The Promise of Novel Biomarkers for Head and Neck Cancer from an Imaging Perspective

Marcu, Loredana G.; Reid, Paul; Bezak, Eva

doi:10.3390/ijms19092511

Cited by 23 publications

(15 citation statements)

References 70 publications

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“…Next to radiomic signatures, there is a myriad of other prognostic biomarkers for HNSCC available that, for instance, are based on imaging [41], immunohistochemistry [42], and microarray data [4]. The advantages of our radiomic profile is that it is available before treatment and based on standard diagnostic images, thereby avoiding additional costs and discomfort for the patient.…”

Section: Discussionmentioning

confidence: 99%

Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures

et al. 2020

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Objectives Head and neck squamous cell carcinoma (HNSCC) shows a remarkable heterogeneity between tumors, which may be captured by a variety of quantitative features extracted from diagnostic images, termed radiomics. The aim of this study was to develop and validate MRI-based radiomic prognostic models in oral and oropharyngeal cancer. Materials and Methods Native T1-weighted images of four independent, retrospective (2005–2013), patient cohorts (n = 102, n = 76, n = 89, and n = 56) were used to delineate primary tumors, and to extract 545 quantitative features from. Subsequently, redundancy filtering and factor analysis were performed to handle collinearity in the data. Next, radiomic prognostic models were trained and validated to predict overall survival (OS) and relapse-free survival (RFS). Radiomic features were compared to and combined with prognostic models based on standard clinical parameters. Performance was assessed by integrated area under the curve (iAUC). Results In oral cancer, the radiomic model showed an iAUC of 0.69 (OS) and 0.70 (RFS) in the validation cohort, whereas the iAUC in the oropharyngeal cancer validation cohort was 0.71 (OS) and 0.74 (RFS). By integration of radiomic and clinical variables, the most accurate models were defined (iAUC oral cavity, 0.72 (OS) and 0.74 (RFS); iAUC oropharynx, 0.81 (OS) and 0.78 (RFS)), and these combined models outperformed prognostic models based on standard clinical variables only (p < 0.001). Conclusions MRI radiomics is feasible in HNSCC despite the known variability in MRI vendors and acquisition protocols, and radiomic features added information to prognostic models based on clinical parameters. Key Points • MRI radiomics can predict overall survival and relapse-free survival in oral and HPV-negative oropharyngeal cancer. • MRI radiomics provides additional prognostic information to known clinical variables, with the best performance of the combined models. • Variation in MRI vendors and acquisition protocols did not influence performance of radiomic prognostic models.

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Section: Discussionmentioning

confidence: 99%

Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures

et al. 2020

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“…The clinical management of tumour heterogeneity is a significant challenge as tumour response is dictated by the particular behaviour of each sub-group of cancer cells. Cellular heterogeneity given by proliferation kinetics, stemness, hypoxia or other factors calls for specific markers and targeting; therefore, the near future of biomarkers will rely on complementarity rather than a common solution valid for all (radio)biological particularities of a tumour [ 78 ].…”

Section: Discussionmentioning

confidence: 99%

Imaging Biomarkers of Tumour Proliferation and Invasion for Personalised Lung Cancer Therapy

Marcu

2020

JPM

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Personalised treatment in oncology has seen great developments over the last decade, due to both technological advances and more in-depth knowledge of radiobiological processes occurring in tumours. Lung cancer therapy is no exception, as new molecular targets have been identified to further increase treatment specificity and sensitivity. Yet, tumour resistance to treatment is still one of the main reasons for treatment failure. This is due to a number of factors, among which tumour proliferation, the presence of cancer stem cells and the metastatic potential of the primary tumour are key features that require better controlling to further improve cancer management in general, and lung cancer treatment in particular. Imaging biomarkers play a key role in the identification of biological particularities within tumours and therefore are an important component of treatment personalisation in radiotherapy. Imaging techniques such as PET, SPECT, MRI that employ tumour-specific biomarkers already play a critical role in patient stratification towards individualized treatment. The aim of the current paper is to describe the radiobiological challenges of lung cancer treatment in relation to the latest imaging biomarkers that can aid in the identification of hostile cellular features for further treatment adaptation and tailoring to the individual patient’s needs.

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“…Therefore, the possibility of the coexistence of false-positive findings owing to thyroid lesions must be considered and further evaluation is required when another focal lesion is seen on a Tc-99m MIBI SPECT scan [21,22]. Furthermore, similar to this MIBI SPECT/CT, a recent study reported the importance of hybrid imaging using tumor-specific biomarkers in head and neck tumors, and this is thought to help the patients’ treatment guidance [23].…”

Section: Discussionmentioning

confidence: 99%

Detecting Synchronous Parathyroid Adenoma and False-Positive Findings on Technetium-99m MIBI Single Photon-Emission Computed Tomography/Computed Tomography

et al. 2019

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Technetium (Tc)-99m-methoxyisobutylisonitrile (MIBI) single photon-emission computed tomography/computed tomography (SPECT/CT) is now being used increasingly for preoperative localization of parathyroid adenomas. Tc-99m-MIBI scintigraphy in a 52-year-old man with a diagnosis of primary hyperparathyroidism revealed two focal areas with retention of radioactivity in the left lobe of the thyroid gland on the delayed phase of MIBI SPECT/CT but no significant focal radioactive uptake on MIBI planar images. The patient subsequently underwent left partial parathyroidectomy. Histological analysis identified one lesion to be thyroid hyperplasia and the other to be parathyroid adenoma. This case demonstrates the value of MIBI SPECT/CT for localization of a parathyroid lesion when compared with planar images and that false-positive findings can lead to misdiagnosis in a patient with coexisting thyroid disease. An appropriate diagnostic work-up that includes Tc-99m MIBI SPECT/CT in addition to ultrasonography is helpful for an accurate diagnosis in patients with concomitant thyroid disease.

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The Promise of Novel Biomarkers for Head and Neck Cancer from an Imaging Perspective

Cited by 23 publications

References 70 publications

Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures

Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures

Imaging Biomarkers of Tumour Proliferation and Invasion for Personalised Lung Cancer Therapy

Detecting Synchronous Parathyroid Adenoma and False-Positive Findings on Technetium-99m MIBI Single Photon-Emission Computed Tomography/Computed Tomography

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