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Li M, Liu J, Liu F, Lv R, Bai H, Liu S. Predictive Value of Corrected 18 F-FDG PET/CT Baseline Parameters for Primary DLBCL Prognosis: A Single-center Study. World J Nucl Med 2024; 23:33-42. [PMID: 38595841 PMCID: PMC11001458 DOI: 10.1055/s-0044-1779282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2024] Open
Abstract
Objective The purpose of this study was to evaluate the prognostic significance of corrected baseline metabolic parameters in fluorodeoxyglucose positron emission tomography imaging ( 18 F-FDG PET/CT) for 3-year progression-free survival (PFS) in patients with primary diffuse large B cell lymphoma (DLBCL). Patients and Methods Retrospective clinical and pathological data were collected for 199 patients of DLBCL diagnosed between January 2018 and January 2021. All patients underwent 18 F-FDG PET/CT scans without any form of treatment. The corrected maximum standardized uptake value (corSUVmax), corrected mean standardized uptake value (corSUVmean), corrected whole-body tumor metabolic volume sum (corMTVsum), and corrected total lesion glycolysis of whole body (corTLGtotal) were corrected using the SUVmean in a 1-cm diameter mediastinal blood pool (MBP) from the descending thoracic aorta of patients. Kaplan-Meier survival curves and Cox regression were used to examine the predictive significance of corrected baseline metabolic parameters on 3-year PFS of patients. The incremental values of corrected baseline metabolic parameters were evaluated by using Harrell's C-indices, receiver operating characteristic, and Decision Curve Analysis. Results The multivariate analysis revealed that only the National Comprehensive Cancer Network (NCCN)-International Prognostic Index (IPI) and corMTVsum had an effect on 3-year PFS of patients ( p < 0.05, respectively). The Kaplan-Meier survival analysis demonstrated significant differences in PFS between the risk groups classified by corSUVsum, corMTVsum, and corTLGtotal (log-rank test, p < 0.05). The predictive model composed of corMTVsum and corTLGtotal surpasses the predictive performance of the model incorporating MTVsum and TLGtotal. The optimal performance was observed when corMTVsum was combined with NCCN-IPI, resulting in a Harrell's C index of 0.785 and area under the curve values of 0.863, 0.891, and 0.947 for the 1-, 2-, and 3-year PFS rates, respectively. Conclusion The corMTVsum offers significant prognostic value for patients with DLBCL. Furthermore, the combination of corMTVsum with the NCCN-IPI can provide an accurate prediction of the prognosis.
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Affiliation(s)
- Min Li
- Department of Nuclear Medicine, Tai'an Central Hospital of Qingdao University, Tai'an, Shandong, People's Republic of China
| | - Jianpeng Liu
- Department of Radiology, Huashan Hospital of Fudan University, Shanghai, People's Republic of China
| | - Fangfei Liu
- Department of Nuclear Medicine, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China
| | - Rongbin Lv
- Department of Nuclear Medicine, Tai'an Central Hospital of Qingdao University, Tai'an, Shandong, People's Republic of China
| | - Haowei Bai
- Department of Nuclear Medicine, Tai'an Central Hospital of Qingdao University, Tai'an, Shandong, People's Republic of China
| | - Shuyong Liu
- Department of Nuclear Medicine, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China
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Luining WI, Oprea-Lager DE, Vis AN, van Moorselaar RJA, Knol RJJ, Wondergem M, Boellaard R, Cysouw MCF. Optimization and validation of 18F-DCFPyL PET radiomics-based machine learning models in intermediate- to high-risk primary prostate cancer. PLoS One 2023; 18:e0293672. [PMID: 37943772 PMCID: PMC10635444 DOI: 10.1371/journal.pone.0293672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 10/17/2023] [Indexed: 11/12/2023] Open
Abstract
INTRODUCTION Radiomics extracted from prostate-specific membrane antigen (PSMA)-PET modeled with machine learning (ML) may be used for prediction of disease risk. However, validation of previously proposed approaches is lacking. We aimed to optimize and validate ML models based on 18F-DCFPyL-PET radiomics for the prediction of lymph-node involvement (LNI), extracapsular extension (ECE), and postoperative Gleason score (GS) in primary prostate cancer (PCa) patients. METHODS Patients with intermediate- to high-risk PCa who underwent 18F-DCFPyL-PET/CT before radical prostatectomy with pelvic lymph-node dissection were evaluated. The training dataset included 72 patients, the internal validation dataset 24 patients, and the external validation dataset 27 patients. PSMA-avid intra-prostatic lesions were delineated semi-automatically on PET and 480 radiomics features were extracted. Conventional PET-metrics were derived for comparative analysis. Segmentation, preprocessing, and ML methods were optimized in repeated 5-fold cross-validation (CV) on the training dataset. The trained models were tested on the combined validation dataset. Combat harmonization was applied to external radiomics data. Model performance was assessed using the receiver-operating-characteristics curve (AUC). RESULTS The CV-AUCs in the training dataset were 0.88, 0.79 and 0.84 for LNI, ECE, and GS, respectively. In the combined validation dataset, the ML models could significantly predict GS with an AUC of 0.78 (p<0.05). However, validation AUCs for LNI and ECE prediction were not significant (0.57 and 0.63, respectively). Conventional PET metrics-based models had comparable AUCs for LNI (0.59, p>0.05) and ECE (0.66, p>0.05), but a lower AUC for GS (0.73, p<0.05). In general, Combat harmonization improved external validation AUCs (-0.03 to +0.18). CONCLUSION In internal and external validation, 18F-DCFPyL-PET radiomics-based ML models predicted high postoperative GS but not LNI or ECE in intermediate- to high-risk PCa. Therefore, the clinical benefit seems to be limited. These results underline the need for external and/or multicenter validation of PET radiomics-based ML model analyses to assess their generalizability.
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Affiliation(s)
- Wietske I. Luining
- Department of Urology, Amsterdam University Medical Centers, Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Daniela E. Oprea-Lager
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - André N. Vis
- Department of Urology, Amsterdam University Medical Centers, Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
| | - Reindert J. A. van Moorselaar
- Department of Urology, Amsterdam University Medical Centers, Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
| | - Remco J. J. Knol
- Department of Nuclear Medicine, Northwest Clinics, Alkmaar, The Netherlands
| | - Maurits Wondergem
- Department of Nuclear Medicine, Northwest Clinics, Alkmaar, The Netherlands
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Matthijs C. F. Cysouw
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, Cancer Center Amsterdam, Amsterdam, The Netherlands
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Weissinger M, Kommoss S, Jacoby J, Ursprung S, Seith F, Hoffmann S, Nikolaou K, Brucker SY, La Fougère C, Dittmann H. Multiparametric Dual-Time-Point [18F]FDG PET/MRI for Lymph Node Staging in Patients with Untreated FIGO I/II Cervical Carcinoma. J Clin Med 2022; 11:jcm11174943. [PMID: 36078873 PMCID: PMC9456388 DOI: 10.3390/jcm11174943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 08/15/2022] [Accepted: 08/17/2022] [Indexed: 11/16/2022] Open
Abstract
[18F]FDG PET/MRI was shown to have limited sensitivity for N-staging in FIGO I/II cervical carcinoma. Therefore, this prospective study aimed to investigate the additional value of multiparametric dual-time-point PET/MRI and to assess potential influencing factors for lymph node metastasis (LNM) detection. A total of 63 patients underwent whole-body dual-time-point [18F]FDG PET/MRI 60 + 90 min p.i., and 251 LN were evaluated visually, quantified multiparametrically, and correlated with histology. Grading of the primary tumor (G2/G3) had a significant impact on visual detection (sens: 8.3%/31%). The best single parameter for LNM detection was SUVavg, however, with a significant loss of discriminatory power in G2 vs. G3 tumors (AUC: 0.673/0.901). The independent predictors SUVavg, ∆SUVpeak, LN sphericity, ADC, and histologic grade were included in the logistic-regression-based malignancy score (MS) for multiparametric analysis. Application of MS enhanced AUCs, especially in G2 tumors (AUC: G2:0.769; G3:0.877) and improved the accuracy for single LNM from 34.5% to 55.5% compared with the best univariate parameter SUVavg. Compared with visual analysis, the use of the malignancy score increased the overall sensitivity from 31.0% to 79.3% (Youden optimum) with a moderate decrease in specificity from 98.3% to 75.6%. These findings indicate that multiparametric evaluation of dual-time-point PET/MRI has the potential to improve accuracy compared with visual interpretation and enables sufficient N-staging also in G2 cervical carcinoma.
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Affiliation(s)
- Matthias Weissinger
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, 72076 Tuebingen, Germany
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Hoppe Seyler-Straße 3, 72076 Tuebingen, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, 72076 Tuebingen, Germany
| | - Stefan Kommoss
- Department of Women’s Health, University Hospital Tuebingen, 72076 Tuebingen, Germany
| | - Johann Jacoby
- Institute for Clinical Epidemiology and Applied Biometry, University Hospital Tuebingen, 72076 Tuebingen, Germany
| | - Stephan Ursprung
- Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, 72076 Tuebingen, Germany
| | - Ferdinand Seith
- Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, 72076 Tuebingen, Germany
| | - Sascha Hoffmann
- Department of Women’s Health, University Hospital Tuebingen, 72076 Tuebingen, Germany
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, 72076 Tuebingen, Germany
- iFIT-Cluster of Excellence, Eberhard Karls University Tuebingen, 72074 Tuebingen, Germany
- German Cancer Consortium (DKTK), Partner Site Tuebingen, 69120 Heidelberg, Germany
| | - Sara Yvonne Brucker
- Department of Women’s Health, University Hospital Tuebingen, 72076 Tuebingen, Germany
| | - Christian La Fougère
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, 72076 Tuebingen, Germany
- iFIT-Cluster of Excellence, Eberhard Karls University Tuebingen, 72074 Tuebingen, Germany
- German Cancer Consortium (DKTK), Partner Site Tuebingen, 69120 Heidelberg, Germany
- Correspondence: ; Tel.: +49-7071-2986553; Fax: +49-7071-29-4601
| | - Helmut Dittmann
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, 72076 Tuebingen, Germany
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Pesqué L, Delyon J, Lheure C, Baroudjian B, Battistella M, Merlet P, Lebbé C, Vercellino L. Yield of FDG PET/CT for Defining the Extent of Disease in Patients with Kaposi Sarcoma. Cancers (Basel) 2022; 14:cancers14092189. [PMID: 35565319 PMCID: PMC9102885 DOI: 10.3390/cancers14092189] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/15/2022] [Accepted: 04/21/2022] [Indexed: 11/18/2022] Open
Abstract
Simple Summary The potential role of positron emission tomography/computed tomography with fluorodeoxyglucose (FDG PET/CT) for assessing the extent of Kaposi sarcoma is not well studied. We analyzed FDG PET/CTs performed on 75 patients referred to our department for Kaposi sarcoma staging or restaging. FDG PET/CTs detected most lymph nodes, bone, and muscle lesions, whereas digestive and mucous lesions could be missed. Most cutaneous lesions can be identified when whole-body FDG PET/CT (including lower limbs) is performed. Thus, a true whole-body FDG PET/CT can be recommended for staging purposes in patients with active Kaposi sarcoma and, if positive, be useful for therapeutic evaluation and follow-up. Abstract Background: Positron emission tomography/computed tomography with fluorodeoxyglucose (F-18) (FDG PET/CT) is increasingly used in Kaposi sarcoma (KS), but its value has not been assessed. Objectives: In this study, we aimed to evaluate the diagnostic accuracy of FDG PET/CT to define the extent of disease in KS. Methods: Consecutive patients with KS referred to our department for FDG PET/CT were included. The diagnostic accuracy of FDG PET/CT for cutaneous and extra-cutaneous KS staging was assessed on a per lesion basis compared to staging obtained from clinical examination, standard imaging, endoscopy, histological analyses, and follow-up. Results: From 2007 to 2017, 75 patients with FDG PET/CT were analyzed. The sensitivity and specificity of FDG PET/CT for the overall detection of KS lesions were 71 and 98%, respectively. Sensitivity and specificity were 100 and 85% for lymph nodes, 87 and 98% for bone, 87 and 100% for lungs, and 100 and 100% for muscle involvement, whereas sensitivity was only 17% to detect KS digestive involvement. The sensitivity of the diagnostic for KS cutaneous involvement increased from 73 to 88% when using a whole-body examination. Conclusion: FDG PET/CT showed good sensitivity and specificity for KS staging (digestive involvement excepted) and could be used for staging patients with active KS.
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Affiliation(s)
- Louise Pesqué
- Nuclear Medicine Department, Saint Louis University Hospital, Assistance-Publique Hôpitaux de Paris, 1 Avenue Claude Vellefaux, 75010 Paris, France; (L.P.); (P.M.)
| | - Julie Delyon
- Department of Dermatology, Saint Louis University Hospital, Assistance-Publique Hôpitaux de Paris, 1 Avenue Claude Vellefaux, 75010 Paris, France; (J.D.); (B.B.); (C.L.)
- INSERM HIPI Team 1, U976, Saint Louis University Hospital, 1 Avenue Claude Vellefaux, 75010 Paris, France;
- Université de Paris Cité, 75006 Paris, France;
| | - Coralie Lheure
- Université de Paris Cité, 75006 Paris, France;
- Department of Dermatology, Cochin University Hospital, 27, Rue du Faubourg-Saint-Jacques, 75014 Paris, France
| | - Barouyr Baroudjian
- Department of Dermatology, Saint Louis University Hospital, Assistance-Publique Hôpitaux de Paris, 1 Avenue Claude Vellefaux, 75010 Paris, France; (J.D.); (B.B.); (C.L.)
| | - Maxime Battistella
- INSERM HIPI Team 1, U976, Saint Louis University Hospital, 1 Avenue Claude Vellefaux, 75010 Paris, France;
- Université de Paris Cité, 75006 Paris, France;
- Department of Pathology, Saint Louis University Hospital, Assistance-Publique Hôpitaux de Paris, 1 Avenue Claude Vellefaux, 75010 Paris, France
| | - Pascal Merlet
- Nuclear Medicine Department, Saint Louis University Hospital, Assistance-Publique Hôpitaux de Paris, 1 Avenue Claude Vellefaux, 75010 Paris, France; (L.P.); (P.M.)
- Université de Paris Cité, 75006 Paris, France;
| | - Céleste Lebbé
- Department of Dermatology, Saint Louis University Hospital, Assistance-Publique Hôpitaux de Paris, 1 Avenue Claude Vellefaux, 75010 Paris, France; (J.D.); (B.B.); (C.L.)
- INSERM HIPI Team 1, U976, Saint Louis University Hospital, 1 Avenue Claude Vellefaux, 75010 Paris, France;
- Université de Paris Cité, 75006 Paris, France;
| | - Laetitia Vercellino
- Nuclear Medicine Department, Saint Louis University Hospital, Assistance-Publique Hôpitaux de Paris, 1 Avenue Claude Vellefaux, 75010 Paris, France; (L.P.); (P.M.)
- Université de Paris, INSERM, UMR_S942 MASCOT, 75006 Paris, France
- Correspondence: ; Tel.: +33-142499411
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Driscoll B, Shek T, Vines D, Sun A, Jaffray D, Yeung I. Phantom Validation of a Conservation of Activity-Based Partial Volume Correction Method for Arterial Input Function in Dynamic PET Imaging. Tomography 2022; 8:842-857. [PMID: 35314646 PMCID: PMC8938778 DOI: 10.3390/tomography8020069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 03/10/2022] [Accepted: 03/16/2022] [Indexed: 11/16/2022] Open
Abstract
Dynamic PET (dPET) imaging can be utilized to perform kinetic modelling of various physiologic processes, which are exploited by the constantly expanding range of targeted radiopharmaceuticals. To date, dPET remains primarily in the research realm due to a number of technical challenges, not least of which is addressing partial volume effects (PVE) in the input function. We propose a series of equations for the correction of PVE in the input function and present the results of a validation study, based on a purpose built phantom. 18F-dPET experiments were performed using the phantom on a set of flow tubes representing large arteries, such as the aorta (1" 2.54 cm ID), down to smaller vessels, such as the iliac arteries and veins (1/4" 0.635 cm ID). When applied to the dPET experimental images, the PVE correction equations were able to successfully correct the image-derived input functions by as much as 59 ± 35% in the presence of background, which resulted in image-derived area under the curve (AUC) values within 8 ± 9% of ground truth AUC. The peak heights were similarly well corrected to within 9 ± 10% of the scaled DCE-CT curves. The same equations were then successfully applied to correct patient input functions in the aorta and internal iliac artery/vein. These straightforward algorithms can be applied to dPET images from any PET-CT scanner to restore the input function back to a more clinically representative value, without the need for high-end Time of Flight systems or Point Spread Function correction algorithms.
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Affiliation(s)
- Brandon Driscoll
- Quantitative Imaging for Personalized Cancer Medicine (QIPCM)—Techna Institute, University Health Network, Toronto, ON M5G 2C4, Canada; (T.S.); (D.J.); (I.Y.)
- Correspondence:
| | - Tina Shek
- Quantitative Imaging for Personalized Cancer Medicine (QIPCM)—Techna Institute, University Health Network, Toronto, ON M5G 2C4, Canada; (T.S.); (D.J.); (I.Y.)
| | - Douglass Vines
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada; (D.V.); (A.S.)
- Department of Radiation Oncology, University of Toronto, Toronto, ON M5T 1P5, Canada
| | - Alex Sun
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada; (D.V.); (A.S.)
- Department of Radiation Oncology, University of Toronto, Toronto, ON M5T 1P5, Canada
| | - David Jaffray
- Quantitative Imaging for Personalized Cancer Medicine (QIPCM)—Techna Institute, University Health Network, Toronto, ON M5G 2C4, Canada; (T.S.); (D.J.); (I.Y.)
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada; (D.V.); (A.S.)
- Department of Radiation Oncology, University of Toronto, Toronto, ON M5T 1P5, Canada
| | - Ivan Yeung
- Quantitative Imaging for Personalized Cancer Medicine (QIPCM)—Techna Institute, University Health Network, Toronto, ON M5G 2C4, Canada; (T.S.); (D.J.); (I.Y.)
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada; (D.V.); (A.S.)
- Department of Radiation Oncology, University of Toronto, Toronto, ON M5T 1P5, Canada
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Neira-Castro S, Guiu-Souto J, Pardo-Montero J. Dosimetry in positron emission tomography. Nucl Med Mol Imaging 2022. [DOI: 10.1016/b978-0-12-822960-6.00026-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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Ren T, Nedzvedz O, Ye F, Jiang J, Nedzved A, Gurevich I, Yashina V. Reconstruction of the Volume of Affected Lymph Nodes on Positron Emission and Computed Tomography Images. PATTERN RECOGNITION AND IMAGE ANALYSIS 2021. [DOI: 10.1134/s1054661821040180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Weissinger M, Taran FA, Gatidis S, Kommoss S, Nikolaou K, Sahbai S, Fougère CL, Brucker SY, Dittmann H. Lymph Node Staging with a Combined Protocol of 18F-FDG PET/MRI and Sentinel Node SPECT/CT: A Prospective Study in Patients with FIGO I/II Cervical Carcinoma. J Nucl Med 2021; 62:1062-1067. [PMID: 33509973 PMCID: PMC8833872 DOI: 10.2967/jnumed.120.255919] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 12/04/2020] [Indexed: 11/16/2022] Open
Abstract
Lymph node metastasis (LNM) is present in a minority of patients with early stages of cervical carcinomas. As conventional imaging including PET/CT has shown limited sensitivity, systematic lymphadenectomies are often conducted for staging purposes. Therefore, the aim of this prospective study was to analyze the impact of 18F-FDG PET/MRI in addition to sentinel lymph node (SLN) biopsy on lymph node (LN) status. Methods: Forty-two women with an initial diagnosis of Fédération Internationale de Gynécologie et d'Obstétrique (FIGO) IA-IIB cervical carcinoma were included between March 2016 and April 2019. Each patient underwent preoperative whole-body 18F-FDG PET/MRI and SLN imaging with SPECT/CT after intracervical injection of 99mTc-labeled nanocolloid. Systematic lymphadenectomy and SLN biopsy served as the reference standard. Staging using PET/MRI was performed by nuclear medicine and radiology experts working in consensus. Results: One patient was excluded from surgical staging because of liver metastases newly diagnosed on PET/MRI. The overall prevalence of LNM in the remaining 41 patients was 29.3% (12/41). Five of 12 patients with LNM had solely small metastases with a maximum diameter of 5 mm. The consensus interpretation showed PET/MRI to have a specificity of 100% (29/29; 95% CI, 88.3%-100%) for LNM staging but a low sensitivity, 33.3% (4/12; 95% CI, 12.8%-60.9%). LN size was the most important factor for the detectability of metastases, since only LNMs larger than 5 mm could be identified by PET/MRI (sensitivity, 57.1% for >5 mm and 0% for ≤5 mm). Paraaortic LNM was evaluated accurately in 3 of the 4 patients with paraaortic LN metastasis. SLNs were detectable by SPECT/CT in 82.9% of the patients or 69.0% of the hemipelves. In cases with an undetectable SLN on SPECT/CT, the malignancy rate was considerably higher (31.2% vs. 19.3%). The combination of PET/MRI and SLN SPECT/CT improved the detection of pelvic LNM from 33.3% to 75%. Conclusion:18F-FDG PET/MRI is a highly specific N-staging method and improves LNM detection. Because of the limited sensitivity in frequently occurring small LNMs, PET/MRI should be combined with SLN mapping. The proposed combined protocol helps to decide whether extensive surgical staging is necessary in patients with FIGO I/II cervical cancer.
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Affiliation(s)
- Matthias Weissinger
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, Tuebingen, Germany
| | - Florin-Andrei Taran
- Department of Women's Health, University Hospital Zurich, Zurich, Switzerland
| | - Sergios Gatidis
- Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Tuebingen, Germany
| | - Stefan Kommoss
- Department of Women's Health, University Hospital Tuebingen, Tuebingen, Germany
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Tuebingen, Germany
- iFIT Cluster of Excellence, Eberhard Karls University Tuebingen, Tuebingen, Germany; and
- German Cancer Consortium, Partner Site Tuebingen, Germany
| | - Samine Sahbai
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, Tuebingen, Germany
| | - Christian la Fougère
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, Tuebingen, Germany;
- iFIT Cluster of Excellence, Eberhard Karls University Tuebingen, Tuebingen, Germany; and
- German Cancer Consortium, Partner Site Tuebingen, Germany
| | - Sara Yvonne Brucker
- Department of Women's Health, University Hospital Tuebingen, Tuebingen, Germany;
| | - Helmut Dittmann
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, Tuebingen, Germany;
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Mittlmeier LM, Brendel M, Beyer L, Albert NL, Todica A, Zacherl MJ, Wenter V, Herlemann A, Kretschmer A, Ledderose ST, Schmidt-Hegemann NS, Kunz WG, Ricke J, Bartenstein P, Ilhan H, Unterrainer M. Feasibility of Different Tumor Delineation Approaches for 18F-PSMA-1007 PET/CT Imaging in Prostate Cancer Patients. Front Oncol 2021; 11:663631. [PMID: 34094956 PMCID: PMC8176856 DOI: 10.3389/fonc.2021.663631] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 04/19/2021] [Indexed: 12/22/2022] Open
Abstract
Background Delineation of PSMA-positive tumor volume on PET using PSMA-ligands is of highest clinical interest as changes of PSMA-PET/CT-derived whole tumor volume (WTV) have shown to correlate with treatment response in metastatic prostate cancer patients. So far, WTV estimation was performed on PET using 68Ga-labeled ligands; nonetheless, 18F-labeled PET ligands are gaining increasing importance due to advantages over 68Ga-labeled compounds. However, standardized tumor delineation methods for 18F-labeled PET ligands have not been established so far. As correlation of PET-based information and morphological extent in osseous and visceral metastases is hampered by morphological delineation, low contrast in liver tissue and movement artefacts, we correlated CT-based volume of lymph node metastases (LNM) and different PET-based delineation approaches for thresholding on 18F-PSMA-1007 PET. Methods Fifty patients with metastatic prostate cancer, 18F-PSMA-1007 PET/CT and non-bulky LNM (short-axis diameter ≥10mm) were included. Fifty LNM were volumetrically assessed on contrast-enhanced CT (volumetric reference standard). Different approaches for tumor volume delineation were applied and correlated with the reference standard: I) fixed SUV threshold, II) isocontour thresholding relative to SUVmax (SUV%), and thresholds relative to III) liver (SUVliver), IV) parotis (SUVparotis) and V) spleen (SUVspleen). Results A fixed SUV of 4.0 (r=0.807, r2 = 0.651, p<0.001) showed the best overall association with the volumetric reference. 55% SUVmax (r=0.627, r2 = 0.393, p<0.001) showed highest association using an isocontour-based threshold. Best background-based approaches were 60% SUVliver (r=0.715, r2 = 0.511, p<0.001), 80% SUVparotis (r=0.762, r2 = 0.581, p<0.001) and 60% SUVspleen (r=0.645, r2 = 0.416, p<0.001). Background tissues SUVliver, SUVparotis & SUVspleen did not correlate (p>0.05 each). Recently reported cut-offs for intraprostatic tumor delineation (isocontour 44% SUVmax, 42% SUVmax and 20% SUVmax) revealed inferior association for LNM delineation. Conclusions A threshold of SUV 4.0 for tumor delineation showed highest association with volumetric reference standard irrespective of potential changes in PSMA-avidity of background tissues (e. g. parotis). This approach is easily applicable in clinical routine without specific software requirements. Further studies applying this approach for total tumor volume delineation are initiated.
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Affiliation(s)
- Lena M Mittlmeier
- Department of Nuclear Medicine, University Hospital, Ludwig Maximilian University (LMU) Munich, Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital, Ludwig Maximilian University (LMU) Munich, Munich, Germany
| | - Leonie Beyer
- Department of Nuclear Medicine, University Hospital, Ludwig Maximilian University (LMU) Munich, Munich, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, University Hospital, Ludwig Maximilian University (LMU) Munich, Munich, Germany
| | - Andrei Todica
- Department of Nuclear Medicine, University Hospital, Ludwig Maximilian University (LMU) Munich, Munich, Germany
| | - Mathias J Zacherl
- Department of Nuclear Medicine, University Hospital, Ludwig Maximilian University (LMU) Munich, Munich, Germany
| | - Vera Wenter
- Department of Nuclear Medicine, University Hospital, Ludwig Maximilian University (LMU) Munich, Munich, Germany
| | - Annika Herlemann
- Department of Urology, University Hospital, LMU Munich, Munich, Germany
| | | | | | | | - Wolfgang G Kunz
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Jens Ricke
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, University Hospital, Ludwig Maximilian University (LMU) Munich, Munich, Germany
| | - Harun Ilhan
- Department of Nuclear Medicine, University Hospital, Ludwig Maximilian University (LMU) Munich, Munich, Germany
| | - Marcus Unterrainer
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
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10
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Jin J, Wu K, Li X, Yu Y, Wang X, Sun H. Relationship between tumor heterogeneity and volume in cervical cancer: Evidence from integrated fluorodeoxyglucose 18 PET/MR texture analysis. Nucl Med Commun 2021; 42:545-552. [PMID: 33323868 DOI: 10.1097/mnm.0000000000001354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
OBJECTIVE The aim of this study was to evaluate the effect of cervical cancer volume on PET/magnetic resonance (MR) texture heterogeneity. MATERIALS AND METHODS We retrospectively analyzed the PET/MR images of 138 patients with pathologically diagnosed cervical squamous cell carcinoma, including 50 patients undergoing surgery and 88 patients receiving concurrent chemoradiotherapy. Fluorodeoxyglucose 18 (18FDG)-PET/MR examination were performed for each patient before treatment, and the PET and MR texture analysis were undertaken. The texture features of the tumor based on gray-level co-occurrence matrices were extracted, and the correlation between tumor texture features and volume parameters was analyzed using Spearman's rank correlation coefficient. Finally, the variation trend of tumor texture heterogeneity was analyzed as tumor volumes increased. RESULTS PET texture features were highly correlated with metabolic tumor volume (MTV), including entropy-log2, entropy-log10, energy, homogeneity, dissimilarity, contrast, correlation, and the correlation coefficients (rs) were 0.955, 0.955, -0.897, 0.883, -0.881, -0.876, and 0.847 (P < 0.001), respectively. In the range of smaller MTV, the texture heterogeneity of energy, entropy-log2, and entropy-log10 increases with an increase in tumor volume, whereas the texture heterogeneity of homogeneity, dissimilarity, contrast, and correlation decreases with an increase in tumor volume. Only homogeneity, contrast, correlation, and dissimilarity had high correlation with tumor volume on MRI. The correlation coefficients (rs) were 0.76, -0.737, 0.644, and -0.739 (P < 0.001), respectively. The texture heterogeneity of MRI features that are highly correlated with tumor volume decreases with increasing tumor volume. CONCLUSION In the small tumor volume range, the heterogeneity variation trend of PET texture features is inconsistent as the tumor volume increases, but the variation trend of MRI texture heterogeneity is consistent, and MRI texture heterogeneity decreases as tumor volume increases. These results suggest that MRI is a better imaging modality when compared with PET in determining tumor texture heterogeneity in the small tumor volume range.
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Affiliation(s)
- Junjie Jin
- Department of Radiology, Shengjing Hospital of China Medical University
- Liaoning Provincial Key Laboratory of Medical Imaging
| | - Ke Wu
- Department of Radiology, Shengjing Hospital of China Medical University
| | - Xiaoran Li
- Department of Radiology, Shengjing Hospital of China Medical University
| | - Yang Yu
- Department of Nuclear Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xinghao Wang
- Department of Radiology, Shengjing Hospital of China Medical University
| | - Hongzan Sun
- Department of Radiology, Shengjing Hospital of China Medical University
- Liaoning Provincial Key Laboratory of Medical Imaging
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Computed tomography-based skeletal segmentation for quantitative PET metrics of bone involvement in multiple myeloma. Nucl Med Commun 2021; 41:377-382. [PMID: 32058446 PMCID: PMC7077955 DOI: 10.1097/mnm.0000000000001165] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Purpose Quantifications in nuclear medicine are occasionally limited by the lack of standardization for defining volumes of interest (VOIs) on functional images. In the present article, we propose the use of computed tomography (CT)–based skeletal segmentation to determine anatomically the VOI in order to calculate quantitative parameters of fluorine 18 fluorodeoxyglucose (18F-FDG) PET/CT images from patients with multiple myeloma. Methods We evaluated 101 whole-body 18F-FDG PET/CTs of 58 patients with multiple myeloma. An initial subjective visual analysis of the PET images was used to classify the bone involvement as negative/mild, moderate, or marked. Then, a fully automated CT–based segmentation of the skeleton was performed on PET images. The maximum, mean, and SD of the standardized uptake values (SUVmax, SUVmean, and SDSUV) were calculated for bone tissue and compared with the visual analysis. Results Forty-five (44.5%), 32 (31.7%), and 24 (23.8%) PET images were, respectively, classified as negative/mild, moderate, or marked bone involvement. All quantitative parameters were significantly related to the visual assessment of bone involvement. This association was stronger for the SUVmean [odds ratio (OR): 10.52 (95% confidence interval (CI), 5.68–19.48); P < 0.0001] and for the SDSUV [OR: 5.58 (95% CI, 3.31–9.42); P < 0.001) than for the SUVmax [OR: 1.01 (95% CI, 1.003–1.022); P = 0.003]. Conclusion CT–based skeletal segmentation allows for automated and therefore reproducible calculation of PET quantitative parameters of bone involvement in patients with multiple myeloma. Using this method, the SUVmean and its respective SD correlated better with the visual analysis of 18F-FDG PET images than SUVmax. Its value in staging and evaluating therapy response needs to be evaluated.
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12
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Mouminah A, Borja AJ, Hancin EC, Chang YC, Werner TJ, Swisher-McClure S, Korostoff J, Alavi A, Revheim ME. 18F-FDG-PET/CT in radiation therapy-induced parotid gland inflammation. Eur J Hybrid Imaging 2020; 4:22. [PMID: 34191165 PMCID: PMC8218117 DOI: 10.1186/s41824-020-00091-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 10/12/2020] [Indexed: 12/21/2022] Open
Abstract
Background 18F-fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) is used in the clinical management of oncologic and inflammatory pathologies. It may have utility in detecting radiotherapy (RT)-induced damage of oral tissues. Thus, the aim of the present study was to use FDG-PET/CT to evaluate parotid gland inflammation following RT in patients with head and neck cancer (HNC). Methods This retrospective study included patients with HNC treated with photon, proton, or combined photon/proton RT, in addition to chemotherapy. All patients received FDG-PET/CT imaging pre-treatment and 3 months post-treatment. The average mean standardized uptake value (Avg SUVmean) and the average maximum standardized uptake value (Avg SUVmax) of the left and right parotid glands were determined by global assessment of FDG activity using OsiriX MD software. A two-tailed paired t test was used to compare Avg SUVmean and Avg SUVmax pre- and post-RT. Results Forty-seven HNC patients were included in the study. Parotid gland Avg SUVmean was significantly higher at 3 months post-treatment than pre-treatment (p < 0.05) in patients treated with photon RT, but no significant differences were found between pre- and post-treatment Avg SUVmean in patients treated with proton RT or combined photon/proton RT. Conclusion Our results suggest that photon RT may cause radiation-induced inflammation of the parotid gland, and that proton RT, which distributes less off-target radiation, is a safer treatment alternative.
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Affiliation(s)
- Alaa Mouminah
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.,The University of Pennsylvania School of Dental Medicine, Philadelphia, PA, USA
| | - Austin J Borja
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.,Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Emily C Hancin
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.,Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA
| | - Yu Cheng Chang
- The University of Pennsylvania School of Dental Medicine, Philadelphia, PA, USA
| | - Thomas J Werner
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jonathan Korostoff
- The University of Pennsylvania School of Dental Medicine, Philadelphia, PA, USA
| | - Abass Alavi
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Mona-Elisabeth Revheim
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA. .,Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway. .,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
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13
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Cysouw MCF, Jansen BHE, van de Brug T, Oprea-Lager DE, Pfaehler E, de Vries BM, van Moorselaar RJA, Hoekstra OS, Vis AN, Boellaard R. Machine learning-based analysis of [ 18F]DCFPyL PET radiomics for risk stratification in primary prostate cancer. Eur J Nucl Med Mol Imaging 2020; 48:340-349. [PMID: 32737518 PMCID: PMC7835295 DOI: 10.1007/s00259-020-04971-z] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 07/22/2020] [Indexed: 01/15/2023]
Abstract
PURPOSE Quantitative prostate-specific membrane antigen (PSMA) PET analysis may provide for non-invasive and objective risk stratification of primary prostate cancer (PCa) patients. We determined the ability of machine learning-based analysis of quantitative [18F]DCFPyL PET metrics to predict metastatic disease or high-risk pathological tumor features. METHODS In a prospective cohort study, 76 patients with intermediate- to high-risk PCa scheduled for robot-assisted radical prostatectomy with extended pelvic lymph node dissection underwent pre-operative [18F]DCFPyL PET-CT. Primary tumors were delineated using 50-70% peak isocontour thresholds on images with and without partial-volume correction (PVC). Four hundred and eighty standardized radiomic features were extracted per tumor. Random forest models were trained to predict lymph node involvement (LNI), presence of any metastasis, Gleason score ≥ 8, and presence of extracapsular extension (ECE). For comparison, models were also trained using standard PET features (SUVs, volume, total PSMA uptake). Model performance was validated using 50 times repeated 5-fold cross-validation yielding the mean receiver-operator characteristic curve AUC. RESULTS The radiomics-based machine learning models predicted LNI (AUC 0.86 ± 0.15, p < 0.01), nodal or distant metastasis (AUC 0.86 ± 0.14, p < 0.01), Gleason score (0.81 ± 0.16, p < 0.01), and ECE (0.76 ± 0.12, p < 0.01). The highest AUCs reached using standard PET metrics were lower than those of radiomics-based models. For LNI and metastasis prediction, PVC and a higher delineation threshold improved model stability. Machine learning pre-processing methods had a minor impact on model performance. CONCLUSION Machine learning-based analysis of quantitative [18F]DCFPyL PET metrics can predict LNI and high-risk pathological tumor features in primary PCa patients. These findings indicate that PSMA expression detected on PET is related to both primary tumor histopathology and metastatic tendency. Multicenter external validation is needed to determine the benefits of using radiomics versus standard PET metrics in clinical practice.
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Affiliation(s)
- Matthijs C F Cysouw
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, the Netherlands.
| | - Bernard H E Jansen
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, the Netherlands.,Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Urology, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, the Netherlands
| | - Tim van de Brug
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Biostatistics, De Boelelaan, 1117, Amsterdam, the Netherlands
| | - Daniela E Oprea-Lager
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, the Netherlands
| | - Elisabeth Pfaehler
- Department of Nuclear Medicine and Molecular Imaging, Medical Imaging Center, University of Groningen, Groningen, the Netherlands
| | - Bart M de Vries
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, the Netherlands
| | - Reindert J A van Moorselaar
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Urology, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, the Netherlands
| | - Otto S Hoekstra
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, the Netherlands
| | - André N Vis
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Urology, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, the Netherlands
| | - Ronald Boellaard
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, the Netherlands
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Barrington SF, Zwezerijnen BGJC, de Vet HCW, Heymans MW, Mikhaeel NG, Burggraaff CN, Eertink JJ, Pike LC, Hoekstra OS, Zijlstra JM, Boellaard R. Automated Segmentation of Baseline Metabolic Total Tumor Burden in Diffuse Large B-Cell Lymphoma: Which Method Is Most Successful? A Study on Behalf of the PETRA Consortium. J Nucl Med 2020; 62:332-337. [PMID: 32680929 DOI: 10.2967/jnumed.119.238923] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 06/17/2020] [Indexed: 12/22/2022] Open
Abstract
Metabolic tumor volume (MTV) is a promising biomarker of pretreatment risk in diffuse large B-cell lymphoma (DLBCL). Different segmentation methods can be used that predict prognosis equally well but give different optimal cutoffs for risk stratification. Segmentation can be cumbersome; a fast, easy, and robust method is needed. Our aims were to evaluate the best automated MTV workflow in DLBCL; determine whether uptake time, compliance or noncompliance with standardized recommendations for 18F-FDG scanning, and subsequent disease progression influence the success of segmentation; and assess differences in MTVs and discriminatory power of segmentation methods. Methods: One hundred forty baseline 18F-FDG PET/CT scans were selected from U.K. and Dutch studies on DLBCL to provide a balance between scans at 60 and 90 min of uptake, parameters compliant and noncompliant with standardized recommendations for scanning, and patients with and without progression. An automated tool was applied for segmentation using an SUV of 2.5 (SUV2.5), an SUV of 4.0 (SUV4.0), adaptive thresholding (A50P), 41% of SUVmax (41%), a majority vote including voxels detected by at least 2 methods (MV2), and a majority vote including voxels detected by at least 3 methods (MV3). Two independent observers rated the success of the tool to delineate MTV. Scans that required minimal interaction were rated as a success; scans that missed more than 50% of the tumor or required more than 2 editing steps were rated as a failure. Results: One hundred thirty-eight scans were evaluable, with significant differences in success and failure ratings among methods. The best performing was SUV4.0, with higher success and lower failure rates than any other method except MV2, which also performed well. SUV4.0 gave a good approximation of MTV in 105 (76%) scans, with simple editing for a satisfactory result in additionally 20% of cases. MTV was significantly different for all methods between patients with and without progression. The 41% segmentation method performed slightly worse, with longer uptake times; otherwise, scanning conditions and patient outcome did not influence the tool's performance. The discriminative power was similar among methods, but MTVs were significantly greater using SUV4.0 and MV2 than using other thresholds, except for SUV2.5. Conclusion: SUV4.0 and MV2 are recommended for further evaluation. Automated estimation of MTV is feasible.
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Affiliation(s)
- Sally F Barrington
- King's College London and Guy's and St. Thomas' PET Center, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Ben G J C Zwezerijnen
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Henrica C W de Vet
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Martijn W Heymans
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - N George Mikhaeel
- Department of Clinical Oncology, Guy's and St. Thomas' NHS Foundation Trust and School of Cancer and Pharmaceutical Sciences, King's College London, London, United Kingdom; and
| | - Coreline N Burggraaff
- Department of Hematology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jakoba J Eertink
- Department of Hematology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Lucy C Pike
- King's College London and Guy's and St. Thomas' PET Center, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Otto S Hoekstra
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Josée M Zijlstra
- Department of Hematology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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15
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Rezaei S, Ghafarian P, Jha AK, Rahmim A, Sarkar S, Ay MR. Joint compensation of motion and partial volume effects by iterative deconvolution incorporating wavelet-based denoising in oncologic PET/CT imaging. Phys Med 2019; 68:52-60. [PMID: 31743884 DOI: 10.1016/j.ejmp.2019.10.031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 09/29/2019] [Accepted: 10/17/2019] [Indexed: 10/25/2022] Open
Abstract
OBJECTIVES We aim to develop and rigorously evaluate an image-based deconvolution method to jointly compensate respiratory motion and partial volume effects (PVEs) for quantitative oncologic PET imaging, including studying the impact of various reconstruction algorithms on quantification performance. PROCEDURES An image-based deconvolution method that incorporated wavelet-based denoising within the Lucy-Richardson algorithm was implemented and assessed. The method was evaluated using phantom studies with signal-to-background ratios (SBR) of 4 and 8, and clinical data of 10 patients with 42 lung lesions ≤30 mm in diameter. In each study, PET images were reconstructed using four different algorithms: OSEM-basic, PSF, TOF, and TOFPSF. The performance was quantified using contrast recovery (CR), coefficient of variation (COV) and contrast-to-noise-ratio (CNR) metrics. Further, in each study, variabilities arising due to the four different reconstruction algorithms were assessed. RESULTS In phantom studies, incorporation of wavelet-based denoising improved COV in all cases. Processing images using proposed method yielded significantly higher CR and CNR particularly in small spheres, for all reconstruction algorithms and all SBRs (P < 0.05). In patient studies, processing images using the proposed method yielded significantly higher CR and CNR (P < 0.05). The choice of the reconstruction algorithm impacted quantification performance for changes in motion amplitude, tumor size and SBRs. CONCLUSIONS Our results provide strong evidence that the proposed joint-compensation method can yield improved PET quantification. The choice of the reconstruction algorithm led to changes in quantitative accuracy, emphasizing the need to carefully select the right combination of reconstruction-image-based compensation methods.
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Affiliation(s)
- Sahar Rezaei
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran; Research Center for Molecular and Cellular Imaging (RCMCI), Tehran University of Medical Sciences, Tehran, Iran
| | - Pardis Ghafarian
- Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran; PET/CT and Cyclotron Center, Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - Abhinav K Jha
- Department of Biomedical Engineering, Washington University in St. Louis, USA; Mallinckrodt Institute of Radiology, Washington University in St. Louis, USA
| | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Vancouver, Canada; Department of Integrative Oncology, BC Cancer Research Center, Vancouver, Canada
| | - Saeed Sarkar
- Research Center for Molecular and Cellular Imaging (RCMCI), Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Ay
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran; Research Center for Molecular and Cellular Imaging (RCMCI), Tehran University of Medical Sciences, Tehran, Iran
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Weber M, Binse I, Nagarajah J, Bockisch A, Herrmann K, Jentzen W. The role of 124I PET/CT lesion dosimetry in differentiated thyroid cancer. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF RADIOPHARMACEUTICAL CHEMISTRY AND BIOLOGY 2019; 63:235-252. [DOI: 10.23736/s1824-4785.19.03201-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
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Cysouw MCF, Golla SVS, Frings V, Smit EF, Hoekstra OS, Kramer GM, Boellaard R. Partial-volume correction in dynamic PET-CT: effect on tumor kinetic parameter estimation and validation of simplified metrics. EJNMMI Res 2019; 9:12. [PMID: 30715647 PMCID: PMC6362178 DOI: 10.1186/s13550-019-0483-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 01/25/2019] [Indexed: 12/27/2022] Open
Abstract
Background Partial-volume effects generally result in an underestimation of tumor tracer uptake on PET-CT for small lesions, necessitating partial-volume correction (PVC) for accurate quantification. However, investigation of PVC in dynamic oncological PET studies to date is scarce. The aim of this study was to investigate PVC’s impact on tumor kinetic parameter estimation from dynamic PET-CT acquisitions and subsequent validation of simplified semi-quantitative metrics. Ten patients with EGFR-mutated non-small cell lung cancer underwent dynamic 18F-fluorothymidine PET-CT before, 7 days after, and 28 days after commencing treatment with a tyrosine kinase inhibitor. Parametric PVC was applied using iterative deconvolution without and with highly constrained backprojection (HYPR) denoising, respectively. Using an image-derived input function with venous parent plasma calibration, we estimated full kinetic parameters VT, K1, and k3/k4 (BPND) using a reversible two-tissue compartment model, and simplified metrics (SUV and tumor-to-blood ratio) at 50–60 min post-injection. Results PVC had a non-linear effect on measured activity concentrations per timeframe. PVC significantly changed each kinetic parameter, with a median increase in VT of 11.8% (up to 25.1%) and 10.8% (up to 21.7%) without and with HYPR, respectively. Relative changes in kinetic parameter estimates vs. simplified metrics after applying PVC were poorly correlated (correlations 0.36–0.62; p < 0.01). PVC increased correlations between simplified metrics and VT from 0.82 and 0.81 (p < 0.01) to 0.90 and 0.88 (p < 0.01) for SUV and TBR, respectively, albeit non-significantly. PVC also increased correlations between treatment-induced changes in simplified metrics vs. VT at 7 (SUV) and 28 (SUV and TBR) days after treatment start non-significantly. Delineation on partial-volume corrected PET images resulted in a median decrease in metabolic tumor volume of 14.3% (IQR − 22.1 to − 7.5%), and increased the effect of PVC on kinetic parameter estimates. Conclusion PVC has a significant impact on tumor kinetic parameter estimation from dynamic PET-CT data, which differs from its effect on simplified metrics. However, it affected validation of these simplified metrics both as single measurements and as biomarkers of treatment response only to a small extent. Future dynamic PET studies should preferably incorporate PVC. Trial registration Dutch Trial Register, NTR3557. Electronic supplementary material The online version of this article (10.1186/s13550-019-0483-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- M C F Cysouw
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands.
| | - S V S Golla
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - V Frings
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - E F Smit
- Department of Thoracic Oncology, Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam, the Netherlands
| | - O S Hoekstra
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - G M Kramer
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - R Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
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Jiménez-Ortega E, Ureba A, Baeza JA, Barbeiro AR, Balcerzyk M, Parrado-Gallego Á, Wals-Zurita A, García-Gómez FJ, Leal A. Accurate, robust and harmonized implementation of morpho-functional imaging in treatment planning for personalized radiotherapy. PLoS One 2019; 14:e0210549. [PMID: 30625230 PMCID: PMC6326505 DOI: 10.1371/journal.pone.0210549] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Accepted: 12/27/2018] [Indexed: 12/25/2022] Open
Abstract
In this work we present a methodology able to use harmonized PET/CT imaging in dose painting by number (DPBN) approach by means of a robust and accurate treatment planning system. Image processing and treatment planning were performed by using a Matlab-based platform, called CARMEN, in which a full Monte Carlo simulation is included. Linear programming formulation was developed for a voxel-by-voxel robust optimization and a specific direct aperture optimization was designed for an efficient adaptive radiotherapy implementation. DPBN approach with our methodology was tested to reduce the uncertainties associated with both, the absolute value and the relative value of the information in the functional image. For the same H&N case, a single robust treatment was planned for dose prescription maps corresponding to standardized uptake value distributions from two different image reconstruction protocols: One to fulfill EARL accreditation for harmonization of [18F]FDG PET/CT image, and the other one to use the highest available spatial resolution. Also, a robust treatment was planned to fulfill dose prescription maps corresponding to both approaches, the dose painting by contour based on volumes and our voxel-by-voxel DPBN. Adaptive planning was also carried out to check the suitability of our proposal. Different plans showed robustness to cover a range of scenarios for implementation of harmonizing strategies by using the highest available resolution. Also, robustness associated to discretization level of dose prescription according to the use of contours or numbers was achieved. All plans showed excellent quality index histogram and quality factors below 2%. Efficient solution for adaptive radiotherapy based directly on changes in functional image was obtained. We proved that by using voxel-by-voxel DPBN approach it is possible to overcome typical drawbacks linked to PET/CT images, providing to the clinical specialist confidence enough for routinely implementation of functional imaging for personalized radiotherapy.
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Affiliation(s)
- Elisa Jiménez-Ortega
- Departamento de Fisiología Médica y Biofísica, Universidad de Sevilla, Seville, Spain
- Instituto de Biomedicina de Sevilla, IBIS, Seville, Spain
| | - Ana Ureba
- Departamento de Fisiología Médica y Biofísica, Universidad de Sevilla, Seville, Spain
| | - José Antonio Baeza
- Departamento de Fisiología Médica y Biofísica, Universidad de Sevilla, Seville, Spain
| | - Ana Rita Barbeiro
- Departamento de Fisiología Médica y Biofísica, Universidad de Sevilla, Seville, Spain
| | - Marcin Balcerzyk
- Centro Nacional de Aceleradores (CNA), Universidad de Sevilla, Junta de Andalucía, Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain
| | - Ángel Parrado-Gallego
- Centro Nacional de Aceleradores (CNA), Universidad de Sevilla, Junta de Andalucía, Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain
| | - Amadeo Wals-Zurita
- Hospital Universitario Virgen Macarena, Servicio de Radioterapia, Seville, Spain
| | | | - Antonio Leal
- Departamento de Fisiología Médica y Biofísica, Universidad de Sevilla, Seville, Spain
- Instituto de Biomedicina de Sevilla, IBIS, Seville, Spain
- * E-mail:
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Alavi A, Werner TJ, Høilund-Carlsen PF, Zaidi H. Correction for Partial Volume Effect Is a Must, Not a Luxury, to Fully Exploit the Potential of Quantitative PET Imaging in Clinical Oncology. Mol Imaging Biol 2018; 20:1-3. [PMID: 29181818 DOI: 10.1007/s11307-017-1146-y] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The partial volume effect (PVE) is considered as one of the major degrading factors impacting image quality and hampering the accuracy of quantitative PET imaging in clinical oncology. This effect is the consequence of the limited spatial resolution of whole-body PET scanners, which results in blurring of the generated images by the scanner's response function. A number of strategies have been devised to deal with partial volume effect. However, the lack of consensus on the clinical relevance of partial volume correction and the most appropriate technique to be used in the context of clinical oncology limited their application in clinical setting. This issue is debated in this commentary.
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Affiliation(s)
- Abass Alavi
- Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
| | - Thomas J Werner
- Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | | | - Habib Zaidi
- Department of Nuclear Medicine, University of Southern Denmark, DK-500, Odense, Denmark.,Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, 1211, Geneva, Switzerland.,Geneva Neuroscience Centre, University of Geneva, 1205, Geneva, Switzerland.,Department of Nuclear Medicine and Molecular Imaging, University of Groningen, Groningen, Netherlands
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20
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Pfaehler E, De Jong JR, Dierckx RAJO, van Velden FHP, Boellaard R. SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool. EJNMMI Phys 2018; 5:16. [PMID: 30225675 PMCID: PMC6141406 DOI: 10.1186/s40658-018-0215-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Accepted: 04/25/2018] [Indexed: 01/28/2023] Open
Abstract
Background Positron-emission tomography (PET) simulators are frequently used for development and performance evaluation of segmentation methods or quantitative uptake metrics. To date, most PET simulation tools are based on Monte Carlo simulations, which are computationally demanding. Other analytical simulation tools lack the implementation of time of flight (TOF) or resolution modelling (RM). In this study, a fast and easy-to-use PET simulation-reconstruction package, SiMulAtion and ReconsTruction (SMART)-PET, is developed and validated, which includes both TOF and RM. SMART-PET, its documentation and instructions to calibrate the tool to a specific PET/CT system are available on Zenodo. SMART-PET allows the fast generation of 3D PET images. As input, it requires one image representing the activity distribution and one representing the corresponding CT image/attenuation map. It allows the user to adjust different parameters, such as reconstruction settings (TOF/RM), noise level or scan duration. Furthermore, a random spatial shift can be included, representing patient repositioning. To evaluate the tool, simulated images were compared with real scan data of the NEMA NU 2 image quality phantom. The scan was acquired as a 60-min list-mode scan and reconstructed with and without TOF and/or RM. For every reconstruction setting, ten statistically equivalent images, representing 30, 60, 120 and 300 s scan duration, were generated. Simulated and real-scan data were compared regarding coefficient of variation in the phantom background and activity recovery coefficients (RCs) of the spheres. Furthermore, standard deviation images of each of the ten statistically equivalent images were compared. Results SMART-PET produces images comparable to actual phantom data. The image characteristics of simulated and real PET images varied in similar ways as function of reconstruction protocols and noise levels. The change in image noise with variation of simulated TOF settings followed the theoretically expected behaviour. RC as function of sphere size agreed within 0.3–11% between simulated and actual phantom data. Conclusions SMART-PET allows for rapid and easy simulation of PET data. The user can change various acquisition and reconstruction settings (including RM and TOF) and noise levels. The images obtained show similar image characteristics as those seen in actual phantom data. Electronic supplementary material The online version of this article (10.1186/s40658-018-0215-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Elisabeth Pfaehler
- Departments of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Johan R De Jong
- Departments of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Rudi A J O Dierckx
- Departments of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Floris H P van Velden
- Department of Radiology, Section of Nuclear Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Ronald Boellaard
- Departments of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. .,Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands.
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Jomaa H, Mabrouk R, Khlifa N. Post-reconstruction-based partial volume correction methods: A comprehensive review. Biomed Signal Process Control 2018. [DOI: 10.1016/j.bspc.2018.05.029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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22
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Belli ML, Mori M, Broggi S, Cattaneo GM, Bettinardi V, Dell'Oca I, Fallanca F, Passoni P, Vanoli EG, Calandrino R, Di Muzio N, Picchio M, Fiorino C. Quantifying the robustness of [ 18 F]FDG-PET/CT radiomic features with respect to tumor delineation in head and neck and pancreatic cancer patients. Phys Med 2018; 49:105-111. [PMID: 29866335 DOI: 10.1016/j.ejmp.2018.05.013] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 05/08/2018] [Accepted: 05/10/2018] [Indexed: 11/18/2022] Open
Abstract
PURPOSE To investigate the robustness of PET radiomic features (RF) against tumour delineation uncertainty in two clinically relevant situations. METHODS Twenty-five head-and-neck (HN) and 25 pancreatic cancer patients previously treated with 18F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT)-based planning optimization were considered. Seven FDG-based contours were delineated for tumour (T) and positive lymph nodes (N, for HN patients only) following manual (2 observers), semi-automatic (based on SUV maximum gradient: PET_Edge) and automatic (40%, 50%, 60%, 70% SUV_max thresholds) methods. Seventy-three RF (14 of first order and 59 of higher order) were extracted using the CGITA software (v.1.4). The impact of delineation on volume agreement and RF was assessed by DICE and Intra-class Correlation Coefficients (ICC). RESULTS A large disagreement between manual and SUV_max method was found for thresholds ≥50%. Inter-observer variability showed median DICE values between 0.81 (HN-T) and 0.73 (pancreas). Volumes defined by PET_Edge were better consistent with the manual ones compared to SUV40%. Regarding RF, 19%/19%/47% of the features showed ICC < 0.80 between observers for HN-N/HN-T/pancreas, mostly in the Voxel-alignment matrix and in the intensity-size zone matrix families. RFs with ICC < 0.80 against manual delineation (taking the worst value) increased to 44%/36%/61% for PET_Edge and to 69%/53%/75% for SUV40%. CONCLUSIONS About 80%/50% of 72 RF were consistent between observers for HN/pancreas patients. PET_edge was sufficiently robust against manual delineation while SUV40% showed a worse performance. This result suggests the possibility to replace manual with semi-automatic delineation of HN and pancreas tumours in studies including PET radiomic analyses.
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Affiliation(s)
| | - Martina Mori
- Medical Physics, San Raffaele Scientific Institute, Milano, Italy
| | - Sara Broggi
- Medical Physics, San Raffaele Scientific Institute, Milano, Italy
| | | | | | - Italo Dell'Oca
- Radiotherapy, San Raffaele Scientific Institute, Milano, Italy
| | | | - Paolo Passoni
- Radiotherapy, San Raffaele Scientific Institute, Milano, Italy
| | | | | | - Nadia Di Muzio
- Radiotherapy, San Raffaele Scientific Institute, Milano, Italy
| | - Maria Picchio
- Nuclear Medicine, San Raffaele Scientific Institute, Milano, Italy
| | - Claudio Fiorino
- Medical Physics, San Raffaele Scientific Institute, Milano, Italy.
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Satoh Y, Motosugi U, Saito A, Omiya Y, Onishi H. Pretreatment 18F-fluorodeoxyglucose Uptake in the Lung Parenchyma Predicts Poor Survival After Stereotactic Body Radiation Therapy in Patients With Stage I Non-Small Cell Lung Cancer. Technol Cancer Res Treat 2018; 17:1533033818794934. [PMID: 30222060 PMCID: PMC6141922 DOI: 10.1177/1533033818794934] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
PURPOSE In this study, we aimed to evaluate the prognostic value of fluorodeoxyglucose uptake in the lung parenchyma and the presence of subclinical interstitial lung disease on computed tomography as predictive factors for survival following stereotactic body radiation therapy in patients with stage I non-small cell lung cancer. METHODS We retrospectively evaluated 125 patients with stage I non-small cell lung cancer who underwent stereotactic body radiation therapy at our institute between December 2005 and March 2013 for various demographic and clinical parameters. The fluorodeoxyglucose uptake in the lung parenchyma corrected with computed tomography value (tissue fraction-corrected standardized uptake value) was quantified using fluorodeoxyglucose-positron emission tomography/computed tomography before the therapy. Additionally, the radiological findings of interstitial lung disease on computed tomography were evaluated. The prognostic analyses were performed using the Kaplan-Meier analysis and Cox proportional hazards regression model for univariate and multivariate analyses. RESULTS The median follow-up period was 39 months. The 3-year overall survival rate was 67.9%, and the 3-year progression-free survival rate was 52.0%. The multivariate analysis indicated that the tissue fraction-corrected standardized uptake value was correlated with the patients' overall survival ( P = .027, hazard ratio: 2.694, 95% confidence interval: 1.109-8.057). The presence of subclinical interstitial lung disease showed no correlation with the overall survival ( P = .535, hazard ratio: 1.256, 95% confidence interval: 0.592-2.473). CONCLUSION The results indicated that fluorodeoxyglucose uptake in the lung parenchyma, expressed as the tissue fraction-corrected standardized uptake value, was an independent prognostic factor in patients with stage I non-small cell lung cancer who have received stereotactic body radiation therapy.
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Affiliation(s)
- Yoko Satoh
- 1 Yamanashi PET Imaging Clinic, Kofu Neurosurgical Hospital, Chuo City, Yamanashi Prefecture, Japan.,2 Department of Radiology, University of Yamanashi, Chuo City, Yamanashi Prefecture, Japan
| | - Utaroh Motosugi
- 2 Department of Radiology, University of Yamanashi, Chuo City, Yamanashi Prefecture, Japan
| | - Akitoshi Saito
- 3 Department of Radiology, Yamanashi Prefectural Hospital, Kofu City, Yamanashi Prefecture, Japan
| | - Yoshie Omiya
- 2 Department of Radiology, University of Yamanashi, Chuo City, Yamanashi Prefecture, Japan
| | - Hiroshi Onishi
- 2 Department of Radiology, University of Yamanashi, Chuo City, Yamanashi Prefecture, Japan
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Cysouw MCF, Kramer GM, Schoonmade LJ, Boellaard R, de Vet HCW, Hoekstra OS. Impact of partial-volume correction in oncological PET studies: a systematic review and meta-analysis. Eur J Nucl Med Mol Imaging 2017; 44:2105-2116. [PMID: 28776088 PMCID: PMC5656693 DOI: 10.1007/s00259-017-3775-4] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Accepted: 07/02/2017] [Indexed: 11/03/2022]
Abstract
Purpose Positron-emission tomography can be useful in oncology for diagnosis, (re)staging, determining prognosis, and response assessment. However, partial-volume effects hamper accurate quantification of lesions <2–3× the PET system’s spatial resolution, and the clinical impact of this is not evident. This systematic review provides an up-to-date overview of studies investigating the impact of partial-volume correction (PVC) in oncological PET studies. Methods We searched in PubMed and Embase databases according to the PRISMA statement, including studies from inception till May 9, 2016. Two reviewers independently screened all abstracts and eligible full-text articles and performed quality assessment according to QUADAS-2 and QUIPS criteria. For a set of similar diagnostic studies, we statistically pooled the results using bivariate meta-regression. Results Thirty-one studies were eligible for inclusion. Overall, study quality was good. For diagnosis and nodal staging, PVC yielded a strong trend of increased sensitivity at expense of specificity. Meta-analysis of six studies investigating diagnosis of pulmonary nodules (679 lesions) showed no significant change in diagnostic accuracy after PVC (p = 0.222). Prognostication was not improved for non-small cell lung cancer and esophageal cancer, whereas it did improve for head and neck cancer. Response assessment was not improved by PVC for (locally advanced) breast cancer or rectal cancer, and it worsened in metastatic colorectal cancer. Conclusions The accumulated evidence to date does not support routine application of PVC in standard clinical PET practice. Consensus on the preferred PVC methodology in oncological PET should be reached. Partial-volume-corrected data should be used as adjuncts to, but not yet replacement for, uncorrected data. Electronic supplementary material The online version of this article (doi:10.1007/s00259-017-3775-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Matthijs C F Cysouw
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, P.O. Box 7057, 1007 MB, Amsterdam, Netherlands
| | - Gerbrand M Kramer
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, P.O. Box 7057, 1007 MB, Amsterdam, Netherlands
| | - Linda J Schoonmade
- Department of Medical Library, VU University Medical Centre, Amsterdam, Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, P.O. Box 7057, 1007 MB, Amsterdam, Netherlands.,Department of Nuclear Medicine & Molecular Imaging, University Medical Centre Groningen, Groningen, Netherlands
| | - Henrica C W de Vet
- Department of Epidemiology and Biostatistics, VU University Medical Centre, Amsterdam, Netherlands
| | - Otto S Hoekstra
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, P.O. Box 7057, 1007 MB, Amsterdam, Netherlands.
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Wallsten E, Axelsson J, Karlsson M, Riklund K, Larsson A. A Study of Dynamic PET Frame-Binning on the Reference Logan Binding Potential. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2017. [DOI: 10.1109/tns.2016.2639560] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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