Laser interstitial thermotherapy (LITT) for breast cancer: dosimetry optimization and numerical simulation.

Surgical treatment is standard for the treatment of small breast cancers. Due to the pain and esthetic sequelae that can follow surgery, minimally invasive treatments are under investigation. Our aim was to conduct a dosimetry study of laser interstitial thermotherapy. Turkey tissue was used as an ex vivo model, and mammary glands from ewes were used as in vivo models. We used two different wavelength lasers (805 nm and 980 nm). Two types of fiber from two different manufacturers were used: bare fibers with a diameter of 600 µm and diffusing fiber. The diffusing fibers were 5 mm and 10 mm in length. We also used a computerized model to predict thermal damage and to correlate with the ex vivo and in vivo procedures using a constant and variable coefficient. The mathematical model was based on the finite element method for solving light distribution, bio-heat, and thermal damage equations. Based on our ex vivo and in vivo experiments, we found that the optimal configuration for this treatment was the use of the 980-nm laser at 4 W with bare fibers for a minimum treatment time of 150 s. We also developed a predictive mathematical model that showed good predictability of necrosis in line with the experimental data. Laser treatment is a promising therapy for small breast lesions. However, further development of treatment guidance is necessary to support its use in clinical practice.

Photodynamic therapy for glioblastoma: A preliminary approach for practical application of light propagation models.

PURPOSE: Photodynamic therapy (PDT) is a promising treatment modality to be added in the management of glioblastoma multiforme (GBM). Light distribution modeling is required for planning and optimizing PDT. Several models have been developed to predict the light propagation inside biological tissues. In the present study, two analytical methods of light propagation emitted from a cylindrical fiber source were evaluated: a discrete and a continuous method. METHODS: The two analytical approaches were compared according to their fluence rate results. Several cylindrical diffuse lengths were evaluated, and the relative deviation in the fluence rates was estimated. Moreover, a sensitivity analysis was conducted to compute the variance of each analytical model. RESULTS: The discrete method provided fluence rate estimations closer to the Monte-Carlo simulations than the continuous method. The sensitivity study results did not reveal significant differences between the variance of the two analytical models. CONCLUSIONS: Although the discrete model provides relevant light distribution, the heterogeneity of GBM tissues was not considered. With the improvement in parallel computing that drastically decreased the computing time, replacing the analytical model by a Monte-Carlo GPU-accelerated code appeared relevant to the GBM case. Nonetheless, the analytical modeling may still function in the optimization algorithms, which might be used in the Photodynamic treatment planning system. Lasers Surg. Med. 50:523-534, 2018. © 2017 Wiley Periodicals, Inc.

Is interstitial photodynamic therapy for brain tumors ready for clinical practice? A systematic review.

BACKGROUND: Interstitial photodynamic therapy (iPDT), inserting optical fibers inside brain tumors, has been proposed for more than 30 years. While a promising therapeutic option, it is still an experimental treatment, with different ways of application, depending on the team performing the technique. OBJECTIVE: In this systematic review, we reported the patient selection process, the treatment parameters, the potential adverse events and the oncological outcomes related to iPDT treatment applied to brain tumors. METHODS: We performed a search in PubMed, Embase and Medline based on the following Mesh terms: "interstitial" AND "photodynamic therapy" AND "brain tumor" OR "glioma" OR glioblastoma" from January 1990 to April 2020. We screened 350 studies. Twelve matched all selection criteria. RESULTS: 251 patients underwent iPDT. Tumors were mainly de novo or recurrent high-grade gliomas (171 (68%) of glioblastomas), located supratentorial, with a median volume of 12 cm3. Hematoporphyrin derive agent (HpD) or protoporphyrin IX (PpIX) induced by 5-aminolevulinic acid (5-ALA) was used as a photosensitizer. Up to 6 optical fibers were introduced inside the tumor, delivering 200 mW/cm at a wavelength of 630 nm. Overall mortality was 1%. Transient and persistent morbidity were both 5%. No permanent deficit occurred using 5-ALA PDT. Tumor response rate after iPDT was 92% (IQR, 67; 99). Regarding glioblastomas, progression-free-survival was respectively 14.5 months (IQR, 13.8; 15.3) for de novo lesions and 14 months (IQR, 7; 30) for recurrent lesions, while overall survival was respectively 19 months (IQR, 14; 20) and 8 months (IQR, 6.3; 8.5). In patients harboring high-grade gliomas, 33 (13%) were considered long-term survivors (> 2 years) after iPDT. CONCLUSION: Regardless of heterogeneity in its application, iPDT appears safe and efficient to treat brain tumors, especially high-grade gliomas. Stand-alone iPDT (i.e., without combined craniotomy and intracavitary PDT) using 5-ALA appears to be the best option in terms of controlling side effects: it avoids the occurrence of permanent neurological deficits while reducing the risks of hemorrhage and sepsis.

Real-time light dosimetry for intra-cavity photodynamic therapy: Application for pleural mesothelioma treatment.

Complete and homogeneous illumination of the target is necessary for the success of a photodynamic therapy (PDT) procedure. In most applications, light dosimetry is done using detectors placed at strategic locations of the target. In this study we propose a novel approach based on the combination of light distribution modeling with spatial localization of the light applicator for real time estimation and display of the applied dose on medical images. The feasibility approach is demonstrated for intrapleural PDT of malignant pleural mesothelioma.

Laser interstitial thermotherapy application for breast surgery: Current situation and new trends.

While breast specialists debate on therapeutic de-escalation in breast cancer, the treatment of benign lesions is also discussed in relation to new percutaneous ablation techniques. The purpose of these innovations is to minimize potential morbidity. Laser Interstitial ThermoTherapy (LITT) is an option for the ablation of targeted nodules. This review evaluated the scientific publications investigating the LITT approach in malignant and benign breast disease. Three preclinical studies and eight clinical studies (2 studies including fibroadenomas and 6 studies including breast cancers) were reviewed. Although the feasibility and safety of LITT have been confirmed in a phase I trial, heterogeneous inclusion criteria and methods seem to be the main reason for LITT not being yet an extensively used treatment option. In conclusion, further development is necessary before this technique can be used in daily practice.

Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

Accurate tumor segmentation in [18F]-fluorodeoxyglucose positron emission tomography is crucial for tumor response assessment and target volume definition in radiation therapy. Evaluation of segmentation methods from clinical data without ground truth is usually based on physicians' manual delineations. In this context, the simultaneous truth and performance level estimation (STAPLE) algorithm could be useful to manage the multi-observers variability. In this paper, we evaluated how this algorithm could accurately estimate the ground truth in PET imaging. Complete evaluation study using different criteria was performed on simulated data. The STAPLE algorithm was applied to manual and automatic segmentation results. A specific configuration of the implementation provided by the Computational Radiology Laboratory was used. Consensus obtained by the STAPLE algorithm from manual delineations appeared to be more accurate than manual delineations themselves (80% of overlap). An improvement of the accuracy was also observed when applying the STAPLE algorithm to automatic segmentations results. The STAPLE algorithm, with the configuration used in this paper, is more appropriate than manual delineations alone or automatic segmentations results alone to estimate the ground truth in PET imaging. Therefore, it might be preferred to assess the accuracy of tumor segmentation methods in PET imaging.

Evaluation of PET volume segmentation methods: comparisons with expert manual delineations.

INTRODUCTION: [¹8F]-Fluorodeoxyglucose PET has become an essential technique in oncology. Accurate segmentation is important for treatment planning. With the increasing number of available methods, it will be useful to establish a reliable evaluation tool. METHOD: Five methods for [F]-fluorodeoxyglucose PET image segmentation (MIP-based, Fuzzy C-means, Daisne, Nestle and the 42% threshold-based approach) were evaluated on non-Hodgkin's lymphoma lesions by comparing them with manual delineations performed by a panel of experts. The results were analyzed using different similarity measures. Intraoperator and interoperator variabilities were also studied. RESULTS: The maximum of intensity projection-based method provided results closest to the manual delineations set [binary Jaccard index mean (SD) 0.45 (0.15)]. The fuzzy C-means algorithm yielded slightly less satisfactory results. The application of a 42% threshold-based approach yielded results furthest from the manual delineations [binary Jaccard index mean (SD) 0.38 (0.16)]; the Daisne and the Nestle methods yielded intermediate results. Important intraoperator and interoperator variabilities were demonstrated. CONCLUSION: A simple assessment framework based on comparisons with manual delineations was proposed. The use of a set of manual delineations performed by five different experts as the reference seemed to be suitable to take the intraoperator and the interoperator variabilities into account. The online distribution of the data set generated in this study will make it possible to evaluate any new segmentation method.

A new method for volume segmentation of PET images, based on possibility theory.

18F-fluorodeoxyglucose positron emission tomography (18FDG PET) has become an essential technique in oncology. Accurate segmentation and uptake quantification are crucial in order to enable objective follow-up, the optimization of radiotherapy planning, and therapeutic evaluation. We have designed and evaluated a new, nearly automatic and operator-independent segmentation approach. This incorporated possibility theory, in order to take into account the uncertainty and inaccuracy inherent in the image. The approach remained independent of PET facilities since it did not require any preliminary calibration. Good results were obtained from phantom images [percent error =18.38% (mean) ± 9.72% (standard deviation)]. Results on simulated and anatomopathological data sets were quantified using different similarity measures and showed the method was efficient (simulated images: Dice index =82.18% ± 13.53% for SUV =2.5 ). The approach could, therefore, be an efficient and robust tool for uptake volume segmentation, and lead to new indicators for measuring volume of interest activity.