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Lin R, Lv H, Yu J, Song C, Tian A. 18F-fluorodeoxyglucose positron emission tomography-computed tomography in the localization of the lesions in the osteogenic region of breast cancer bone metastases after therapy. Quant Imaging Med Surg 2024; 14:4950-4964. [PMID: 39022246 PMCID: PMC11250318 DOI: 10.21037/qims-23-1738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 05/30/2024] [Indexed: 07/20/2024]
Abstract
Background Accurate efficacy evaluation of bone metastases (BMs) from breast cancer (BC) is an intractable issue in clinical practice, for which solutions are urgently needed. This study aimed to investigate the utility of 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) in the response evaluation of bone metastasis of BC. Methods In total, 22 patients diagnosed with BC and BM were enrolled. These patients underwent repeated 18F-FDG PET/CT evaluations. The patients and each BM site were divided into two groups based on their response to treatment: progressive disease (PD) and nonprogressive disease (non-PD). We analyzed and compared the changes in PET and CT images, as well as the serum concentration of carcinoembryonic antigen (CEA), carbohydrate antigen 153 (CA153), alkaline phosphatase (ALP), and calcium (Ca) over the same time frame. The immunohistochemistry (IHC) of primary lesions between groups and between the primary focus and BM with high 18F-FDG uptake were compared and analyzed. Results Maximum standard uptake value (SUVmax) after therapy [area under the curve (AUC): 0.932] and Δ-value of SUVmax (AUC: 0.811) on 18F-FDG PET imaging proved significantly valuable for the efficacy of therapy outcomes related to BM lesions (P<0.05). In terms of overall evaluation of BM, age and human epidermal growth factor receptor 2 (HER2) expression were significantly lower in the PD group than in the non-PD group (P<0.05). There were marked differences in CEA after therapy, the changes of CEA, and CA153 (∆-value) between the groups (P<0.05). The SUVmax and Ca concentration after therapy and ∆-value of SUVmax, along with the levels of CA153, CEA, and ALP, were valuable indicators for evaluating the efficacy of individual BMs (P<0.05). IHC of BM in the PD group showed differences compared to primary lesions, with antigen Ki-67 being downregulated in metastatic lesions and HER2 being downregulated in a portion of BMs (2 of 6). Meanwhile, the expression of estrogen receptor (ER) and progesterone receptor (PR) remained relatively unchanged. Conclusions 18F-FDG PET/CT confers precise assessment of the posttreatment efficacy pertaining to BM in BC. This modality facilitates the identification of poor effect lesions following extant therapies and localization for pathological assessment and may substantially contribute to evaluating therapeutic efficacy, refining treatment strategies, and predicting the disease trajectory of patients with BC and BM.
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Affiliation(s)
- Runlong Lin
- Department of Nuclear Medicine, The Second Hospital of Dalian Medical University, Dalian, China
| | - Huiyun Lv
- Department of Oncology, The Second Hospital of Dalian Medical University, Dalian, China
| | - Jing Yu
- Department of Nuclear Medicine, The Second Hospital of Dalian Medical University, Dalian, China
| | - Chen Song
- Department of Oncology, The Second Hospital of Dalian Medical University, Dalian, China
| | - Aijuan Tian
- Department of Nuclear Medicine, The Second Hospital of Dalian Medical University, Dalian, China
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Caracciolo M, Castello A, Urso L, Borgia F, Marzola MC, Uccelli L, Cittanti C, Bartolomei M, Castellani M, Lopci E. Comparison of MRI vs. [ 18F]FDG PET/CT for Treatment Response Evaluation of Primary Breast Cancer after Neoadjuvant Chemotherapy: Literature Review and Future Perspectives. J Clin Med 2023; 12:5355. [PMID: 37629397 PMCID: PMC10455346 DOI: 10.3390/jcm12165355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 08/11/2023] [Accepted: 08/12/2023] [Indexed: 08/27/2023] Open
Abstract
The purpose of this systematic review was to investigate the diagnostic accuracy of [18F]FDG PET/CT and breast MRI for primary breast cancer (BC) response assessment after neoadjuvant chemotherapy (NAC) and to evaluate future perspectives in this setting. We performed a critical review using three bibliographic databases (i.e., PubMed, Scopus, and Web of Science) for articles published up to the 6 June 2023, starting from 2012. The Quality Assessment of Diagnosis Accuracy Study (QUADAS-2) tool was adopted to evaluate the risk of bias. A total of 76 studies were identified and screened, while 14 articles were included in our systematic review after a full-text assessment. The total number of patients included was 842. Eight out of fourteen studies (57.1%) were prospective, while all except one study were conducted in a single center. In the majority of the included studies (71.4%), 3.0 Tesla (T) MRI scans were adopted. Three out of fourteen studies (21.4%) used both 1.5 and 3.0 T MRI and only two used 1.5 T. [18F]FDG was the radiotracer used in every study included. All patients accepted surgical treatment after NAC and each study used pathological complete response (pCR) as the reference standard. Some of the studies have demonstrated the superiority of [18F]FDG PET/CT, while others proved that MRI was superior to PET/CT. Recent studies indicate that PET/CT has a better specificity, while MRI has a superior sensitivity for assessing pCR in BC patients after NAC. The complementary value of the combined use of these modalities represents probably the most important tool to improve diagnostic performance in this setting. Overall, larger prospective studies, possibly randomized, are needed, hopefully evaluating PET/MR and allowing for new tools, such as radiomic parameters, to find a proper place in the setting of BC patients undergoing NAC.
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Affiliation(s)
- Matteo Caracciolo
- Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
| | - Angelo Castello
- Nuclear Medicine Unit, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Luca Urso
- Department of Nuclear Medicine PET/CT Centre, S. Maria della Misericordia Hospital, 45100 Rovigo, Italy
| | - Francesca Borgia
- Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Maria Cristina Marzola
- Department of Nuclear Medicine PET/CT Centre, S. Maria della Misericordia Hospital, 45100 Rovigo, Italy
| | - Licia Uccelli
- Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Corrado Cittanti
- Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Mirco Bartolomei
- Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
| | - Massimo Castellani
- Nuclear Medicine Unit, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Egesta Lopci
- Nuclear Medicine Unit, IRCCS—Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Italy
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Quartuccio N, Alongi P, Urso L, Ortolan N, Borgia F, Bartolomei M, Arnone G, Evangelista L. 18F-FDG PET-Derived Volume-Based Parameters to Predict Disease-Free Survival in Patients with Grade III Breast Cancer of Different Molecular Subtypes Candidates to Neoadjuvant Chemotherapy. Cancers (Basel) 2023; 15:2715. [PMID: 37345052 DOI: 10.3390/cancers15102715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 05/02/2023] [Accepted: 05/09/2023] [Indexed: 06/23/2023] Open
Abstract
We investigated whether baseline [18F] Fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)-derived semiquantitative parameters could predict disease-free survival (DFS) in patients with grade III breast cancer (BC) of different molecular subtypes candidate to neoadjuvant chemotherapy (NAC). For each 18F-FDG-PET/CT scan, the following parameters were calculated in the primary tumor (SUVmax, SUVmean, MTV, TLG) and whole-body (WB_SUVmax, WB_MTV, and WB_TLG). Receiver operating characteristic (ROC) analysis was used to determine the capability to predict DFS and find the optimal threshold for each parameter. Ninety-five grade III breast cancer patients with different molecular types were retrieved from the databases of the University Hospital of Padua and the University Hospital of Ferrara (luminal A: 5; luminal B: 34; luminal B-HER2: 22; HER2-enriched: 7; triple-negative: 27). In luminal B patients, WB_MTV (AUC: 0.75; best cut-off: WB_MTV > 195.33; SS: 55.56%, SP: 100%; p = 0.002) and WB_TLG (AUC: 0.73; best cut-off: WB_TLG > 1066.21; SS: 55.56%, SP: 100%; p = 0.05) were the best predictors of DFS. In luminal B-HER2 patients, WB_SUVmax was the only predictor of DFS (AUC: 0.857; best cut-off: WB_SUVmax > 13.12; SS: 100%; SP: 71.43%; p < 0.001). No parameter significantly affected the prediction of DFS in patients with grade III triple-negative BC. Volume-based parameters, extracted from baseline 18F-FDG PET, seem promising in predicting recurrence in patients with grade III luminal B and luminal B- HER2 breast cancer undergoing NAC.
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Affiliation(s)
- Natale Quartuccio
- Nuclear Medicine Unit, Ospedali Riuniti Villa Sofia-Cervello, 90144 Palermo, Italy
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico, Di Cristina e Benfratelli, 90127 Palermo, Italy
| | - Pierpaolo Alongi
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico, Di Cristina e Benfratelli, 90127 Palermo, Italy
| | - Luca Urso
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Naima Ortolan
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Francesca Borgia
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Mirco Bartolomei
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Gaspare Arnone
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico, Di Cristina e Benfratelli, 90127 Palermo, Italy
| | - Laura Evangelista
- Department of Medicine DIMED, University of Padua, 35128 Padua, Italy
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Classifying Breast Cancer Metastasis Based on Imaging of Tumor Primary and Tumor Biology. Diagnostics (Basel) 2023; 13:diagnostics13030437. [PMID: 36766541 PMCID: PMC9914718 DOI: 10.3390/diagnostics13030437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 01/14/2023] [Accepted: 01/21/2023] [Indexed: 01/27/2023] Open
Abstract
The molecular classification of breast cancer has allowed for a better understanding of both prognosis and treatment of breast cancer. Imaging of the different molecular subtypes has revealed that biologically different tumors often exhibit typical features in mammography, ultrasound, and MRI. Here, we introduce the molecular classification of breast cancer and review the typical imaging features of each subtype, examining the predictive value of imaging with respect to distant metastases.
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Suto H, Inui Y, Okamura A. Is CT or FDG-PET more useful for evaluation of the treatment response in metastatic HER2-positive breast cancer? a case report and literature review. Front Oncol 2023; 13:1158797. [PMID: 37152012 PMCID: PMC10157226 DOI: 10.3389/fonc.2023.1158797] [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] [Received: 02/04/2023] [Accepted: 04/05/2023] [Indexed: 05/09/2023] Open
Abstract
Response evaluation criteria in solid tumors version 1.1 (RECIST ver1.1) has been widely adopted to evaluate treatment efficacy in solid tumors, including breast cancer (BC), in clinical trials and clinical practice. RECIST is based mainly on computed tomography (CT) images, and the role of fluorodeoxyglucose-positron emission tomography (FDG-PET) is limited. However, because the rate of tumor shrinkage on CT does not necessarily reflect the potential remaining tumor cells, there may be a discrepancy between the treatment response and prognosis in some cases. Here we report a case of metastatic human epidermal growth factor receptor 2 (HER2)-positive BC where FDG-PET was preferable to CT for evaluation of the treatment response. A 40-year-old woman became aware of a lump in her right breast in September 201X. She was pregnant and underwent further examinations, including a biopsy, in November. The diagnosis was HER2-positive BC (cT2N2bM1, stage IV). Trastuzumab plus pertuzumab plus docetaxel (TPD) therapy was initiated in December 201X. CT performed in February 201X+1 showed cystic changes in the metastatic lesions in the liver, and the treatment response was stable disease (SD) according to RECIST. However, FDG-PET in March 201X+1 did not detect abnormal uptake of FDG in the hepatic lesions. The disease remained stable thereafter. Thus, tumor shrinkage may not be apparent in situations where the response to treatment results in rapid changes in blood flow within the tumor, which is associated with cystic changes. When patients with hypervascular liver metastases receive treatment with highly effective regimens, the target lesion may show cystic changes rather than shrinkage, as observed in the present case. Therefore, FDG-PET is sometimes superior to CT in judging a tumor response.
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Affiliation(s)
- Hirotaka Suto
- Department of Medical Oncology, The Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan
- Department of Medical Oncology/Hematology, Kakogawa Central City Hospital, Hyogo, Japan
- *Correspondence: Hirotaka Suto,
| | - Yumiko Inui
- Department of Medical Oncology/Hematology, Kakogawa Central City Hospital, Hyogo, Japan
| | - Atsuo Okamura
- Department of Medical Oncology/Hematology, Kakogawa Central City Hospital, Hyogo, Japan
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Urso L, Evangelista L, Alongi P, Quartuccio N, Cittanti C, Rambaldi I, Ortolan N, Borgia F, Nieri A, Uccelli L, Schirone A, Panareo S, Arnone G, Bartolomei M. The Value of Semiquantitative Parameters Derived from 18F-FDG PET/CT for Predicting Response to Neoadjuvant Chemotherapy in a Cohort of Patients with Different Molecular Subtypes of Breast Cancer. Cancers (Basel) 2022; 14:cancers14235869. [PMID: 36497351 PMCID: PMC9738922 DOI: 10.3390/cancers14235869] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 11/25/2022] [Accepted: 11/27/2022] [Indexed: 12/03/2022] Open
Abstract
Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) is a strong prognostic factor in breast cancer (BC). The aim of this study was to investigate whether semiquantitative parameters derived from baseline [18F]Fluorodeoxyglucose ([18F]FDG) positron emission computed tomography/computed tomography (PET/CT) could predict pCR after NAC and survival outcomes in patients affected by different molecular subtypes of BC. We retrospectively retrieved patients from the databases of two Italian hospitals (Centre A: University Hospital of Ferrara; Centre B: University of Padua) meeting the following inclusion criteria: (1) diagnosis of BC; (2) history of NAC; (3) baseline [18F]FDG PET/CT performed before the first cycle of NAC; (4) available follow-up data (response after NAC and survival information). For each [18F]FDG PET/CT scan, semiquantitative parameters (SUVmax, SUVmean, MTV and TLG) related to the primary tumor (B), to the reference lesion for both axillary (N) and distant lymph node (DN), and to the whole-body burden of disease (WB) were evaluated. Patients enrolled were 133: 34 from centre A and 99 from centre B. Patients' molecular subtypes were: 9 luminal A, 49 luminal B, 33 luminal B + HER-2, 10 HER-2 enriched, and 32 triple negative (TNBC). Luminal A and HER-2 enriched BC patients were excluded from the analysis due to the small sample size. pCR after NAC was achieved in 47 patients (41.2%). [18F]FDG PET/CT detected the primary tumor in 98.3% of patients and lymph node metastases were more frequently detected in Luminal B subgroup. Among Luminal B patients, median SUVmean_B values were significantly higher (p = 0.027) in responders (7.06 ± 5.9) vs. non-responders (4.4 ± 2.1) to NAC. Luminal B + HER-2 non-responders showed a statistically significantly higher median MTV_B (7.3 ± 4.2 cm3 vs. 3.5 ± 2.5 cm3; p = 0.003) and TLG_B (36.5 ± 24.9 vs. 18.9 ± 17.7; p = 0.025) than responders at baseline [18F]FDG PET/CT. None of the semiquantitative parameters predicted pCR after NAC in TNBC patients. However, among TNBC patients who achieved pCR after NAC, 4 volumetric parameters (MTV_B, TLG_B, MTV_WB and TLG_WB) were significantly higher in patients dead at follow-up. If confirmed in further studies, these results could open up a widespread use of [18F]FDG PET/CT as a baseline predictor of response to NAC in luminal B and luminal B + HER-2 patients and as a prognostic tool in TNBC.
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Affiliation(s)
- Luca Urso
- Department of Translational Medicine, University of Ferrara, Via Aldo Moro 8, 44124 Ferrara, Italy
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Laura Evangelista
- Department of Medicine DIMED, University of Padua, 35128 Padua, Italy
| | - Pierpaolo Alongi
- Nuclear Medicine Unit, ARNAS Ospedali Civico, Di Cristina e Benfratelli, 90127 Palermo, Italy
| | - Natale Quartuccio
- Nuclear Medicine Unit, Ospedali Riuniti Villa Sofia-Cervello, 90146 Palermo, Italy
| | - Corrado Cittanti
- Department of Translational Medicine, University of Ferrara, Via Aldo Moro 8, 44124 Ferrara, Italy
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
- Correspondence: ; Tel.: +39-0532326387
| | - Ilaria Rambaldi
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Naima Ortolan
- Department of Translational Medicine, University of Ferrara, Via Aldo Moro 8, 44124 Ferrara, Italy
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Francesca Borgia
- Department of Translational Medicine, University of Ferrara, Via Aldo Moro 8, 44124 Ferrara, Italy
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Alberto Nieri
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Licia Uccelli
- Department of Translational Medicine, University of Ferrara, Via Aldo Moro 8, 44124 Ferrara, Italy
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Alessio Schirone
- Oncology Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
| | - Stefano Panareo
- Nuclear Medicine Unit, Oncology and Haematology Department, University Hospital of Modena, 41125 Modena, Italy
| | - Gaspare Arnone
- Nuclear Medicine Unit, ARNAS Ospedali Civico, Di Cristina e Benfratelli, 90127 Palermo, Italy
| | - Mirco Bartolomei
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
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Urso L, Manco L, Castello A, Evangelista L, Guidi G, Castellani M, Florimonte L, Cittanti C, Turra A, Panareo S. PET-Derived Radiomics and Artificial Intelligence in Breast Cancer: A Systematic Review. Int J Mol Sci 2022; 23:13409. [PMID: 36362190 PMCID: PMC9653918 DOI: 10.3390/ijms232113409] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 10/27/2022] [Accepted: 10/28/2022] [Indexed: 08/13/2023] Open
Abstract
Breast cancer (BC) is a heterogeneous malignancy that still represents the second cause of cancer-related death among women worldwide. Due to the heterogeneity of BC, the correct identification of valuable biomarkers able to predict tumor biology and the best treatment approaches are still far from clear. Although molecular imaging with positron emission tomography/computed tomography (PET/CT) has improved the characterization of BC, these methods are not free from drawbacks. In recent years, radiomics and artificial intelligence (AI) have been playing an important role in the detection of several features normally unseen by the human eye in medical images. The present review provides a summary of the current status of radiomics and AI in different clinical settings of BC. A systematic search of PubMed, Web of Science and Scopus was conducted, including all articles published in English that explored radiomics and AI analyses of PET/CT images in BC. Several studies have demonstrated the potential role of such new features for the staging and prognosis as well as the assessment of biological characteristics. Radiomics and AI features appear to be promising in different clinical settings of BC, although larger prospective trials are needed to confirm and to standardize this evidence.
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Affiliation(s)
- Luca Urso
- Department of Translational Medicine, University of Ferrara, Via Aldo Moro 8, 44124 Ferrara, Italy
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Luigi Manco
- Medical Physics Unit, Azienda USL of Ferrara, 44124 Ferrara, Italy
- Medical Physics Unit, University Hospital of Ferrara, 44124 Cona, Italy
| | - Angelo Castello
- Nuclear Medicine Unit, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Laura Evangelista
- Department of Medicine DIMED, University of Padua, 35128 Padua, Italy
| | - Gabriele Guidi
- Medical Physics Unit, University Hospital of Modena, 41125 Modena, Italy
| | - Massimo Castellani
- Nuclear Medicine Unit, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Luigia Florimonte
- Nuclear Medicine Unit, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Corrado Cittanti
- Department of Translational Medicine, University of Ferrara, Via Aldo Moro 8, 44124 Ferrara, Italy
- Nuclear Medicine Unit, Oncological Medical and Specialist Department, University Hospital of Ferrara, 44124 Cona, Italy
| | - Alessandro Turra
- Medical Physics Unit, University Hospital of Ferrara, 44124 Cona, Italy
| | - Stefano Panareo
- Nuclear Medicine Unit, Oncology and Haematology Department, University Hospital of Modena, 41125 Modena, Italy
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