Sotirchos VS, et al. Colorectal cancer liver metastases: biopsy of the ablation zone and margins can be used to predict oncologic outcome. Radiology. 2016;280(3):949–59.

Article  PubMed  Google Scholar 

Shady W, et al. Percutaneous microwave versus radiofrequency ablation of colorectal liver metastases: ablation with clear margins (A0) provides the best local tumor control. J Vasc Interv Radiol. 2018;29(2):268-275.e1.

Article  PubMed  Google Scholar 

Cornelis FH, et al. Immediate postablation (18)F-FDG injection and corresponding SUV are surrogate biomarkers of local tumor progression after thermal ablation of colorectal carcinoma liver metastases. J Nucl Med. 2018;59(9):1360–5.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kurilova I, et al. Factors associated with local tumor control and complications after thermal ablation of colorectal cancer liver metastases: a 15-year retrospective cohort study. Clin Colorectal Cancer. 2021;20(2):e82–95.

Article  PubMed  Google Scholar 

Vasiniotis Kamarinos N, et al. Biopsy and margins optimize outcomes after thermal ablation of colorectal liver metastases. Cancers (Basel). 2022;14(3).

Faber RA, et al. Three-dimensional quantitative margin assessment in patients with colorectal liver metastases treated with percutaneous thermal ablation using semi-automatic rigid MRI/CECT-CECT co-registration. Eur J Radiol. 2022;156: 110552.

Article  PubMed  Google Scholar 

Lin YM, et al. Ablative margins of colorectal liver metastases using deformable ct image registration and autosegmentation. Radiology. 2023;307(2): e221373.

Article  PubMed  Google Scholar 

Laimer G, et al. Volumetric assessment of the periablational safety margin after thermal ablation of colorectal liver metastases. Eur Radiol. 2021;31(9):6489–99.

Article  PubMed  PubMed Central  Google Scholar 

Benson AB et al. Colon cancer, Version 2.2021, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2021;19(3):329–59.

Cervantes A, et al. Metastatic colorectal cancer: ESMO clinical practice guideline for diagnosis, treatment and follow-up. Ann Oncol. 2023;34(1):10–32.

Article  CAS  PubMed  Google Scholar 

Ryan ER, et al. Split-dose technique for FDG PET/CT-guided percutaneous ablation: a method to facilitate lesion targeting and to provide immediate assessment of treatment effectiveness. Radiology. 2013;268(1):288–95.

Article  PubMed  PubMed Central  Google Scholar 

Zirakchian Zadeh M et al. Real-time split-dose PET/CT-guided ablation improves colorectal liver metastasis detection and ablation zone margin assessments without the need for repeated contrast injection. Cancers (Basel). 2022;14(24).

Laimer G, et al. Minimal ablative margin (MAM) assessment with image fusion: an independent predictor for local tumor progression in hepatocellular carcinoma after stereotactic radiofrequency ablation. Eur Radiol. 2020;30(5):2463–72.

Article  PubMed  PubMed Central  Google Scholar 

Kishore SA, Drabkin MJ, Sofocleous CT. Fluorodeoxyglucose-PET for ablation treatment planning, intraprocedural monitoring, and response. PET Clinics. 2019;14(4):427–36.

Article  PubMed  Google Scholar 

Casadaban LC, et al. Assessing ablation margins of FDG-avid liver tumors during PET/CT-guided thermal ablation procedures: a retrospective study. Eur J Nucl Med Mol Imaging. 2021;48(9):2914–24.

Article  PubMed  Google Scholar 

Shyn PB, et al. PET/CT-guided percutaneous liver mass biopsies and ablations: targeting accuracy of a single 20 s breath-hold PET acquisition. Clin Radiol. 2014;69(4):410–5.

Article  CAS  PubMed  Google Scholar 

Kaye EA, et al. Volumetric 3D assessment of ablation zones after thermal ablation of colorectal liver metastases to improve prediction of local tumor progression. Eur Radiol. 2019;29(5):2698–705.

Article  PubMed  Google Scholar 

VasiniotisKamarinos N, et al. 3D margin assessment predicts local tumor progression after ablation of colorectal cancer liver metastases. Int J Hyperthermia. 2022;39(1):880–7.

Article  CAS  Google Scholar 

Im HJ, et al. Current methods to define metabolic tumor volume in positron emission tomography: which one is better? Nucl Med Mol Imaging. 2018;52(1):5–15.

Article  PubMed  Google Scholar 

Cheebsumon P, et al. Effects of image characteristics on performance of tumor delineation methods: a test-retest assessment. J Nucl Med. 2011;52(10):1550–8.

Article  CAS  PubMed  Google Scholar 

Moon SH, Hyun SH, Choi JY. Prognostic significance of volume-based PET parameters in cancer patients. Korean J Radiol. 2013;14(1):1–12.

Article  PubMed  Google Scholar 

ZirakchianZadeh M, et al. Comparison of (18)F-sodium fluoride uptake in the whole bone, pelvis, and femoral neck of multiple myeloma patients before and after high-dose therapy and conventional-dose chemotherapy. Eur J Nucl Med Mol Imaging. 2020;47(12):2846–55.

Article  CAS  Google Scholar 

Zadeh MZ, et al. Evolving roles of fluorodeoxyglucose and sodium fluoride in assessment of multiple myeloma patients: Introducing a novel method of PET quantification to overcome shortcomings of the existing approaches. PET Clin. 2019;14(3):341–52.

Article  PubMed  Google Scholar 

ZirakchianZadeh M, et al. Prognostic significance of conventional and volumetric PET parameters with and without partial volume correction in the assessment of head and neck squamous cell carcinoma. Nucl Med Commun. 2022;43(7):800–6.

Article  CAS  Google Scholar 

ZirakchianZadeh M, et al. A review of different methods used for quantification and assessment of FDG-PET/CT in multiple myeloma. Nucl Med Commun. 2022;43(4):378–91.

Article  CAS  Google Scholar 

Ahmed M, et al. Image-guided tumor ablation: standardization of terminology and reporting criteria–a 10-year update. Radiology. 2014;273(1):241–60.

Article  PubMed  Google Scholar 

Ryan ER, et al. PET/CT-guided interventions: personnel radiation dose. Cardiovasc Intervent Radiol. 2013;36(4):1063–7.

Article  PubMed  Google Scholar 

Taghvaei R, et al. Pre-treatment partial-volume-corrected TLG is the best predictor of overall survival in patients with relapsing/refractory non-hodgkin lymphoma following radioimmunotherapy. Am J Nucl Med Mol Imaging. 2018;8(6):407–14.

CAS  PubMed  PubMed Central  Google Scholar 

Zadeh MZ, et al. Prognostic significance of (18)F-sodium fluoride in newly diagnosed multiple myeloma patients. Am J Nucl Med Mol Imaging. 2020;10(4):151–60.

CAS  PubMed  PubMed Central  Google Scholar 

Seraj SM, et al. The evolving role of PET-based novel quantitative techniques in the interventional radiology procedures of the liver. PET Clin. 2019;14(4):419–25.

Article  PubMed  Google Scholar 

Carter JV, et al. ROC-ing along: evaluation and interpretation of receiver operating characteristic curves. Surgery. 2016;159(6):1638–45.

Article  PubMed  Google Scholar 

Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15(2):155–63.

Article  PubMed  PubMed Central  Google Scholar 

Gönen M, Panageas KS, Larson SM. Statistical issues in analysis of diagnostic imaging experiments with multiple observations per patient. Radiology. 2001;221(3):763–7.

Article  PubMed  Google Scholar 

Suzuki O, et al. Defining PET standardized uptake value threshold for tumor delineation with metastatic lymph nodes in head and neck cancer. Jpn J Clin Oncol. 2012;42(6):491–7.

Article  PubMed  Google Scholar 

Wilson JM, Partridge M, Hawkins M. The application of functional imaging techniques to personalise chemoradiotherapy in upper gastrointestinal malignancies. Clin Oncol (R Coll Radiol). 2014;26(9):581–96.

Article  CAS  PubMed  Google Scholar 

Erdi YE, et al. Segmentation of lung lesion volume by adaptive positron emission tomography image thresholding. Cancer. 1997;80(12 Suppl):2505–9.

Article  CAS  PubMed  Google Scholar 

Lin Y, et al. Prognostic value of preoperative metabolic tumor volumes on PET-CT in predicting disease-free survival of patients with stage I non-small cell lung cancer. Anticancer Res. 2012;32(11):5087–91.

PubMed  Google Scholar 

Graves EE, Quon A, Loo BW Jr. RT_Image: an open-source tool for investigating PET in radiation oncology. Technol Cancer Res Treat. 2007;6(2):111–21.

Article  PubMed  Google Scholar 

Werner-Wasik M, et al. What is the best way to contour lung tumors on PET scans? Multiobserver validation of a gradient-based method using a NSCLC digital PET phantom. Int J Radiat Oncol Biol Phys. 2012;82(3):1164–71.

Article  PubMed  Google Scholar 

Geets X, et al. A gradient-based method for segmenting FDG-PET images: methodology and validation. Eur J Nucl Med Mol Imaging. 2007;34(9):1427–38.

Article  PubMed  Google Scholar 

Sridhar P, et al. FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors. AJR Am J Roentgenol. 2014;202(5):1114–9.

Article  PubMed  Google Scholar 

Nelson A, et al. PET tumor segmentation: Validation of a gradient-based method using a NSCLC PET phantom. J Nucl Med. 2009;50(supplement 2):1659–1659.

Google Scholar 

Takeda K, et al. Clinical utility of texture analysis of 18F-FDG PET/CT in patients with Stage I lung cancer treated with stereotactic body radiotherapy. J Radiat Res. 2017;58(6):862–9.

Article  CAS