Evidence map›Paper›PMID 34123824›Full record

ArticleFrontiers in oncology2021

Targeting Treatment Resistance in Head and Neck Squamous Cell Carcinoma - Proof of Concept for CT Radiomics-Based Identification of Resistant Sub-Volumes.

Marta Bogowicz, Matea Pavic, Oliver Riesterer, Tobias Finazzi, Helena Garcia Schüler, Edna Holz-Sapra, Leonie Rudofsky, Lucas Basler, Manon Spaniol, Andreas Ambrusch and 3 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Article
  3. Current Role of Delta Radiomics in Head and Neck Oncology.International journal of molecular sciences · 2023
    Review
  4. Article
  5. Review
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 1 country.

Marta BogowiczDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Matea PavicDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Oliver RiestererDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Tobias FinazziDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Helena Garcia SchülerDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Edna Holz-SapraDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Leonie RudofskyDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Lucas BaslerDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Manon SpaniolDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Andreas AmbruschDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Martin HüllnerDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Matthias GuckenbergerDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Stephanie Tanadini-LangDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
University Hospital of Zurich · CHUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeRadiomics has already been proposed as a prognostic biomarker in head and neck cancer (HNSCC). However, its predictive power in radiotherapy has not yet been studied. Here, we investigated a local radiomics approach to distinguish between tumor sub-volumes with different levels of radiosensitivity as a possible target for radiation dose intensification. MATERIALS AND

methodsOf 40 patients (n=28 training and n=12 validation) with biopsy confirmed locally recurrent HNSCC, pretreatment contrast-enhanced CT images were registered with follow-up PET/CT imaging allowing identification of controlled (GTVcontrol) vs non-controlled (GTVrec) tumor sub-volumes on pretreatment imaging. A bi-regional model was built using radiomic features extracted from pretreatment CT in the GTVrec and GTVcontrol to differentiate between those regions. Additionally, concept of local radiomics was implemented to perform detection task. The original tumor volume was divided into sub-volumes with no prior information on the location of recurrence. Radiomic features from those sub-volumes were then used to detect recurrent sub-volumes using multivariable logistic regression.

resultsRadiomic features extracted from non-controlled regions differed significantly from those in controlled regions (training AUC = 0.79 CI 95% 0.66 - 0.91 and validation AUC = 0.88 CI 95% 0.72 - 1.00). Local radiomics analysis allowed efficient detection of non-controlled sub-volumes both in the training AUC = 0.66 (CI 95% 0.56 - 0.75) and validation cohort 0.70 (CI 95% 0.53 - 0.86), however performance of this model was inferior to bi-regional model. Both models indicated that sub-volumes characterized by higher heterogeneity were linked to tumor recurrence.

conclusionLocal radiomics is able to detect sub-volumes with decreased radiosensitivity, associated with location of tumor recurrence in HNSCC in the pre-treatment CT imaging. This proof of concept study, indicates that local CT radiomics can be used as predictive biomarker in radiotherapy and potential target for dose intensification.

Indexed as

contrast-enhanced CThead and neck cancerlocal radiomicspredictive biomarkerradioresistancetumor recurrence

Identifiers

PMID34123824
PMCPMC8191457
OpenAlexW3167725018

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.