose to targets and organs at risk (OARs) and normal tissue complication probabilities (NTCP) were compared. CBCT-based sCTs resulted in higher image quality with an average MAE of 40 ± 4 HU and a DSC of 0.95, while for MR-based sCTs a MAE of 65 ± 4 HU and a DSC of 0.89 was observed. Also in clinical proton dose calculations, sCT CBCT achieved higher average gamma pass ratios (2%/2 mm criteria) than sCT MR (96.1% vs. 93.3%). Dose-volume histograms for selected OARs and NTCP-values showed a very small difference between sCT CBCT and sCT MR and a high agreement with the reference pCT. CBCT- and MR-based sCTs have the potential to enable accurate proton dose calculations valuable for daily adaptive PT. Significant image quality differences were observed but did not affect proton dose calculation accuracy in a similar manner. Especially the recalculation of clinical treatment plans showed high agreement with the pCT for both sCT CBCT and sCT MR.
    Type of Medium: Online Resource
    ISSN: 0031-9155 , 1361-6560
    URL: Article
    DOI: 10.1088/1361-6560/abb1d6
    RVK:
    WA 15000
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2020
    detail.hit.zdb_id: 1473501-5
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 6
    Online Resource
    Online Resource
    Classification of various sources of error in range assessment using proton radiography and neural networks in head and neck cancer patients
    IOP Publishing ; 2020
    In:  Physics in Medicine & Biology Vol. 65, No. 23 ( 2020-12-07), p. 235009-
    Details
    In: Physics in Medicine & Biology, IOP Publishing, Vol. 65, No. 23 ( 2020-12-07), p. 235009-
    Abstract: This study evaluates the suitability of convolutional neural networks (CNNs) to automatically process proton radiography (PR)-based images. CNNs are used to classify PR images impaired by several sources of error affecting the proton range, more precisely setup and calibration curve errors. PR simulations were performed in 40 head and neck cancer patients, at three different anatomical locations (fields A, B and C, centered for head and neck, neck and base of skull coverage). Field sizes were 26 × 26cm 2 for field A and 4.5 × 4.5cm 2 for fields B and C. Range shift maps were obtained by comparing an unperturbed reference PR against a PR where one or more sources of error affected the proton range. CT calibration curve errors in soft, bone and fat tissues and setup errors in the anterior–posterior and inferior–superior directions were simulated individually and in combination. A CNN was trained for each type of PR field, leading to three CNNs trained with a mixture of range shift maps arising from one or more sources of range error. To test the full/partial/wrong agreement between predicted and actual sources of range error in the range shift maps, exact, partial and wrong match percentages were computed for an independent test dataset containing range shift maps arising from isolated or combined errors, retrospectively. The CNN corresponding to field A showed superior capability to detect isolated and combined errors, with exact matches of 92% and 71% respectively. Field B showed exact matches of 80% and 54%, and field C resulted in exact matches of 77% and 41%. The suitability of CNNs to classify PR-based images containing different sources of error affecting the proton range was demonstrated. This procedure enables the detection of setup and calibration curve errors when they appear individually or in combination, providing valuable information for the interpretation of PR images.
    Type of Medium: Online Resource
    ISSN: 0031-9155 , 1361-6560
    URL: Article
    DOI: 10.1088/1361-6560/abc09c
    RVK:
    WA 15000
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2020
    detail.hit.zdb_id: 1473501-5
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...