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Wang L, Sanders J, Ward JF, Lee SR, Poenisch F, Swanson DM, Sahoo N, Zhu XR, Ma J, Kudchadker RJ, Choi SL, Nguyen QN, Mayo LL, Shah SJ, Frank SJ. A Novel Polymer-Encapsulated Multi-Imaging Modality Fiducial Marker with Positive Signal Contrast for Image-Guided Radiation Therapy. Cancers (Basel) 2024; 16:625. [PMID: 38339376 PMCID: PMC10854757 DOI: 10.3390/cancers16030625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 01/22/2024] [Accepted: 01/28/2024] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND Current fiducial markers (FMs) in external-beam radiotherapy (EBRT) for prostate cancer (PCa) cannot be positively visualized on magnetic resonance imaging (MRI) and create dose perturbation and significant imaging artifacts on computed tomography (CT) and MRI. We report our initial experience with clinical imaging of a novel multimodality FM, NOVA. METHODS We tested Gold Anchor [G-FM], BiomarC [carbon, C-FM], and NOVA FMs in phantoms imaged with kilovoltage (kV) X-rays, transrectal ultrasound (TRUS), CT, and MRI. Artifacts of the FMs on CT were quantified by the relative streak artifacts level (rSAL) metric. Proton dose perturbations (PDPs) were measured with Gafchromic EBT3 film, with FMs oriented either perpendicular to or parallel with the beam axis. We also tested the performance of NOVA-FMs in a patient. RESULTS NOVA-FMs were positively visualized on all 4 imaging modalities tested. The rSAL on CT was 0.750 ± 0.335 for 2-mm reconstructed slices. In F-tests, PDP was associated with marker type and depth of measurement (p < 10-6); at 5-mm depth, PDP was significantly greater for the G-FM (12.9%, p = 10-6) and C-FM (6.0%, p = 0.011) than NOVA (4.5%). EBRT planning with MRI/CT image co-registration and daily alignments using NOVA-FMs in a patient was feasible and reproducible. CONCLUSIONS NOVA-FMs were positively visible and produced less PDP than G-FMs or C-FMs. NOVA-FMs facilitated MRI/CT fusion and identification of regions of interest.
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Affiliation(s)
- Li Wang
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Jeremiah Sanders
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (J.S.); (J.M.)
| | - John F. Ward
- Department of Urology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Stephen R. Lee
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Falk Poenisch
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (F.P.); (N.S.); (X.R.Z.); (R.J.K.)
| | - David Michael Swanson
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Narayan Sahoo
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (F.P.); (N.S.); (X.R.Z.); (R.J.K.)
| | - Xiaorong Ronald Zhu
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (F.P.); (N.S.); (X.R.Z.); (R.J.K.)
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (J.S.); (J.M.)
| | - Rajat J. Kudchadker
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (F.P.); (N.S.); (X.R.Z.); (R.J.K.)
| | - Seungtaek L. Choi
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (S.L.C.); (Q.-N.N.); (L.L.M.); (S.J.S.)
| | - Quynh-Nhu Nguyen
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (S.L.C.); (Q.-N.N.); (L.L.M.); (S.J.S.)
| | - Lauren L. Mayo
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (S.L.C.); (Q.-N.N.); (L.L.M.); (S.J.S.)
| | - Shalin J. Shah
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (S.L.C.); (Q.-N.N.); (L.L.M.); (S.J.S.)
| | - Steven J. Frank
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (S.L.C.); (Q.-N.N.); (L.L.M.); (S.J.S.)
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Sanders JW, Tang C, Kudchadker RJ, Venkatesan AM, Mok H, Hanania AN, Thames HD, Bruno TL, Starks C, Santiago E, Cunningham M, Frank SJ. Uncertainty in magnetic resonance imaging-based prostate postimplant dosimetry: Results of a 10-person human observer study, and comparisons with automatic postimplant dosimetry. Brachytherapy 2023; 22:822-832. [PMID: 37716820 DOI: 10.1016/j.brachy.2023.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 04/03/2023] [Accepted: 08/02/2023] [Indexed: 09/18/2023]
Abstract
PURPOSE Uncertainties in postimplant quality assessment (QA) for low-dose-rate prostate brachytherapy (LDRPBT) are introduced at two steps: seed localization and contouring. We quantified how interobserver variability (IoV) introduced in both steps impacts dose-volume-histogram (DVH) parameters for MRI-based LDRPBT, and compared it with automatically derived DVH parameters. METHODS AND MATERIALS Twenty-five patients received MRI-based LDRPBT. Seven clinical observers contoured the prostate and four organs at risk, and 4 dosimetrists performed seed localization, on each MRI. Twenty-eight unique manual postimplant QAs were created for each patient from unique observer pairs. Reference QA and automatic QA were also performed for each patient. IoV of prostate, rectum, and external urinary sphincter (EUS) DVH parameters owing to seed localization and contouring was quantified with coefficients of variation. Automatically derived DVH parameters were compared with those of the reference plans. RESULTS Coefficients of variation (CoVs) owing to contouring variability (CoVcontours) were significantly higher than those due to seed localization variability (CoVseeds) (median CoVcontours vs. median CoVseeds: prostate D90-15.12% vs. 0.65%, p < 0.001; prostate V100-5.36% vs. 0.37%, p < 0.001; rectum V100-79.23% vs. 8.69%, p < 0.001; EUS V200-107.74% vs. 21.18%, p < 0.001). CoVcontours were lower when the contouring observers were restricted to the 3 radiation oncologists, but were still markedly higher than CoVseeds. Median differences in prostate D90, prostate V100, rectum V100, and EUS V200 between automatically computed and reference dosimetry parameters were 3.16%, 1.63%, -0.00 mL, and -0.00 mL, respectively. CONCLUSIONS Seed localization introduces substantially less variability in postimplant QA than does contouring for MRI-based LDRPBT. While automatic seed localization may potentially help improve workflow efficiency, it has limited potential for improving the consistency and quality of postimplant dosimetry.
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Affiliation(s)
- Jeremiah W Sanders
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Chad Tang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Rajat J Kudchadker
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Aradhana M Venkatesan
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Henry Mok
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Howard D Thames
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Teresa L Bruno
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Christine Starks
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Edwin Santiago
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Mandy Cunningham
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Steven J Frank
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
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Vilanova JC, Pérez de Tudela A, Thio-Henestrosa S, Barceló J, Boada M, Planas M, Sala S, Artazkoz J, García-Figueiras R, Baleato-González S, Vilanova C, Puig J. Usefulness of balanced SSFP sequence in robot-assisted MRI-guided prostate biopsy: Beyond scouting. Eur J Radiol 2023; 160:110707. [PMID: 36689791 DOI: 10.1016/j.ejrad.2023.110707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 01/07/2023] [Accepted: 01/17/2023] [Indexed: 01/21/2023]
Abstract
OBJECTIVES To determine whether bSSFP images are useful for visualizing prostatic lesionsin MRI-guided in-bore transrectal biopsy. METHODS This retrospective studyincluded 67 men witha single suspected cancer on MRI (PI-RADS 2.1 category ≥ 3) who underwent in-bore transrectal MRI-guided biopsy. Two uroradiologists independently rated lesion conspicuity on a 3-point scale (1:non-visible, 2:slightly visible, 3:clearly visible) on T2WI, DWI, and balanced SSFP.We used measures of frequency to compare lesion conspicuity in 3 sequences. We used Cohen's kappa to assess inter-rater reliability. RESULTS Lesions were rated (1) non-visible in 18 % (12/67) of T2WI, 5 % (3/67) of DWI, and 10 % (7/67) of balanced SSFP images, (2) slightly visible in 56 % (37/67) on T2WI, 13 % (9/67) on DWI, and 48 % (32/67) on bSSFP, and (3) clearly visible in 27 %(18/67) on T2WI, 82 % (55/67) on DWI, and 42 % (28/67) on bSSFP. Lesions classified as prostate cancer at histology were slightly-clearly visible in 85 % (41/48) on T2WI, 100 % (48/48) on DWI, and 94 % (45/48) on bSSFP. Lesions classified as PI-RADS ≥ 4 were visible in 87 % (47/54) of T2WI, 100 % (54/54) of DWI, and 93 % (50/54) of bSSFP. Gleason ≥ 3 + 4 lesions were visible in 85 % (37/43) of T2WI, 100 % (43/43) of DWI, and 95 % (41/43) of bSSFP. Inter-rater agreement was excellent for T2WI (k = 0.97) and bSSFP (k = 0.94), and good for DWI (k = 0.75). CONCLUSION Balanced SSFP is useful for visualizing prostatic lesions. Replacing T2WI with balanced SSFP can reduce the duration of in-bore transrectal MRI-guided biopsy.
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Affiliation(s)
- Joan C Vilanova
- Department of Magnetic Resonance, Clinica Girona, 17005 Girona, Spain; Research Unit of Diagnostic Imaging Institute (IDI), Department of Radiology (Girona Biomedical Research Institute) IDIBGI, Hospital Universitari Dr. Josep Trueta, 17007 Girona, Spain; Department of Medical Sciences, Faculty of Medicine, University of Girona, 17003 Girona, Spain.
| | | | - Santiago Thio-Henestrosa
- Department of Computer Science, Applied Mathematics and Statistics, University of Girona, 17003 Girona, Spain
| | - Joaquim Barceló
- Department of Magnetic Resonance, Clinica Girona, 17005 Girona, Spain; Research Unit of Diagnostic Imaging Institute (IDI), Department of Radiology (Girona Biomedical Research Institute) IDIBGI, Hospital Universitari Dr. Josep Trueta, 17007 Girona, Spain; Department of Medical Sciences, Faculty of Medicine, University of Girona, 17003 Girona, Spain
| | - Maria Boada
- Department of Magnetic Resonance, Clinica Girona, 17005 Girona, Spain; Department of Medical Sciences, Faculty of Medicine, University of Girona, 17003 Girona, Spain
| | - Montse Planas
- Department of Magnetic Resonance, Clinica Girona, 17005 Girona, Spain
| | - Sònia Sala
- Department of Magnetic Resonance, Clinica Girona, 17005 Girona, Spain
| | - Juanjo Artazkoz
- Department of Medical Sciences, Faculty of Medicine, University of Girona, 17003 Girona, Spain
| | - Roberto García-Figueiras
- Department of Radiology, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706. Spain
| | - Sandra Baleato-González
- Department of Radiology, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706. Spain
| | - Cristina Vilanova
- Hospital Germans Trias i Pujol, Carretera de Canyet, s/n, 08916 Badalona, Barcelona, Spain
| | - Josep Puig
- Research Unit of Diagnostic Imaging Institute (IDI), Department of Radiology (Girona Biomedical Research Institute) IDIBGI, Hospital Universitari Dr. Josep Trueta, 17007 Girona, Spain
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Sanders JW, Kudchadker RJ, Tang C, Mok H, Venkatesan AM, Thames HD, Frank SJ. Prospective Evaluation of Prostate and Organs at Risk Segmentation Software for MRI-based Prostate Radiation Therapy. Radiol Artif Intell 2022; 4:e210151. [PMID: 35391775 DOI: 10.1148/ryai.210151] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 12/20/2021] [Accepted: 01/05/2022] [Indexed: 12/24/2022]
Abstract
The segmentation of the prostate and surrounding organs at risk (OARs) is a necessary workflow step for performing dose-volume histogram analyses of prostate radiation therapy procedures. Low-dose-rate prostate brachytherapy (LDRPBT) is a curative prostate radiation therapy treatment that delivers a single fraction of radiation over a period of days. Prior studies have demonstrated the feasibility of fully convolutional networks to segment the prostate and surrounding OARs for LDRPBT dose-volume histogram analyses. However, performance evaluations have been limited to measures of global similarity between algorithm predictions and a reference. To date, the clinical use of automatic segmentation algorithms for LDRPBT has not been evaluated, to the authors' knowledge. The purpose of this work was to assess the performance of fully convolutional networks for prostate and OAR delineation on a prospectively identified cohort of patients who underwent LDRPBT by using clinically relevant metrics. Thirty patients underwent LDRPBT and were imaged with fully balanced steady-state free precession MRI after implantation. Custom automatic segmentation software was used to segment the prostate and four OARs. Dose-volume histogram analyses were performed by using both the original automatically generated contours and the physician-refined contours. Dosimetry parameters of the prostate, external urinary sphincter, and rectum were compared without and with the physician refinements. This study observed that physician refinements to the automatic contours did not significantly affect dosimetry parameters. Keywords: MRI, Neural Networks, Radiation Therapy, Radiation Therapy/Oncology, Genital/Reproductive, Prostate, Segmentation, Dosimetry Supplemental material is available for this article. © RSNA, 2022.
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Affiliation(s)
- Jeremiah W Sanders
- Departments of Imaging Physics (J.W.S.), Radiation Physics (R.J.K.), Radiation Oncology (C.T., H.M., S.J.F.), Diagnostic Radiology (A.M.V.), and Biostatistics (H.D.T.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Rajat J Kudchadker
- Departments of Imaging Physics (J.W.S.), Radiation Physics (R.J.K.), Radiation Oncology (C.T., H.M., S.J.F.), Diagnostic Radiology (A.M.V.), and Biostatistics (H.D.T.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Chad Tang
- Departments of Imaging Physics (J.W.S.), Radiation Physics (R.J.K.), Radiation Oncology (C.T., H.M., S.J.F.), Diagnostic Radiology (A.M.V.), and Biostatistics (H.D.T.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Henry Mok
- Departments of Imaging Physics (J.W.S.), Radiation Physics (R.J.K.), Radiation Oncology (C.T., H.M., S.J.F.), Diagnostic Radiology (A.M.V.), and Biostatistics (H.D.T.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Aradhana M Venkatesan
- Departments of Imaging Physics (J.W.S.), Radiation Physics (R.J.K.), Radiation Oncology (C.T., H.M., S.J.F.), Diagnostic Radiology (A.M.V.), and Biostatistics (H.D.T.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Howard D Thames
- Departments of Imaging Physics (J.W.S.), Radiation Physics (R.J.K.), Radiation Oncology (C.T., H.M., S.J.F.), Diagnostic Radiology (A.M.V.), and Biostatistics (H.D.T.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Steven J Frank
- Departments of Imaging Physics (J.W.S.), Radiation Physics (R.J.K.), Radiation Oncology (C.T., H.M., S.J.F.), Diagnostic Radiology (A.M.V.), and Biostatistics (H.D.T.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
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Sanders JW, Mok H, Hanania AN, Venkatesan AM, Tang C, Bruno TL, Thames HD, Kudchadker RJ, Frank SJ. Computer-aided segmentation on MRI for prostate radiotherapy, part II: Comparing human and computer observer populations and the influence of annotator variability on algorithm variability. Radiother Oncol 2021; 169:132-139. [PMID: 34979213 DOI: 10.1016/j.radonc.2021.12.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 12/21/2021] [Accepted: 12/22/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND PURPOSE Comparing deep learning (DL) algorithms to human interobserver variability, one of the largest sources of noise in human-performed annotations, is necessary to inform the clinical application, use, and quality assurance of DL for prostate radiotherapy. MATERIALS AND METHODS One hundred fourteen DL algorithms were developed on 295 prostate MRIs to segment the prostate, external urinary sphincter (EUS), seminal vesicles (SV), rectum, and bladder. Fifty prostate MRIs of 25 patients undergoing MRI-based low-dose-rate prostate brachytherapy were acquired as an independent test set. Groups of DL algorithms were created based on the loss functions used to train them, and the spatial entropy (SE) of their predictions on the 50 test MRIs was computed. Five human observers contoured the 50 test MRIs, and SE maps of their contours were compared with those of the groups of the DL algorithms. Additionally, similarity metrics were computed between DL algorithm predictions and consensus annotations of the 5 human observers' contours of the 50 test MRIs. RESULTS A DL algorithm yielded statistically significantly higher similarity metrics for the prostate than did the human observers (H) (prostate Matthew's correlation coefficient, DL vs. H: planning-0.931 vs. 0.903, p < 0.001; postimplant-0.925 vs. 0.892, p < 0.001); the same was true for the 4 organs at risk. The SE maps revealed that the DL algorithms and human annotators were most variable in similar anatomical regions: the prostate-EUS, prostate-SV, prostate-rectum, and prostate-bladder junctions. CONCLUSIONS Annotation quality is an important consideration when developing, evaluating, and using DL algorithms clinically.
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Affiliation(s)
- Jeremiah W Sanders
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, United States.
| | - Henry Mok
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, United States
| | - Alexander N Hanania
- Department of Radiation Oncology, Baylor College of Medicine, Houston, United States
| | - Aradhana M Venkatesan
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, United States
| | - Chad Tang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, United States
| | - Teresa L Bruno
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, United States
| | - Howard D Thames
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, United States
| | - Rajat J Kudchadker
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, United States
| | - Steven J Frank
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, United States
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Sanders JW, Mok H, Hanania AN, Venkatesan AM, Tang C, Bruno TL, Thames HD, Kudchadker RJ, Frank SJ. Computer-aided segmentation on MRI for prostate radiotherapy, Part I: Quantifying human interobserver variability of the prostate and organs at risk and its impact on radiation dosimetry. Radiother Oncol 2021; 169:124-131. [PMID: 34921895 DOI: 10.1016/j.radonc.2021.12.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 11/13/2021] [Accepted: 12/08/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND AND PURPOSE Quantifying the interobserver variability (IoV) of prostate and periprostatic anatomy delineation on prostate MRI is necessary to inform its use for treatment planning, treatment delivery, and treatment quality assessment. MATERIALS AND METHODS Twenty five prostate cancer patients underwent MRI-based low-dose-rate prostate brachytherapy (LDRPBT). The patients were scanned with a 3D T2-weighted sequence for treatment planning and a 3D T2/T1-weighted sequence for quality assessment. Seven observers involved with the LDRPBT workflow delineated the prostate, external urinary sphincter (EUS), seminal vesicles, rectum, and bladder on all 50 MRIs. IoV was assessed by measuring contour similarity metrics, differences in organ volumes, and differences in dosimetry parameters between unique observer pairs. Measurements from a group of 3 radiation oncologists (G1) were compared against those from a group consisting of the other 4 clinical observers (G2). RESULTS IoV of the prostate was lower for G1 than G2 (Matthew's correlation coefficient [MCC], G1 vs. G2: planning-0.906 vs. 0.870, p < 0.001; postimplant-0.899 vs. 0.861, p < 0.001). IoV of the EUS was highest of all the organs for both groups, but was lower for G1 (MCC, G1 vs. G2: planning-0.659 vs. 0.402, p < 0.001; postimplant-0.684 vs. 0.398, p < 0.001). Large differences in prostate dosimetry parameters were observed (G1 maximum absolute prostate ΔD90: planning-76.223 Gy, postimplant-36.545 Gy; G1 maximum absolute prostate ΔV100: planning-13.927%, postimplant-8.860%). CONCLUSIONS While MRI is optimal in the management of prostate cancer with radiation therapy, significant interobserver variability of the prostate and external urinary sphincter still exist.
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Affiliation(s)
- Jeremiah W Sanders
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, USA.
| | - Henry Mok
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA
| | | | - Aradhana M Venkatesan
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, USA
| | - Chad Tang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA
| | - Teresa L Bruno
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA
| | - Howard D Thames
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, USA.
| | - Rajat J Kudchadker
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, USA
| | - Steven J Frank
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA
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Wei S, Li C, Li M, Xiong Y, Jiang Y, Sun H, Qiu B, Lin CJ, Wang J. Radioactive Iodine-125 in Tumor Therapy: Advances and Future Directions. Front Oncol 2021; 11:717180. [PMID: 34660280 PMCID: PMC8514864 DOI: 10.3389/fonc.2021.717180] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 09/07/2021] [Indexed: 12/11/2022] Open
Abstract
Radioactive iodine-125 (I-125) is the most widely used radioactive sealed source for interstitial permanent brachytherapy (BT). BT has the exceptional ability to deliver extremely high doses that external beam radiotherapy (EBRT) could never achieve within treated lesions, with the added benefit that doses drop off rapidly outside the target lesion by minimizing the exposure of uninvolved surrounding normal tissue. Spurred by multiple biological and technological advances, BT application has experienced substantial alteration over the past few decades. The procedure of I-125 radioactive seed implantation evolved from ultrasound guidance to computed tomography guidance. Compellingly, the creative introduction of 3D-printed individual templates, BT treatment planning systems, and artificial intelligence navigator systems remarkably increased the accuracy of I-125 BT and individualized I-125 ablative radiotherapy. Of note, utilizing I-125 to treat carcinoma in hollow cavity organs was enabled by the utility of self-expandable metal stents (SEMSs). Initially, I-125 BT was only used in the treatment of rare tumors. However, an increasing number of clinical trials upheld the efficacy and safety of I-125 BT in almost all tumors. Therefore, this study aims to summarize the recent advances of I-125 BT in cancer therapy, which cover experimental research to clinical investigations, including the development of novel techniques. This review also raises unanswered questions that may prompt future clinical trials and experimental work.
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Affiliation(s)
- Shuhua Wei
- Department of Radiation Oncology, Peking University 3rd Hospital, Beijing, China
| | - Chunxiao Li
- Department of Radiation Oncology, Peking University 3rd Hospital, Beijing, China
| | - Mengyuan Li
- Department of Radiation Oncology, Peking University 3rd Hospital, Beijing, China
| | - Yan Xiong
- Department of Radiation Oncology, Peking University 3rd Hospital, Beijing, China
| | - Yuliang Jiang
- Department of Radiation Oncology, Peking University 3rd Hospital, Beijing, China
| | - Haitao Sun
- Department of Radiation Oncology, Peking University 3rd Hospital, Beijing, China
| | - Bin Qiu
- Department of Radiation Oncology, Peking University 3rd Hospital, Beijing, China
| | | | - Junjie Wang
- Department of Radiation Oncology, Peking University 3rd Hospital, Beijing, China
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