SPECTRA: Intraoperative Hyperspectral Imaging for Prostate Cancer (SPECTRA)
Radical prostatectomy (RP) is currently one of the gold standard of care in managing localized prostate cancer (Pca). However, despite advances in Robot-Assisted RP (RARP), cancer cells may still be found (up to 42%) at the edge of the removed prostate specimen, commonly referred as Positive Surgical Margins (PSM). PSM are well-known risk factors of adverse oncological outcomes (biochemical recurrence).
It is therefore essential to characterize intraoperatively the tumor extent. In RARP, the leading intraoperative margin assessment (IMA) technique, NeuroSAFE is based on Intra-operative frozen section (IFS) of both prostate lateral sides sampled at 3-5 mm intervals. However, despite proven oncological benefit, adoption is still limited to expert centers due to a prolonged operative time, loss of integrity of the surgical specimen for definitive histopathological analysis, omission of regions (apex, base), and logistical complexity (trained uropathologist, cryostat…).
With this prospective single-center project, we wish to explore the use of non-invasive optical imaging technology, HyperSpectral Imaging (HSI), as a reliable alternative for examination of the ex-vivo prostate specimen to
- Distinguish normal versus tumor tissue at the surgical margin in fresh specimen.
- Quantify whether HSI can be integrated into the intraoperative workflow (feasibility), thus, image acquisition time and inference time should then be evaluated.
Обзор исследования
Статус
Подробное описание
Prostate cancer (Pca) is the second most frequently diagnosed cancer in men worldwide with over 1.5 million new cases annually and a median age at diagnosis of 66 years. Despite the natural history being slow and clinically insignificant in most cases, its heterogeneity and high prevalence mean it remains the second leading cause of cancer-related death worldwide. Treatment options depend on cancer stage, risk stratification and patient preferences.
Radical prostatectomy (RP), which consists of the surgical removal of the prostate and the seminal vesicles, is one of the gold-standard curative treatment for localized diseases. RP techniques include open, laparoscopic, and robotic-assisted surgery. Despite recent advances in the robotic field, positive surgical margins (PSM) can occur up to 42 %. According to the International Society of Urological Pathology (ISUP), PSM is defined by tumor cells reaching the inked surgical margin of the prostatectomy specimen. PSM significantly reduces progression-free survival and is a known prognostic parameter for postoperative biochemical recurrence (BCR).
Current margin assessment relies on Intraoperative Frozen Section (IFS), the current gold-standard technique is the Neurovascular Structure-Adjacent Frozen-Section Examination (NeuroSAFE). It consists of an IFS analysis of tissue adjacent to neurovascular bundles. While this neurovascular structure sparing method improves postoperative erectile function and reduces PSM, its implementation is limited due to additional operating time (45-60 minutes), increased resource demands on pathology departments, and the inability to provide a whole specimen analysis.
Hyperspectral Imaging (HSI) combines conventional imaging (camera) with a spectrometer, providing both spatial and spectral information of the analyzed structures, enabling tissue differentiation based on structural properties. HSI uses reflectance spectroscopic imaging measurements, which involve a white light irradiation of the tissue and subsequently a recording of the remitted spectral intensities. The interaction between the incident light and the tissue modifies the light's spectral distribution with the reflected light containing information about the tissue composition. This technology has already been successfully applied in visceral surgery to quantify liver viability during ischemic and reperfusion phases. More recently, in Urology, HSI was successfully used as a predictive tool for early postoperative kidney graft.
Another clinical application of HSI is the ability to discriminate between normal and cancerous tissue as observed in gastric, head and neck (H&N), colorectal, brain and breast cancers. Similarly, in 2024, spectral data from Diffuse Reflectance Spectroscopy (DRS) showed promising results achieving an average sensitivity of 89% with a specificity of 82%, in 59 prostatectomy specimens, confirming the potential of spectroscopy. However, DRS approach comes with limitations, more particularly in spatial orientation because it requires multiple point-based measurements across the prostate surface with the inability to evaluate the entire tissue volume. In contrast, HSI provides spatially resolved spectral data across the entire field of view, enabling comprehensive tissue mapping. In 2012, the feasibility of HSI for PCa detection was evaluated in in-vivo mice and in pathological tissue slides, achieving 93% sensitivity and 97% specificity using a support vector machine algorithm and providing an estimated AUC-ROC of 0.9485. In this context, HSI provides a unique opportunity to assess fully a specimen. However, its application for real-time margin assessment during surgery remains unexplored. Recently, a 3D pipeline that co-registers multi-angle ex-vivo HSI with volumetric histopathology was implemented, enabling voxel-wise tumor segmentation and AR visualization in H&N specimens using convolutional neural networks (CNNs).
This project aims to validate HSI feasibility in ex-vivo prostate specimens. By providing a non-invasive and contactless evaluation in the operating theatre, HSI could reduce PSM rates, minimizing adjuvant radiotherapy needs and overall, improve long-term oncological outcomes.
In this research project, the TIVITA® Tissue system, a CMOS (Complementary Metal Oxide Semiconductor) Push-broom Scanning Hyperspectral Camera device, designed for real-time tissue assessment, will be employed. This CE (Conformité Européenne) certified device can provide 640x480 pixel images with a spectral range of 500 to 1000 nm and a spectral resolution of 5nm. The illumination system consists in six 20 W halogen spotlights (OSRAM GmbH, Munich, Germany). Each measurement takes approximately 7 seconds with a measured area up to 20-30 cm (wide enough for a whole prostate specimen).
Тип исследования
Регистрация (Оцененный)
Фаза
- Непригодный
Контакты и местонахождение
Контакты исследования
- Имя: Vincent Benard, Resident
- Номер телефона: + 41 79 553 62 68
- Электронная почта: vincent.benard@hug.ch
Учебное резервное копирование контактов
- Имя: Laurence Zulianello, PhD
- Номер телефона: + 41 22 372 79 70
- Электронная почта: laurence.zulianello@hug.ch
Места учебы
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Canton of Geneva
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Geneva, Canton of Geneva, Швейцария, 1205
- Рекрутинг
- Hôpitaux Universitaires de Genève - Dept de Chirurgie - Service d'Urologie
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Контакт:
- Vincent Benard, Resident
- Номер телефона: + 41 79 553 62 68
- Электронная почта: vincent.benard@hug.ch
-
Контакт:
- Laurence Zulianello, PhD
- Номер телефона: + 41 79 553 44 15
- Электронная почта: laurence.zulianello@hug.ch
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Главный следователь:
- Massimo Valerio, Prof Dr med
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Младший исследователь:
- Jean-Christophe Tille, MD
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Младший исследователь:
- Oliver Windisch, MD
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Младший исследователь:
- Michele Diana, Prof Dr med
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Младший исследователь:
- Doron Merkler, Prof Dr med
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Младший исследователь:
- Mario Kreutzfeldt, MD
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Младший исследователь:
- Andrew Janawczyk, Prof Dr med
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Младший исследователь:
- Vincent Benard, Resident
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Младший исследователь:
- Christian Lovis, Prof Dr med
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Младший исследователь:
- Mina Bjelogrlic, PhD
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Критерии участия
Критерии приемлемости
Возраст, подходящий для обучения
- Взрослый
- Пожилой взрослый
Принимает здоровых добровольцев
Описание
Inclusion Criteria:
- Histological diagnosis (biopsy) of Pca
- Prostate volume < 100 cm3 (measured on preoperative MRI) for a smooth acquisition with the hyperspectral device
- Capable of forming his own views
Exclusion Criteria:
- Unwilling to participate.
- Inability to follow study procedures, for example due to language problems, psychological disorders, dementia, etc.
Учебный план
Как устроено исследование?
Детали дизайна
- Основная цель: Диагностика
- Распределение: Н/Д
- Интервенционная модель: Одногрупповое задание
- Маскировка: Нет (открытая этикетка)
Оружие и интервенции
Группа участников / Армия |
Вмешательство/лечение |
|---|---|
|
Экспериментальный: Participants with prostate cancer undergoing robot-assisted prostatectomy. HyperSpectral imaging.
One visit related to the research protocol which consists in the information consultation during which the participant receives detailed oral and written information. RAPR (day 0) is performed according to standard practice and is not part of the research-specific procedure. The study is then based solely on ex-vivo analysis. |
The study specific specimen handling consists in a multi-Angle HSI Image Acquisition before routine pathology. To enhance the co-registration between the two modalities, a black-ink may be applied on the ex-vivo specimen based on a MRI suspicious region of extra-prostatic extension (EPE Grade ≥ 2). This procedure follows prior robust registration work between ex-vivo HSI and histology evaluation. The identification of this region will rely on the standard pre-operative MRI review already performed as part of routine care within our prostate cancer center before each radical prostatectomy. |
Что измеряет исследование?
Первичные показатели результатов
Мера результата |
Мера Описание |
Временное ограничение |
|---|---|---|
|
Tumor extent
Временное ограничение: HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
Dice similarity coefficient between HSI-derived and histopathology spatial overlap between the HSI tumor map and co-registered histopathology
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HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
Вторичные показатели результатов
Мера результата |
Мера Описание |
Временное ограничение |
|---|---|---|
|
Boundary delineation
Временное ограничение: HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
Normalized surface distance between HSI-derived andhistopathological tumor contours.
Contour agreement
|
HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
|
Region overlap
Временное ограничение: HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
Jaccard index between HSI-derived and histopathological tumor masks intersection over union
|
HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
|
Foreground discrimination
Временное ограничение: HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
Pixel-wise sensitivity of HSI for tumor classification.
Proportion of histologically tumor-positive pixels classified as tumor
|
HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
|
Background discrimination
Временное ограничение: HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
Pixel-wise specificity of HSI for tumor classification .
Proportion of histologically non-tumor pixels classified as non-tumor
|
HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
|
Overall agreement:
Временное ограничение: HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
Pixel-wise accuracy of HSI for tumor classification.
Proportion of evaluated pixels correctly classified, histopathology as reference
|
HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
|
Clinical workflow
Временное ограничение: HSI acquisition on Day 0 (day of surgery)
|
HSI acquisition time
|
HSI acquisition on Day 0 (day of surgery)
|
|
Computational runtime
Временное ограничение: HSI acquisition on Day 0 (day of surgery)
|
Mean model inference time per hyperspectral image
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HSI acquisition on Day 0 (day of surgery)
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Другие показатели результатов
Мера результата |
Мера Описание |
Временное ограничение |
|---|---|---|
|
Surgical margins
Временное ограничение: HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
Diagnostic accuracy of HSI for detection of histologically positive margins
|
HSI acquisition on Day 0 (day of surgery); reference histopathological assessment on postoperative Days 7
|
Соавторы и исследователи
Спонсор
Следователи
- Главный следователь: Massimo Valerio, HUG
Даты записи исследования
Изучение основных дат
Начало исследования (Действительный)
Первичное завершение (Оцененный)
Завершение исследования (Оцененный)
Даты регистрации исследования
Первый отправленный
Впервые представлено, что соответствует критериям контроля качества
Первый опубликованный (Действительный)
Обновления учебных записей
Последнее опубликованное обновление (Действительный)
Последнее отправленное обновление, отвечающее критериям контроля качества
Последняя проверка
Дополнительная информация
Термины, связанные с этим исследованием
Ключевые слова
Дополнительные соответствующие термины MeSH
Другие идентификационные номера исследования
- 2026-00595
Планирование данных отдельных участников (IPD)
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Информация о лекарствах и устройствах, исследовательские документы
Изучает лекарственный продукт, регулируемый FDA США.
Изучает продукт устройства, регулируемый Управлением по санитарному надзору за качеством пищевых продуктов и медикаментов США.
Эта информация была получена непосредственно с веб-сайта clinicaltrials.gov без каких-либо изменений. Если у вас есть запросы на изменение, удаление или обновление сведений об исследовании, обращайтесь по адресу register@clinicaltrials.gov. Как только изменение будет реализовано на clinicaltrials.gov, оно будет автоматически обновлено и на нашем веб-сайте. .