Methods in Cancer Imaging and Image-directed Interventions

Editorial

17 October 2023

Editorial: Methods in cancer imaging and image-directed interventions

Jasper Nijkamp

and

Bahram Mohajer

764 views

0 citations

Editors

Bahram Mohajer

Department of Radiology, Perelman School of Medicine, University of Pennsylvania

Jasper Nijkamp

Department of Clinical Medicine, Faculty of Health, Aarhus University

Impact

In this example two readers (R1 and R4) selected the same lesions with different classification of target and non-target leading to discrepant responses. This discrepancy hinges on the measurement of the lymph node (15mm for Reader 4, and unstated for Reader 1) as well as the subjective opinion of Readers 1 and 4 about the measurability of the lung lesion.

Original Research

16 March 2023

Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?

Antoine Iannessi

and

Hubert Beaumont

2,796 views

5 citations

Methods

02 March 2023

Intrafraction tumor motion monitoring and dose reconstruction for liver pencil beam scanning proton therapy

Saber Nankali

, 7 more and

Per Rugaard Poulsen

2,545 views

5 citations

Original Research

19 April 2023

A novel approach for automatic segmentation of prostate and its lesion regions on magnetic resonance imaging

Huipeng Ren

, 10 more and

Ming Zhang

2,561 views

4 citations

Original Research

21 March 2023

The synergized diagnostic value of VTQ with chemokine CXCL13 in lung tumors

Xu Zhang

, 9 more and

Rui Tian

1,240 views

1 citations

Original Research

20 February 2023

Correlation between ADC, ADC ratio, and Gleason Grade group in prostate cancer patients undergoing radical prostatectomy: Retrospective multicenter study with different MRI scanners

Johan Bengtsson

, 5 more and

Despina Flondell-Sité

2,320 views

12 citations

The mean and standard deviation for each metric are represented as the center and extremes of the error bars, respectively. Statistical significance was determined using Wilcoxon signed-rank tests corrected with Benjamini-Hochberg procedure for all OARs and models. Comparison symbols: ns (p > 0.05), * (p ≤ 0.05), ** (p ≤ 0.01), *** (p ≤ 1e-4), **** (p ≤ 1e-5).

Original Research

28 February 2023

Segmentation stability of human head and neck cancer medical images for radiotherapy applications under de-identification conditions: Benchmarking data sharing and artificial intelligence use-cases

Jaakko Sahlsten

, 8 more and

Kimmo Kaski

2,590 views

6 citations

Original Research

13 February 2023

Lesion-specific 3D-printed moulds for image-guided tissue multi-sampling of ovarian tumours: A prospective pilot study

Maria Delgado-Ortet

, 15 more and

Evis Sala

3,758 views

2 citations

Original Research

31 January 2023

A CT-based radiomics approach to predict immediate response of radiofrequency ablation in colorectal cancer lung metastases

Haozhe Huang

, 8 more and

Wentao Li

3,128 views

3 citations

$(A) Doses from all fractions are mapped backward onto the pre-treatment simulation anatomy. (B) Doses from all fractions are mapped forward onto the anatomy from the last fraction. (C) At a given time point during RT, all previous doses are mapped forward onto the anatomy for the current fraction. The summed dose is used as an input for dose-optimized adaptive replanning. All doses are scaled to the total prescription dose.$

Review

26 January 2023

Dose accumulation for MR-guided adaptive radiotherapy: From practical considerations to state-of-the-art clinical implementation

Brigid A. McDonald

, 16 more and

Kristy K. Brock

MRI-linear accelerator (MR-linac) devices have been introduced into clinical practice in recent years and have enabled MR-guided adaptive radiation therapy (MRgART). However, by accounting for anatomical changes throughout radiation therapy (RT) and delivering different treatment plans at each fraction, adaptive radiation therapy (ART) highlights several challenges in terms of calculating the total delivered dose. Dose accumulation strategies—which typically involve deformable image registration between planning images, deformable dose mapping, and voxel-wise dose summation—can be employed for ART to estimate the delivered dose. In MRgART, plan adaptation on MRI instead of CT necessitates additional considerations in the dose accumulation process because MRI pixel values do not contain the quantitative information used for dose calculation. In this review, we discuss considerations for dose accumulation specific to MRgART and in relation to current MR-linac clinical workflows. We present a general dose accumulation framework for MRgART and discuss relevant quality assurance criteria. Finally, we highlight the clinical importance of dose accumulation in the ART era as well as the possible ways in which dose accumulation can transform clinical practice and improve our ability to deliver personalized RT.

5,688 views

25 citations

Original Research

09 January 2023

Diagnostic value of [68Ga]Ga-FAPI-04 in patients with colorectal cancer in comparison with [18F]F-FDG PET/CT

Xinfeng Lin

, 8 more and

Xuejuan Wang

Purpose: This study aimed to compare the diagnostic performance of [⁶⁸Ga]Ga-FAPI-04 PET/CT and [¹⁸F]F-FDG PET/CT in primary and metastatic colorectal cancer (CRC) lesions.

Methods: This single-center preliminary clinical study (NCT04750772) was conducted at the Peking University Cancer Hospital & Institute and included 61 participants with CRC who underwent sequential evaluation through PET/CT with [¹⁸F]F-FDG and [⁶⁸Ga]Ga-FAPI-04. Their PET/CT images were analysed to quantify the uptake of the two tracers in the form of maximum standardised uptake (SUV_max) values and target-to-background ratio (TBR), which were then compared using Wilcoxon’s signed-rank test. The final changes in the tumour–node–metastasis (TNM) stage of all participants were recorded.

Results: Of all the participants, 21 were treatment naïve and 40 had been previously treated. In primary CRC lesions, the average TBRs of [⁶⁸Ga]Ga-FAPI-04 and [¹⁸F]F-FDG were 13.3 ± 8.9 and 8.2 ± 6.5, respectively. The SUV_max of [⁶⁸Ga]Ga-FAPI-04 in signet-ring/mucinous carcinomas (11.4 ± 4.9) was higher than that of [¹⁸F]F-FDG (7.9 ± 3.6) (P = 0.03). Both median SUV_max in peritoneal metastases and TBR in liver metastases of [⁶⁸Ga]Ga-FAPI-04 were higher than those of [¹⁸F]F-FDG (5.2 vs. 3.8, P < 0.001; 3.7 vs. 1.9, P < 0.001, respectively). Compared with [¹⁸F]F-FDG PET/CT, clinical TNM staging based on [⁶⁸Ga]Ga-FAPI-04 PET/CT led to upstaging and downstaging in 10 (16.4%) and 5 participants (8.2%), respectively. Therefore, the treatment options were changed in 13 participants (21.3%), including 9 with additional chemo/radiotherapy and/or surgery and others with avoidance or narrowed scope of surgery.

Conclusion: [⁶⁸Ga]Ga-FAPI-04 showed potential as a novel PET/CT tracer to detect lymph nodes and distant metastases, which improved CRC staging, thus prompting the optimisation or adjustment of treatment decisions.

2,625 views

23 citations

Original Research

13 January 2023

Magnetic resonance imaging radiomics to differentiate ovarian sex cord-stromal tumors and primary epithelial ovarian cancers

Meiying Cheng

, 9 more and

Xin Zhao

1,403 views

4 citations

Systematic Review

24 November 2022

Visualising spatial heterogeneity in glioblastoma using imaging habitats

Mueez Waqar

, 10 more and

Gerben R. Borst

Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glioblastoma’s imaging features and heterogeneity have focussed on individual imaging biomarkers, or high-throughput radiomic approaches that consider a vast number of imaging variables across the tumour as a whole. Habitat imaging is a novel approach to cancer imaging that identifies tumour regions or ‘habitats’ based on shared imaging characteristics, usually defined using multiple imaging biomarkers. Habitat imaging reflects the evolution of imaging biomarkers and offers spatially preserved assessment of tumour physiological processes such perfusion and cellularity. This allows for regional assessment of treatment response to facilitate personalised therapy. In this review, we explore different methodologies to derive imaging habitats in glioblastoma, strategies to overcome its technical challenges, contrast experiences to other cancers, and describe potential clinical applications.

4,618 views

14 citations