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Frackowiak B, Van den Bosch V, Tokoutsi Z, Baragona M, de Greef M, Elevelt A, Isfort P. First validation of a model-based hepatic percutaneous microwave ablation planning on a clinical dataset. Sci Rep 2023; 13:16862. [PMID: 37803064 PMCID: PMC10558472 DOI: 10.1038/s41598-023-42543-x] [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: 04/05/2023] [Accepted: 09/12/2023] [Indexed: 10/08/2023] Open
Abstract
A model-based planning tool, integrated in an imaging system, is envisioned for CT-guided percutaneous microwave ablation. This study aims to evaluate the biophysical model performance, by comparing its prediction retrospectively with the actual ablation ground truth from a clinical dataset in liver. The biophysical model uses a simplified formulation of heat deposition on the applicator and a heat sink related to vasculature to solve the bioheat equation. A performance metric is defined to assess how the planned ablation overlaps the actual ground truth. Results demonstrate superiority of this model prediction compared to manufacturer tabulated data and a significant influence of the vasculature cooling effect. Nevertheless, vasculature shortage due to branches occlusion and applicator misalignment due to registration error between scans affects the thermal prediction. With a more accurate vasculature segmentation, occlusion risk can be estimated, whereas branches can be used as liver landmarks to improve the registration accuracy. Overall, this study emphasizes the benefit of a model-based thermal ablation solution in better planning the ablation procedures. Contrast and registration protocols must be adapted to facilitate its integration into the clinical workflow.
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Affiliation(s)
- Bruno Frackowiak
- Philips Research, Data Science & Digital Twin, 5656 AE, Eindhoven, The Netherlands.
| | - Vincent Van den Bosch
- Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, 52074, Aachen, Germany
| | - Zoi Tokoutsi
- Philips Research, Data Science & Digital Twin, 5656 AE, Eindhoven, The Netherlands
| | - Marco Baragona
- Philips Research, Data Science & Digital Twin, 5656 AE, Eindhoven, The Netherlands
| | - Martijn de Greef
- Philips Research, Data Science & Digital Twin, 5656 AE, Eindhoven, The Netherlands
| | - Aaldert Elevelt
- Philips Research, Data Science & Digital Twin, 5656 AE, Eindhoven, The Netherlands
| | - Peter Isfort
- Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, 52074, Aachen, Germany
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Moreira P, Tuncali K, Tempany C, Tokuda J. AI-Based Isotherm Prediction for Focal Cryoablation of Prostate Cancer. Acad Radiol 2023; 30 Suppl 1:S14-S20. [PMID: 37236896 PMCID: PMC10524864 DOI: 10.1016/j.acra.2023.04.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 04/04/2023] [Accepted: 04/15/2023] [Indexed: 05/28/2023]
Abstract
RATIONALE AND OBJECTIVES Focal therapies have emerged as minimally invasive alternatives for patients with localized low-risk prostate cancer (PCa) and those with postradiation recurrence. Among the available focal treatment methods for PCa, cryoablation offers several technical advantages, including the visibility of the boundaries of frozen tissue on the intraprocedural images, access to anterior lesions, and the proven ability to treat postradiation recurrence. However, predicting the final volume of the frozen tissue is challenging as it depends on several patient-specific factors, such as proximity to heat sources and thermal properties of the prostatic tissue. MATERIALS AND METHODS This paper presents a convolutional neural network model based on 3D-Unet to predict the frozen isotherm boundaries (iceball) resultant from a given a cryo-needle placement. Intraprocedural magnetic resonance images acquired during 38 cases of focal cryoablation of PCa were retrospectively used to train and validate the model. The model accuracy was assessed and compared against a vendor-provided geometrical model, which is used as a guideline in routine procedures. RESULTS The mean Dice Similarity Coefficient using the proposed model was 0.79±0.08 (mean+SD) vs 0.72±0.06 using the geometrical model (P<.001). CONCLUSION The model provided an accurate iceball boundary prediction in less than 0.4second and has proven its feasibility to be implemented in an intraprocedural planning algorithm.
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Affiliation(s)
- Pedro Moreira
- Brigham and Women's Hospital, 75 Francis St, Boston, MA 22115 (P.M., K.T., C.T., J.T.); Harvard Medical School, 25 Shattuck St, Boston, MA 02115 (P.M., K.T., C.T., J.T.).
| | - Kemal Tuncali
- Brigham and Women's Hospital, 75 Francis St, Boston, MA 22115 (P.M., K.T., C.T., J.T.); Harvard Medical School, 25 Shattuck St, Boston, MA 02115 (P.M., K.T., C.T., J.T.)
| | - Clare Tempany
- Brigham and Women's Hospital, 75 Francis St, Boston, MA 22115 (P.M., K.T., C.T., J.T.); Harvard Medical School, 25 Shattuck St, Boston, MA 02115 (P.M., K.T., C.T., J.T.)
| | - Junichi Tokuda
- Brigham and Women's Hospital, 75 Francis St, Boston, MA 22115 (P.M., K.T., C.T., J.T.); Harvard Medical School, 25 Shattuck St, Boston, MA 02115 (P.M., K.T., C.T., J.T.)
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Frackowiak B, Van den Bosch V, Tokoutsi Z, Baragona M, de Greef M, Elevelt A, Isfort P. Model-based hepatic percutaneous microwaveablation planning. First validation on a clinical dataset. RESEARCH SQUARE 2023:rs.3.rs-2781339. [PMID: 37131766 PMCID: PMC10153367 DOI: 10.21203/rs.3.rs-2781339/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
A model-based planning tool, integrated in an imaging system, is envisioned for CT-guided percutaneous microwave ablation. This study aims to evaluate the biophysical model performance, by comparing its prediction retrospectively with the actualablation ground truth from a clinical data set in liver. The biophysical model uses a simplified formulation of heat depositionon the applicator and a heat sink related to vasculature to solve the bioheat equation. A performance metric is defined toassess how the planned ablation overlaps the actual ground truth. Results demonstrate superiority of this model predictioncompared to manufacturer tabulated data and a significant influence of the vasculature cooling effect. Nevertheless, vasculatureshortage due to branches occlusion and applicator misalignment due to registration error between scans affects the thermalprediction. With a more accurate vasculature segmentation, occlusion risk can be estimated, whereas branches can be usedas liver landmarks to improve the registration accuracy. Overall, this study emphasizes the benefit of a model-based thermalablation solution in better planning the ablation procedures. Contrast and registration protocols must be adapted to facilitate itsintegration into the clinical workflow.
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Affiliation(s)
- Bruno Frackowiak
- Philips Research, Data Science & Digital Twin,Eindhoven,5656AE, Netherlands
| | - Vincent Van den Bosch
- Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, 52074, Germany
| | - Zoi Tokoutsi
- Philips Research, Data Science & Digital Twin,Eindhoven,5656AE, Netherlands
| | - Marco Baragona
- Philips Research, Data Science & Digital Twin,Eindhoven,5656AE, Netherlands
| | - Martijn de Greef
- Philips Research, Data Science & Digital Twin,Eindhoven,5656AE, Netherlands
| | - Aaldert Elevelt
- Philips Research, Data Science & Digital Twin,Eindhoven,5656AE, Netherlands
| | - Peter Isfort
- Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, 52074, Germany
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de Jager NS, van Oostenbrugge TJ, Pätz T, Jenniskens SFM, Fütterer JJ, Langenhuijsen JF, Overduin CG. Intraoperative MRI-derived volumetric ablation margins and initial correlation with local outcome after MRI-guided cryoablation of renal tumors. Cancer Imaging 2023; 23:31. [PMID: 36998028 PMCID: PMC10064595 DOI: 10.1186/s40644-023-00546-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 03/15/2023] [Indexed: 04/01/2023] Open
Abstract
PURPOSE To assess volumetric ablation margins derived from intraoperative pre- and post-ablation MRI after magnetic resonance imaging (MRI)-guided percutaneous cryoablation of renal tumors and explore its correlation with local treatment success. METHODS Retrospective analysis was performed on 30 patients (mean age 69y) who underwent percutaneous MRI-guided cryoablation between May 2014 and May 2020 for 32 renal tumors (size: 1.6-5.1 cm). Tumor and ice-ball volumes were segmented on intraprocedural pre- and post-ablation MR images using Software Assistant for Interventional Radiology (SAFIR) software. After MRI-MRI co-registration, the software automatically quantified the minimal treatment margin (MTM),defined as the smallest 3D distance between the tumor and ice-ball surface. Local tumor progression (LTP) after cryoablation was assessed on follow-up imaging. RESULTS Median follow-up was 16 months (range: 1-58). Local control after cryoablation was achieved in 26 cases (81%) while LTP occurred in 6 (19%). The intended MTM of ≥5 mm was achieved in 3/32 (9%) cases. Median MTM was significantly smaller for cases with (- 7 mm; IQR:-10 to - 5) vs. without LTP (3 mm; IQR:2 to 4) (P < .001). All cases of LTP had a negative MTM. All negative treatment margins occurred in tumors > 3 cm. CONCLUSIONS Determination of volumetric ablation margins from intraoperative MRI was feasible and may be useful in predicting local outcome after MRI-guided renal cryoablation. In our preliminary data, an intraoperative MRI-derived minimal margin extending at least 1 mm beyond the MRI-visible tumor led to local control and this was more difficult to achieve in tumors > 3 cm. Ultimately, online margin analysis may be a valuable tool to intraoperatively assess therapy success, but larger prospective studies are needed to establish a reliable threshold for clinical use.
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Affiliation(s)
- Nienke S de Jager
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, P.O. Box 9101, 6525, Nijmegen, GA, Netherlands
| | - Tim J van Oostenbrugge
- Department of Urology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525, Nijmegen, GA, Netherlands
| | - Torben Pätz
- Fraunhofer Institute for Digital Medicine, Max-von-Laue-Str. 2, 28359, Bremen, Germany
| | - Sjoerd F M Jenniskens
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, P.O. Box 9101, 6525, Nijmegen, GA, Netherlands
| | - Jurgen J Fütterer
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, P.O. Box 9101, 6525, Nijmegen, GA, Netherlands
| | - Johan F Langenhuijsen
- Department of Urology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525, Nijmegen, GA, Netherlands
| | - Christiaan G Overduin
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, P.O. Box 9101, 6525, Nijmegen, GA, Netherlands.
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Condino S, Cutolo F, Cattari N, Colangeli S, Parchi PD, Piazza R, Ruinato AD, Capanna R, Ferrari V. Hybrid Simulation and Planning Platform for Cryosurgery with Microsoft HoloLens. SENSORS 2021; 21:s21134450. [PMID: 34209748 PMCID: PMC8272062 DOI: 10.3390/s21134450] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 06/23/2021] [Accepted: 06/25/2021] [Indexed: 11/16/2022]
Abstract
Cryosurgery is a technique of growing popularity involving tissue ablation under controlled freezing. Technological advancement of devices along with surgical technique improvements have turned cryosurgery from an experimental to an established option for treating several diseases. However, cryosurgery is still limited by inaccurate planning based primarily on 2D visualization of the patient’s preoperative images. Several works have been aimed at modelling cryoablation through heat transfer simulations; however, most software applications do not meet some key requirements for clinical routine use, such as high computational speed and user-friendliness. This work aims to develop an intuitive platform for anatomical understanding and pre-operative planning by integrating the information content of radiological images and cryoprobe specifications either in a 3D virtual environment (desktop application) or in a hybrid simulator, which exploits the potential of the 3D printing and augmented reality functionalities of Microsoft HoloLens. The proposed platform was preliminarily validated for the retrospective planning/simulation of two surgical cases. Results suggest that the platform is easy and quick to learn and could be used in clinical practice to improve anatomical understanding, to make surgical planning easier than the traditional method, and to strengthen the memorization of surgical planning.
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Affiliation(s)
- Sara Condino
- Information Engineering Department, University of Pisa, 56126 Pisa, Italy; (F.C.); (V.F.)
- Correspondence:
| | - Fabrizio Cutolo
- Information Engineering Department, University of Pisa, 56126 Pisa, Italy; (F.C.); (V.F.)
| | - Nadia Cattari
- EndoCAS Center, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy; (N.C.); (R.P.); (A.D.R.)
| | - Simone Colangeli
- Orthopaedic and Traumatology Division, Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, 56124 Pisa, Italy; (S.C.); (P.D.P.); (R.C.)
| | - Paolo Domenico Parchi
- Orthopaedic and Traumatology Division, Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, 56124 Pisa, Italy; (S.C.); (P.D.P.); (R.C.)
| | - Roberta Piazza
- EndoCAS Center, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy; (N.C.); (R.P.); (A.D.R.)
| | - Alfio Damiano Ruinato
- EndoCAS Center, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy; (N.C.); (R.P.); (A.D.R.)
| | - Rodolfo Capanna
- Orthopaedic and Traumatology Division, Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, 56124 Pisa, Italy; (S.C.); (P.D.P.); (R.C.)
| | - Vincenzo Ferrari
- Information Engineering Department, University of Pisa, 56126 Pisa, Italy; (F.C.); (V.F.)
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Sebek J, Taeprasartsit P, Wibowo H, Beard WL, Bortel R, Prakash P. Microwave ablation of lung tumors: A probabilistic approach for simulation-based treatment planning. Med Phys 2021; 48:3991-4003. [PMID: 33964020 DOI: 10.1002/mp.14923] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 04/16/2021] [Accepted: 04/17/2021] [Indexed: 12/16/2022] Open
Abstract
PURPOSE Microwave ablation (MWA) is a clinically established modality for treatment of lung tumors. A challenge with existing application of MWA, however, is local tumor progression, potentially due to failure to establish an adequate treatment margin. This study presents a robust simulation-based treatment planning methodology to assist operators in comparatively assessing thermal profiles and likelihood of achieving a specified minimum margin as a function of candidate applied energy parameters. METHODS We employed a biophysical simulation-based probabilistic treatment planning methodology to evaluate the likelihood of achieving a specified minimum margin for candidate treatment parameters (i.e., applied power and ablation duration for a given applicator position within a tumor). A set of simulations with varying tissue properties was evaluated for each considered combination of power and ablation duration, and for four different scenarios of contrast in tissue biophysical properties between tumor and normal lung. A treatment planning graph was then assembled, where distributions of achieved minimum ablation zone margins and collateral damage volumes can be assessed for candidate applied power and treatment duration combinations. For each chosen power and time combination, the operator can also visualize the histogram of ablation zone boundaries overlaid on the tumor and target volumes. We assembled treatment planning graphs for generic 1, 2, and 2.5 cm diameter spherically shaped tumors and also illustrated the impact of tissue heterogeneity on delivered treatment plans and resulting ablation histograms. Finally, we illustrated the treatment planning methodology on two example patient-specific cases of tumors with irregular shapes. RESULTS The assembled treatment planning graphs indicate that 30 W, 6 min ablations achieve a 5-mm minimum margin across all simulated cases for 1-cm diameter spherical tumors, and 70 W, 10 min ablations achieve a 3-mm minimum margin across 90% of simulations for a 2.5-cm diameter spherical tumor. Different scenarios of tissue heterogeneity between tumor and lung tissue revealed 2 min overall difference in ablation duration, in order to reliably achieve a 4-mm minimum margin or larger each time for 2-cm diameter spherical tumor. CONCLUSIONS An approach for simulation-based treatment planning for microwave ablation of lung tumors is illustrated to account for the impact of specific geometry of the treatment site, tissue property uncertainty, and heterogeneity between the tumor and normal lung.
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Affiliation(s)
- Jan Sebek
- Department of Electrical and Computer Engineering, Kansas State University Manhattan, KS, 66506, USA.,Department of Circuit Theory, Czech Technical University in Prague, Prague, Czech Republic
| | - Pinyo Taeprasartsit
- PhenoMapper, LLC, San Jose, CA, 95112, USA.,Department of Computing, Faculty of Science, Silpakorn University, Thailand
| | | | - Warren L Beard
- Department of Clinical Sciences, Kansas State University, Manhattan, KS, 66506, USA
| | - Radoslav Bortel
- Department of Circuit Theory, Czech Technical University in Prague, Prague, Czech Republic
| | - Punit Prakash
- Department of Electrical and Computer Engineering, Kansas State University Manhattan, KS, 66506, USA
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