63 research outputs found

    Using Intratumor Heterogeneity of Immunohistochemistry Biomarkers to Classify Laryngeal and Hypopharyngeal Tumors Based on Histologic Features

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    Haralick texture features are used to quantify the spatial distribution of signal intensities within an image. In this study, the heterogeneity of proliferation (Ki-67 expression) and immune cells (CD45 expression) within tumors was quantified and used to classify histologic characteristics of larynx and hypopharynx carcinomas. Of 21 laryngectomy specimens, 74 whole-mount tumor slides were scored on histologic characteristics. Ki-67 and CD45 immunohistochemistry was performed, and all sections were digitized. The tumor area was annotated in QuPath. Haralick features independent of the diaminobenzidine intensity were extracted from the isolated diaminobenzidine signal to quantify intratumor heterogeneity. Haralick features from both Ki-67 and CD45 were used as input for a principal component analysis. A linear support vector machine was fitted to the first 4 principal components for classification and validated with a leave-one-patient-out cross-validation method. Significant differences in individual Haralick features were found between cohesive and noncohesive tumors for CD45 (angular second motion: P =.03, inverse difference moment: P =.009, and entropy: P =.02) and between the larynx and hypopharynx tumors for both CD45 (angular second motion: P =.03, inverse difference moment: P =.007, and entropy: P =.005) and Ki-67 (correlation: P =.003). Therefore, these features were used for classification. The linear classifier resulted in a classification accuracy of 85% for site of origin and 81% for growth pattern. A leave-one-patient-out cross-validation resulted in an error rate of 0.27 and 0.35 for both classifiers, respectively. In conclusion, we show a method to quantify intratumor heterogeneity of immunohistochemistry biomarkers using Haralick features. This study also shows the feasibility of using these features to classify tumors by histologic characteristics. The classifiers created in this study are a proof of concept because more data are needed to create robust classifiers, but the method shows potential for automated tumor classification.</p

    Multi-modal volumetric concept activation to explain detection and classification of metastatic prostate cancer on PSMA-PET/CT

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    Explainable artificial intelligence (XAI) is increasingly used to analyze the behavior of neural networks. Concept activation uses human-interpretable concepts to explain neural network behavior. This study aimed at assessing the feasibility of regression concept activation to explain detection and classification of multi-modal volumetric data. Proof-of-concept was demonstrated in metastatic prostate cancer patients imaged with positron emission tomography/computed tomography (PET/CT). Multi-modal volumetric concept activation was used to provide global and local explanations. Sensitivity was 80% at 1.78 false positive per patient. Global explanations showed that detection focused on CT for anatomical location and on PET for its confidence in the detection. Local explanations showed promise to aid in distinguishing true positives from false positives. Hence, this study demonstrated feasibility to explain detection and classification of multi-modal volumetric data using regression concept activation.Comment: Accepted as: Kraaijveld, R.C.J., Philippens, M.E.P., Eppinga, W.S.C., J\"urgenliemk-Schulz, I.M., Gilhuijs, K.G.A., Kroon, P.S., van der Velden, B.H.M. "Multi-modal volumetric concept activation to explain detection and classification of metastatic prostate cancer on PSMA-PET/CT." MICCAI workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC), 202

    Brain and Head-and-Neck MRI in Immobilization Mask: A Practical Solution for MR-Only Radiotherapy

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    In brain/head-and-neck radiotherapy (RT), thermoplastic immobilization masks guarantee reproducible patient positioning in treatment position between MRI, CT, and irradiation. Since immobilization masks do not fit in the diagnostic MR head/head-and-neck coils, flexible surface coils are used for MRI imaging in clinical practice. These coils are placed around the head/neck, in contact with the immobilization masks. However, the positioning of these flexible coils is technician dependent, thus leading to poor image reproducibility. Additionally, flexible surface coils have an inferior signal-to-noise-ratio (SNR) compared to diagnostic coils. The aim of this work was to create a new immobilization setup which fits into the diagnostic MR coils in order to enhance MR image quality and reproducibility. For this purpose, a practical immobilization setup was constructed. The performances of the standard clinical and the proposed setups were compared with four tests: SNR, image quality, motion restriction, and reproducibility of inter-fraction subject positioning. The new immobilization setup resulted in 3.4 times higher SNR values on average than the standard setup, except directly below the flexible surface coils where similar SNR was observed. Overall, the image quality was superior for brain/head-and-neck images acquired with the proposed RT setup. Comparable motion restriction in feet-head/left-right directions (maximum motion ≈1 mm) and comparable inter-fraction repositioning accuracy (mean inter-fraction movement 1 ± 0.5 mm) were observed for the standard and the new setup

    Supine MRI for regional breast radiotherapy: Imaging axillary lymph nodes before and after sentinel-node biopsy

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    Regional radiotherapy (RT) is increasingly used in breast cancer treatment. Conventionally, computed tomography (CT) is performed for RT planning. Lymph node (LN) target levels are delineated according to anatomical boundaries. Magnetic resonance imaging (MRI) could enable individual LN delineation. The purpose was to evaluate the applicability of MRI for LN detection in supine treatment position, before and after sentinel-node biopsy (SNB). Twenty-three female breast cancer patients (cTis-3N0M0) underwent 1.5 T MRI, before and after SNB, in addition to CT. Endurance for MRI was monitored. Axillary levels were delineated. LNs were identified and delineated on MRI from before and after SNB, and on CT, and compared by Wilcoxon signed-rank tests. LN locations and LN-based volumes were related to axillary delineations and associated volumes. Although postoperative effects were visible, LN numbers on postoperative MRI (median 26 LNs) were highly reproducible compared to preoperative MRI when adding excised sentinel nodes, and higher than on CT (median 11, p < 0.001). LN-based volumes were considerably smaller than respective axillary levels. Supine MRI of LNs is feasible and reproducible before and after SNB. This may lead to more accurate RT target definition compared to CT, with potentially lower toxicity. With the MRI techniques described here, initiation of novel MRI-guided RT strategies aiming at individual LNs could be possible

    Управлiння iнновацiйним розвитком на регiональному рiвнi

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    Метою статтi є формування системи управлiння iнновацiями на регiональному рiвнi

    Diffusion weighted MRI with minimal distortion in head-and-neck radiotherapy using a turbo spin echo acquisition method

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    PURPOSE: Diffusion weighted (DW) MRI, showing high contrast between tumor and background tissue, is a promising technique in radiotherapy for tumor delineation. However, its use for head-and-neck patients is hampered by poor geometric accuracy in conventional echo planar imaging (EPI) DW-MRI. An alternative turbo spin echo sequence, DW-SPLICE, is implemented and demonstrated in patients. METHODS: The DW-SPLICE sequence was implemented on a 3.0T system and evaluated in 10 patients. The patients were scanned in treatment position, using a customized head support and immobilization mask. Image distortions were quantified at the gross tumor volume (GTV) using field map analysis. The apparent diffusion coefficient (ADC) was evaluated using an ice water phantom. RESULTS: The DW images acquired by DW-SPLICE showed no image distortions. Field map analysis at the gross tumor volumes resulted in a median distortion of 0.2 mm for DW-SPLICE, whereas for the conventional method this was 7.2 mm. ADC values, measured using an ice water phantom were in accordance with literature values. CONCLUSIONS: The implementation of DW-SPLICE allows for diffusion weighted imaging of patients in treatment position with excellent geometrical accuracy. The images can be used to facilitate target volume delineation in RT treatment planning. This article is protected by copyright. All rights reserved

    Evolution of motion uncertainty in rectal cancer : implications for adaptive radiotherapy

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    Reduction of motion uncertainty by applying adaptive radiotherapy strategies depends largely on the temporal behavior of this motion. To fully optimize adaptive strategies, insight into target motion is needed. The purpose of this study was to analyze stability and evolution in time of motion uncertainty of both the gross tumor volume (GTV) and clinical target volume (CTV) for patients with rectal cancer. We scanned 16 patients daily during one week, on a 1.5 T MRI scanner in treatment position, prior to each radiotherapy fraction. Single slice sagittal cine MRIs were made at the beginning, middle, and end of each scan session, for one minute at 2 Hz temporal resolution. GTV and CTV motion were determined by registering a delineated reference frame to time-points later in time. The 95th percentile of observed motion (dist95%) was taken as a measure of motion. The stability of motion in time was evaluated within each cine-MRI separately. The evolution of motion was investigated between the reference frame and the cine-MRIs of a single scan session and between the reference frame and the cine-MRIs of several days later in the course of treatment. This observed motion was then converted into a PTV-margin estimate. Within a one minute cine-MRI scan, motion was found to be stable and small. Independent of the time-point within the scan session, the average dist95% remains below 3.6 mm and 2.3 mm for CTV and GTV, respectively 90% of the time. We found similar motion over time intervals from 18 min to 4 days. When reducing the time interval from 18 min to 1 min, a large reduction in motion uncertainty is observed. A reduction in motion uncertainty, and thus the PTV-margin estimate, of 71% and 75% for CTV and tumor was observed, respectively. Time intervals of 15 and 30 s yield no further reduction in motion uncertainty compared to a 1 min time interval

    Examining the regional and cerebral depth-dependent BOLD cerebrovascular reactivity response at 7 T

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    Changes in cerebral blood flow (CBF) in response to hypercapnia induced changes in vascular tone, known as cerebrovascular reactivity (CVR), can be measured using the Blood Oxygenation Level Dependent (BOLD) MR contrast. We examine regional differences in the BOLD-CVR response to a progressively increasing hypercapnic stimulus as well as regional BOLD characteristics for the return to baseline normocapnia. CVR across 9 subjects was highest in the cerebral lobes and deep gray matter. Peak CVR in these regions was measured at 3.6 +/- 1.6 mm Hg above baseline end-tidal CO2. White matter CVR was generally reduced compared to that of the gray matter (peak white matter CVR was similar to 48% lower). A positive relationship between the end-tidal CO2 value at which peak CVR was measured and white matter depth is observed. Furthermore, the time required for the BOLD signal to return to baseline after cessation of the hypercapnic stimulus, was also related to white matter depth; the return, expressed as a time constant, was similar to 25% longer in white matter. To explain the observed differences in regional CVR response, a model is proposed that takes into account the local architecture of the cerebrovascular, which can result in changes in regional blood flow distribution as a function of end-tidal CO2. (C) 2015 Elsevier Inc. All rights reserved

    Pretreatment ADC is not a prognostic factor for local recurrences in head and neck squamous cell carcinoma when clinical T-stage is known

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    OBJECTIVES: Pretreatment identification of radio-insensitive head and neck squamous cell carcinomas (HNSCC) would affect treatment modality selection. The apparent diffusion coefficient (ADC) of a tumor could be a predictor of local recurrence. However, little is known about its prognostic value next to known factors such as clinical T-stage. The aim of the present study is to determine the added value of pretreatment ADC to clinical T-stage as a prognostic factor for local recurrence. METHODS: This retrospective cohort study included 217 patients with HNSCC treated with (chemo)radiotherapy between April 2009 and December 2015. All patients underwent diffusion-weighted MRI prior to treatment. Median ADC values of all tumors were obtained using a semi-automatic delineation method. Univariate models containing ADC and T-stage were compared with a multivariable model containing both variables. RESULTS: Fifty-eight patients experienced a local recurrence within 3 years. On average, the ADC value in the group of patients with a recurrence was 1.01 versus 1.00 (10-3 mm2/s) in the group without a recurrence. Univariate analysis showed no significant association between tumor ADC and local recurrence within 3 years after (chemo)radiotherapy (p = 0.09). Cox regression showed that clinical T-stage was an independent predictor of local recurrence and adding ADC to the model did not increase its performance. CONCLUSION: Pretreatment ADC has no added value as a prognostic factor for local recurrence to clinical T-stage. KEY POINTS: • Pretreatment identification of head and neck squamous cell carcinoma patients who do not benefit from (chemo)radiotherapy could improve personalized cancer care. • The apparent diffusion coefficient (ADC) obtained from diffusion-weighted MRI has been reported to be a prognostic factor for local recurrence. • In this study, ADC has no added value as a prognostic factor compared with clinical T-stage

    Pretreatment ADC is not a prognostic factor for local recurrences in head and neck squamous cell carcinoma when clinical T-stage is known

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    OBJECTIVES: Pretreatment identification of radio-insensitive head and neck squamous cell carcinomas (HNSCC) would affect treatment modality selection. The apparent diffusion coefficient (ADC) of a tumor could be a predictor of local recurrence. However, little is known about its prognostic value next to known factors such as clinical T-stage. The aim of the present study is to determine the added value of pretreatment ADC to clinical T-stage as a prognostic factor for local recurrence. METHODS: This retrospective cohort study included 217 patients with HNSCC treated with (chemo)radiotherapy between April 2009 and December 2015. All patients underwent diffusion-weighted MRI prior to treatment. Median ADC values of all tumors were obtained using a semi-automatic delineation method. Univariate models containing ADC and T-stage were compared with a multivariable model containing both variables. RESULTS: Fifty-eight patients experienced a local recurrence within 3 years. On average, the ADC value in the group of patients with a recurrence was 1.01 versus 1.00 (10-3 mm2/s) in the group without a recurrence. Univariate analysis showed no significant association between tumor ADC and local recurrence within 3 years after (chemo)radiotherapy (p = 0.09). Cox regression showed that clinical T-stage was an independent predictor of local recurrence and adding ADC to the model did not increase its performance. CONCLUSION: Pretreatment ADC has no added value as a prognostic factor for local recurrence to clinical T-stage. KEY POINTS: • Pretreatment identification of head and neck squamous cell carcinoma patients who do not benefit from (chemo)radiotherapy could improve personalized cancer care. • The apparent diffusion coefficient (ADC) obtained from diffusion-weighted MRI has been reported to be a prognostic factor for local recurrence. • In this study, ADC has no added value as a prognostic factor compared with clinical T-stage
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