[OA089] Diffusing Alpha-emitters Radiation Therapy (DaRT): template based treatment planning technique for brachytherapy of squamous cell skin cancer

Cutaneous squamous cell carcinoma is the second most common form of skin cancer and accounts for 20% of cutaneous malignancies. We report the case of a patient who presented with a complaint of nonhealing wounds following radiation therapy for the treatment of noninvasive squamous cell carcinoma of both lower extremities. Initial biopsies of the wounds were benign. However, a second biopsy performed approximately 2 months later was found to be positive for invasive squamous cell carcinoma. This case uniquely exemplifies that all nonhealing wounds should be viewed with a critical eye for possible malignancy even in the presence of previous negative biopsy. This is especially true for radiation wounds that may be prone to malignant transformation or recurrence. (J Am Podiatr Med Assoc 101(4): 360–362, 2011)

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A knowledge-based intensity-modulated radiation therapy treatment planning technique for locally advanced nasopharyngeal carcinoma radiotherapy

10.21203/rs.3.rs-19262/v3 ◽

2020 ◽

Author(s):

Penggang Bai ◽

Xing Weng ◽

Kerun Quan ◽

Jihong Chen ◽

Yitao Dai ◽

...

Keyword(s):

Radiation Therapy ◽

Nasopharyngeal Carcinoma ◽

Treatment Planning ◽

Locally Advanced ◽

Intensity Modulated Radiation Therapy ◽

Target Volume ◽

Planning System ◽

Intensity Modulated ◽

Knowledge Based ◽

Planning Technique

Abstract BackgroundTo investigate the feasibility of a knowledge-based automated intensity-modulated radiation therapy (IMRT) planning technique for locally advanced nasopharyngeal carcinoma (NPC) radiotherapy.Methods140 NPC patients treated with definitive radiation therapy with the step-and-shoot IMRT techniques were retrospectively selected and separated into a knowledge library (n=115) and a test library (n=25). For each patient in the knowledge library, the overlap volume histogram (OVH), target volume histogram (TVH) and dose objectives were extracted from the manually generated plan. 5-fold cross validation was performed to divide the patients in the knowledge library into 5 groups before validating one group by using the other 4 groups to train each neural network (NN) machine learning models. For patients in the test library, their OVH and TVH were then used by the trained models to predict a corresponding set of mean dose objectives, which were subsequently used to generate automated plans (APs) in Pinnacle planning system via an in-house developed automated scripting system. All APs were obtained after a single step of optimization. Manual plans (MPs) for the test patients were generated by an experienced medical physicist strictly following the established clinical protocols. The qualities of the APs and MPs were evaluated by an attending radiation oncologist. The dosimetric parameters for planning target volume (PTV) coverage and the organs-at-risk (OAR) sparing were also quantitatively measured and compared using Mann-Whitney U test and Bonferroni correction.ResultsAPs and MPs had the same rating for more than 80% of the patients (19 out of 25) in the test group. Both AP and MP achieved PTV coverage criteria for no less than 80% of the patients. For each OAR, the number of APs achieving its criterion was similar to that in the MPs. The AP approach improved planning efficiency by greatly reducing the planning duration to about 17% of the MP (9.85±1.13 min vs. 57.10±6.35 min).ConclusionA robust and effective knowledge-based IMRT treatment planning technique for locally advanced NPC is developed. Patient specific dose objectives can be predicted by trained NN models based on the individual’s OVH and clinical TVH goals. The automated planning scripts can use these dose objectives to efficiently generate APs with largely shortened planning time. These APs had comparable dosimetric qualities when compared to our clinic’s manual plans.

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A knowledge-based intensity-modulated radiation therapy treatment planning technique for locally advanced nasopharyngeal carcinoma radiotherapy

10.21203/rs.3.rs-19262/v2 ◽

2020 ◽

Author(s):

Penggang Bai ◽

Xing Weng ◽

Kerun Quan ◽

Jihong Chen ◽

Yitao Dai ◽

...

Keyword(s):

Radiation Therapy ◽

Nasopharyngeal Carcinoma ◽

Treatment Planning ◽

Locally Advanced ◽

Intensity Modulated Radiation Therapy ◽

Target Volume ◽

Planning System ◽

Intensity Modulated ◽

Knowledge Based ◽

Planning Technique

Abstract BackgroundTo investigate the feasibility of a knowledge-based automated intensity-modulated radiation therapy (IMRT) planning technique for locally advanced nasopharyngeal carcinoma (NPC) radiotherapy.Methods140 NPC patients treated with definitive radiation therapy with the step-and-shoot IMRT techniques were retrospectively selected and seperated into a knowledge library (n=115) and a test library (n=25). For each case, in the knowledge library, the patient’s overlap volume histogram (OVH), target volume histogram (TVH) and dose objectives were extracted from the manually generated plan to train a 3-layer neural network (NN) machine learning model. For patients in the test library, their OVH and TVH were then used by the trained model to predict a corresponding set of dose objectives, which were subsequently used to generate automated plans (APs) in Pinnacle planning system via an in-house developed automated scripting system. All APs were obtained after a single step of optimization. Manual plans (MPs) of the same test patients were generated by an experienced medical physicist strictly following the established clinical protocols. The qualities of the APs and MPs were evaluated by an attending radiation oncologist. The dosimetric parameters for planning target volume (PTV) coverage and the organs-at-risk (OAR) sparing were also quantitatively measured and compared.ResultsAPs and MPs had the same rating for more than 80% of the patients (19 out of 25) in the test group. For greater than 80% of the patients, both AP and MP achieved PTV coverage criteria. For each OAR, the number of APs achieving its criterion was similar to that in the MPs. The AP approach significantly improved planning efficiency by reducing the planning duration to about 17% of the MP (9.73±1.80 min vs. 57.10±6.35 min, P<0.001). ConclusionA robust and effective knowledge-based IMRT treatment planning technique for locally advanced NPC is developed. Patient specific dose objectives can be predicted by a trained NN model based on the individual’s OVH and clinical TVH goals. The automated planning scripts can use these dose objectives to efficiently generate APs with largely shortened planning time. These APs had comparable dosimetric qualities when compared to our clinic’s manual plans.

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Iridium-192 interstitial implant in the treatment of advanced squamous cell carcinoma of the tonsil region: Treatment planning, technique, and clinical results

European Journal of Cancer ◽

10.1016/0959-8049(93)91440-v ◽

1993 ◽

Vol 29 ◽

pp. S148

Author(s):

JK Hayes ◽

JH Moeller ◽

RK Davis

Keyword(s):

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Treatment Planning ◽

Squamous Cell ◽

Clinical Results ◽

Advanced Squamous Cell Carcinoma ◽

Planning Technique ◽

Iridium 192

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Practical Dosimetry in the Treatment of Head-and-Neck Squamous Cell Carcinoma by Diffusing Alpha-Emitters Radiation Therapy ("Alpha DaRT")

Brachytherapy ◽

10.1016/j.brachy.2018.04.259 ◽

2018 ◽

Vol 17 (4) ◽

pp. S138-S139 ◽

Cited By ~ 1

Author(s):

Itzahk Kelson ◽

Aron Popovtzer ◽

Lior Arazi ◽

Ran Ben Hur ◽

Yona Keisari

Keyword(s):

Squamous Cell Carcinoma ◽

Radiation Therapy ◽

Cell Carcinoma ◽

Head And Neck ◽

Squamous Cell ◽

Neck Squamous Cell Carcinoma ◽

Alpha Emitters

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14. Radiation Therapy Planning for Skin Cancer: Using 3D Surface Scanning to Localize Tumour

Inquiry@Queen's Undergraduate Research Conference Proceedings ◽

10.24908/iqurcp.11735 ◽

2018 ◽

Author(s):

Anna Ilina

Keyword(s):

Radiation Therapy ◽

Skin Cancer ◽

Treatment Planning ◽

Planning System ◽

Treatment Planning System ◽

Ct Image ◽

Invasive Treatment ◽

Surface Scanning ◽

3D Surface ◽

Surface Scan

Orthovoltage radiation therapy (ORT) is a non‑invasive treatment often used for patients with skin cancer, which is characterized by shallow tumours visible at the surface of the skin. Currently there is no commercially available treatment planning system for ORT. The first step of treatment planning is localizing the tumour in a computed tomography (CT) scan of the patient. We propose using 3D surface scanning to obtain a coloured and textured image of the patient, from which the tumour can be identified. The contour of the tumour can then be overlaid onto the CT image, for planning delivery of radiation therapy. This process was demonstrated using a male mannequin model, with a red sticker on the nose representing a skin tumour. A coloured and textured image of the face was obtained using a handheld 3D surface scanner [Figure 1]. The surface scan was aligned to a CT image of the mannequin head using a two‑step registration process, with a resulting error of 0.25mm. The tumour could then be easily segmented from the coloured surface scan by following the outline of the lesion. The tumour contour was extended in depth to 1cm, to encompass subdermal cancerous tissue in the treatment volume, and saved with the CT image for treatment planning [Figure 2]. This workflow is the first step to an open-source treatment planning system for ORT, which will allow physicians to deliver more precise treatment using ORT. This project was done in collaboration with the Kingston General Hospital.

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