Diffusion weighted MRI as an early predictor of tumor response to hypofractionated stereotactic boost for prostate cancer.

We evaluated the feasibility of using the kinetic of diffusion-weighted MRI (DWI) and the normalized apparent coefficient diffusion (ADC) map value as an early biomarker in patients treated by external beam radiotherapy (EBRT). Twelve patients were included within the frame of a multicenter phase II trial and treated for intermediate risk prostate cancer (PCa). Multiparametric MRI was performed before treatment (M0) and every 6 months until M24. Association between nADC and PSA or PSA kinetic was evaluated using the test of nullity of the Spearman correlation coefficient. The median rates of PSA at the time of diagnosis, two years and four years after EBRT were 9.29 ng/ml (range from 5.26 to 17.67), 0.68 ng/ml (0.07-2.7), 0.47 ng/ml (0.09-1.39), respectively. Median nADC increased from 1.14 × 10-3 mm2/s to 1.59 × 10-3 mm2/s between M0 and M24. Only one patient presented a decrease of nADC (1.35 × 10-3 mm2/s and 1.11 × 10-3 mm2/s at M0 and M12 respectively). The increase in nADC at M6 was correlated with PSA decrease at M18, M24 and M30 (p < 0.05). The increase in nADc at M12 was correlated with PSA decrease at M36 (p = 0.019). Early nADC variation were correlated with late PSA decrease for patients with PCa treated by EBRT.

Malignant pleural mesothelioma segmentation for photodynamic therapy planning.

Medical imaging modalities such as computed tomography (CT) combined with computer-aided diagnostic processing have already become important part of clinical routine specially for pleural diseases. The segmentation of the thoracic cavity represents an extremely important task in medical imaging for different reasons. Multiple features can be extracted by analyzing the thoracic cavity space and these features are signs of pleural diseases including the malignant pleural mesothelioma (MPM) which is the main focus of our research. This paper presents a method that detects the MPM in the thoracic cavity and plans the photodynamic therapy in the preoperative phase. This is achieved by using a texture analysis of the MPM region combined with a thoracic cavity segmentation method. The algorithm to segment the thoracic cavity consists of multiple stages. First, the rib cage structure is segmented using various image processing techniques. We used the segmented rib cage to detect feature points which represent the thoracic cavity boundaries. Next, the proposed method segments the structures of the inner thoracic cage and fits 2D closed curves to the detected pleural cavity features in each slice. The missing bone structures are interpolated using a prior knowledge from manual segmentation performed by an expert. Next, the tumor region is segmented inside the thoracic cavity using a texture analysis approach. Finally, the contact surface between the tumor region and the thoracic cavity curves is reconstructed in order to plan the photodynamic therapy. Using the adjusted output of the thoracic cavity segmentation method and the MPM segmentation method, we evaluated the contact surface generated from these two steps by comparing it to the ground truth. For this evaluation, we used 10 CT scans with pathologically confirmed MPM at stages 1 and 2. We obtained a high similarity rate between the manually planned surface and our proposed method. The average value of Jaccard index was about 0.79 and we obtained a value of 0.88 using the Dice index.

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.

Quantified analysis of histological components and architectural patterns of gleason grades in apparent diffusion coefficient restricted areas upon diffusion weighted MRI for peripheral or transition zone cancer locations.

PURPOSE: To quantify and compare the histological components and architectural patterns of Gleason grades in cancerous areas with restriction on apparent diffusion coefficient (ADC) maps. MATERIALS AND METHODS: Twelve consecutive cases with 14 separate ADC restriction areas, positive for cancer in the peripheral zone (PZ) and transition zone (TZ) were included. All had 3 Tesla MRI and radical prostatectomy. Ten regions of interest (ROIs) within and outside the 14 ADC restriction areas positive for cancer were selected. For each ROI, we performed quantitative analysis of (a) prostate benign and malignant histological component surface ratios, including stroma, glands, epithelium, lumen, cellular nuclei; (b) percent of Gleason grades and measures of ADC values. Means of histological components according to ADC restriction for cancerous area were compared with analyses of variance with repeated measures. RESULTS: Independent predictors of the probability of cancer were median epithelium/ROI ratio (P = 0.001) and nuclei/ROI ratio (P = 0.03). Independent predictors of the probability of ADC restriction were malignant glands/ROI and luminal space/ROI (P < 0.0001). Effect of malignant glands/ROI area was different according to the localization of the ROI (P = 0.03). We observed an overall difference between the means for all of the histological components for the comparison of true positive and false negative (P < 0.0001), except for the percent of Gleason grade 4 (P = 0.18). In TZ cancers, a predominant grade 3 pattern was associated with low ADC values. In PZ cancers, a predominant grade 4 pattern was associated with low ADC values. CONCLUSION: Determinants of low ADC were high ratio of malignant glands/ROI area which may be seen in Gleason grades 3 or 4 cancers. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1786-1796.

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.

Focal therapy as primary treatment for localized prostate cancer: definition, needs and future.

Focal therapy (FT) may offer a promising treatment option in the field of low to intermediate risk localized prostate cancer. The aim of this concept is to combine minimal morbidity with cancer control as well as maintain the possibility of retreatment. Recent advances in MRI and targeted biopsy has improved the diagnostic pathway of prostate cancer and increased the interest in FT. However, before implementation of FT in routine clinical practice, several challenges are still to overcome including patient selection, treatment planning, post-therapy monitoring and definition of oncologic outcome surrogates. In this article, relevant questions regarding the key steps of FT are critically discussed and the main available energy modalities are analyzed taking into account their advantages and unmet needs.

Illumination profile characterization of a light device for the dosimetry of intra-pleural photodynamic therapy for mesothelioma.

BACKGROUND: Complete and homogeneous illumination of the pleural cavity is essential to the success of photodynamic therapy (PDT) for mesothelioma, but remains a challenge. Knowing the repartition and propagation of light around the light applicator could be the first step towards optimizing dosimetry. Here we propose a characterization method of the illumination profile of a specific light device. METHODS: The light wand, made of a cylindrical diffuser located inside an endotracheal tube, was fixed in a tank filled with dilute 0.01% intralipid. Light dosimetry was performed around the tip of the wand using two complementary methods: direct measurements of light power with an isotropic probe and measurements of light distribution characterization. RESULTS: Dosimetry with the isotropic probe showed an ellipse-shaped illumination. An optimized effective attenuation coefficient was deduced. Combined with the spatial representation, a theoretical illumination profile was established with iso-surfaces of fluence rate, defining a gradient light dose according to the distance from the diffuser. CONCLUSION: A theoretical illumination profile of a light device was established and could be part of an intra-operative dosimetry system to improve light delivery during intrapleural PDT.

Stacking denoising auto-encoders in a deep network to segment the brainstem on MRI in brain cancer patients: A clinical study.

Delineation of organs at risk (OARs) is a crucial step in surgical and treatment planning in brain cancer, where precise OARs volume delineation is required. However, this task is still often manually performed, which is time-consuming and prone to observer variability. To tackle these issues a deep learning approach based on stacking denoising auto-encoders has been proposed to segment the brainstem on magnetic resonance images in brain cancer context. Additionally to classical features used in machine learning to segment brain structures, two new features are suggested. Four experts participated in this study by segmenting the brainstem on 9 patients who underwent radiosurgery. Analysis of variance on shape and volume similarity metrics indicated that there were significant differences (p<0.05) between the groups of manual annotations and automatic segmentations. Experimental evaluation also showed an overlapping higher than 90% with respect to the ground truth. These results are comparable, and often higher, to those of the state of the art segmentation methods but with a considerably reduction of the segmentation time.

Assessment of the specificity of a new folate-targeted photosensitizer for peritoneal metastasis of epithelial ovarian cancer to enable intraperitoneal photodynamic therapy. A preclinical study.

BACKGROUND: Ovarian cancer's prognosis remains dire after primary therapy. Recurrence rate is disappointingly high as 60% of women with epithelial ovarian cancer considered in remission will develop recurrent disease within 5 years. Special attention to undetected peritoneal metastasis during surgery is necessary as they are the main predictive factors of recurrences. Folate Receptor α (FRα) shows promising prospects in targeting ovarian cancerous cells and intraperitoneal photodynamic therapy (PDT) could be a solution in addition to macroscopic cytoreductive surgery to treat peritoneal micrometastasis. The aim of this preclinical study is to assess the specificity of a folate-targeted photosensitizer for ovarian peritoneal micrometastasis. METHODS: We used the NuTu-19 epithelial ovarian cancer cell line to induce peritoneal carcinomatosis in female Fischer 344 rats. Three groups of 6 rats were studied (Control (no photosensitizer)/Non-conjugated photosensitizer (Porph)/Folate-conjugated photosensitizer (Porph-s-FA)). Four hours after the administration of the photosensitizer, animals were sacrificed and intraperitoneal organs tissues were sampled. FRα tissue expression was evaluated by immunohistochemistry. Tissue incorporation of photosensitizers was assessed by confocal microscopy and tissue quantification. RESULTS: FRα is overexpressed in tumor, ovary, and liver whereas, peritoneum, colon, small intestine, and kidney do not express it. Cytoplasmic red endocytosis vesicles observed by confocal microscopy are well correlated to FRα tissue expression. Photosensitizer tissue quantification shows a mean tumor-to-normal tissue ratio of 9.6. CONCLUSION: We demonstrated that this new generation folate-targeted photosensitizer is specific of epithelial ovarian peritoneal metastasis and may allow the development of efficient and safe intraperitoneal PDT procedure.

Impact of arterial input function selection on the accuracy of dynamic contrast-enhanced MRI quantitative analysis for the diagnosis of clinically significant prostate cancer.

PURPOSE: Using a limited temporal resolution dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) dataset to assess the impact of the arterial input function (AIF) choice on the transfer constant (K(trans) ) to distinguish prostate carcinoma (PCa) from benign tissue. MATERIALS AND METHODS: Thirty-eight patients with clinically important peripheral PCa (≥0.5 cc) were retrospectively studied. These patients underwent 1.5T multiparametric prostate MR with PCa and benign regions of interest (ROIs) selected using a visual registration with morphometric reconstruction obtained from radical prostatectomy. Using three pharmacokinetic (PK) analysis software programs, the mean K(trans) of ROIs was computed using three AIFs: an individual AIF (Ind-AIF) and two literature population average AIFs of Weinmann (W-AIF) and of Fritz-Hansen (FH-AIF). A pairwise comparison of the area under the receiver operating characteristic curves (AUROCC) obtained with different AIFs was performed. RESULTS: AUROCCs obtained with W-AIF (ranging from 0.801 to 0.843) were significantly higher than FH-AIF (ranging from 0.698 to 0.780, 0.002 ≤ P ≤ 0.045) and similar to or higher than Ind-AIF (ranging from 0.591 to 0.839, 0.014 ≤ P ≤ 0.9). Ind-AIF and FH-AIF provided similar AUROCC (0.34 ≤ P ≤ 0.81). The pairwise correlation of K(trans) values was moderate to very strong when comparing W-AIF with FH-AIF (the Spearman's correlation coefficients [SCCs] ranged from 0.55 to 0.93) and very weak to moderate when comparing W-AIF with Ind-AIF (the SCCs ranged from 0.018 to 0.59) or FH-AIF with Ind-AIF (the SCCs ranged from 0.30 to 0.51). CONCLUSION: W-AIF yielded a higher performance than FH-AIF and a similar or higher performance than Ind-AIF in distinguishing PCa from benign tissue.

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.

Fischer 344 Rat: A Preclinical Model for Epithelial Ovarian Cancer Folate-Targeted Therapy.

OBJECTIVE: Ovarian cancer prognosis remains dire after primary therapy. Recurrence rates are disappointingly high as 60% of women with advanced epithelial ovarian cancer considered in remission will develop recurrent disease within 5 years. Special attention to undetected peritoneal metastasis and residual tumorous cells during surgery is necessary as they are the main predictive factors of recurrences. Folate receptor α (FRα) shows promising prospects in targeting ovarian cancerous cells. Our aim was to determine if the Fischer model described by Rose et al could be used to evaluate folate-targeted therapies in preclinical studies. METHODS: NuTu-19 epithelial ovarian cancer cell line was used to induce peritoneal carcinomatosis in female Fischer 344 rats. FRα expression by NuTu-19 cells was assessed in vitro by immunofluorescence using "Cytospin®" protocol. In vitro folate-targeted compound uptake by NuTu-19 cells was evaluated by incubation of FRα-positive ovarian cancer cell lines (NuTu-19/SKOV-3/OVCAR-3/IGROV-1) with or without (control) a folate-targeted photosensitizer. Intracellular incorporation was assessed by confocal microscopy. Determination of in vivo FRα tissue expression by several organs of the peritoneal cavity was studied by immunohistochemistry. RESULTS: NuTu-19 cells express FRα which allows intracellular incorporation of folate-targeted compound by endocytosis. FRα is expressed in tumor tissue, ovary, and liver. Peritoneum, colon, small intestine, and kidney do not express the receptor. CONCLUSIONS: Female Fischer 344 rat is an inexpensive reproducible and efficient preclinical model to study ovarian peritoneal carcinomatosis folate-targeted therapies.

Comparison of three light doses in the photodynamic treatment of actinic keratosis using mathematical modeling.

Photodynamic therapy (PDT) is an emerging treatment modality for various diseases, especially for cancer therapy. Although high efficacy is demonstrated for PDT using standardized protocols in nonhyperkeratotic actinic keratoses, alternative light doses expected to increase efficiency, to reduce adverse effects or to expand the use of PDT, are still being evaluated and refined. We propose a comparison of the three most common light doses in the treatment of actinic keratosis with 5-aminolevulinic acid PDT through mathematical modeling. The proposed model is based on an iterative procedure that involves determination of the local fluence rate, updating of the local optical properties, and estimation of the local damage induced by the therapy. This model was applied on a simplified skin sample model including an actinic keratosis lesion, with three different light doses (red light dose, 37 J∕cm2, 75 mW∕cm2, 500 s; blue light dose, 10 J∕cm2, 10 mW∕cm2, 1000 s; and daylight dose, 9000 s). Results analysis shows that the three studied light doses, although all efficient, lead to variable local damage. Defining reference damage enables the nonoptimal parameters for the current light doses to be refined and the treatment to be more suitable.

Intrapleural Photodynamic Therapy for Mesothelioma: What Place and Which Future?

In the surgical multimodal management of malignant pleural mesothelioma, it seems crucial to proceed with an efficient local adjuvant treatment to kill residual tumor cells. Intrapleural photodynamic therapy has recently emerged as a potential candidate in this goal. In this review, we analyzed and classified 16 articles in which patients with malignant pleural mesothelioma received intrapleural photodynamic therapy after maximal surgical resection. The toxicity, effect on survival, and development of the technique were assessed. After two decades of clinical studies, intrapleural photodynamic therapy after surgical resection became a safe treatment that significantly improved the survival of patients.

Understanding the pathological implications of MRI: application to focal therapy planning.

PURPOSE OF REVIEW: The current challenge in prostate cancer (PCa) focal therapy indication and planning is how to accurately estimate tumor parameters such as volume, extent and grade. In addition to biopsy results, MRI provides an estimation of PCa contour, volume and histopathological characteristics such as presence of high Gleason grade. Among MRI sequences, diffusion-weighted imaging with apparent diffusion coefficient map is the sequence that showed the best results for cancer aggressiveness characterization. RECENT FINDINGS: It was shown that the higher the Gleason score, the lower the apparent diffusion coefficient value. However, accuracy is not sufficient for peripheral zone cancers to be validated for clinical decision and it was not enough investigated for transition zone cancers. Analysis of tumor extent showed a significant underestimation of tumor volume by imaging and this finding should be taken into consideration when planning focal therapy procedures. SUMMARY: Pathological implications of MRI for focal therapy planning are significant but not mature enough to be validated. Future research should aim to quantify cellularity and architectural patterns of PCa Gleason system in correlation with signal abnormalities for better assessment of tumor aggressiveness and extent, and to compare the boundaries of tumors between MRI and histopathological evaluation in order to define an optimal treatment margin.

Light emitting fabric technologies for photodynamic therapy.

Photodynamic therapy (PDT) is considered to be a promising method for treating various types of cancer. A homogeneous and reproducible illumination during clinical PDT plays a determinant role in preventing under- or over-treatment. The development of flexible light sources would considerably improve the homogeneity of light delivery. The integration of optical fiber into flexible structures could offer an interesting alternative. This paper aims to describe different methods proposed to develop Side Emitting Optical Fibers (SEOF), and how these SEOF can be integrated in a flexible structure to improve light illumination of the skin during PDT. Four main techniques can be described: (i) light blanket integrating side-glowing optical fibers, (ii) light emitting panel composed of SEOF obtained by micro-perforations of the cladding, (iii) embroidery-based light emitting fabric, and (iv) woven-based light emitting fabric. Woven-based light emitting fabrics give the best performances: higher fluence rate, best homogeneity of light delivery, good flexibility.

[FRα: a target for prophylactic photodynamic therapy of ovarian peritoneal metastasis?]. / FRα : une cible pour la thérapie photodynamique prophylactique des métastases péritonéales ovariennes ?

Partly due to delays in its diagnosis, ovarian cancer's prognosis remains dire after primary therapy. Treatment consists in complete cytoreductive surgery and platinum-based chemotherapy. Recurrence rates are disappointingly high, as 60% of women with advanced epithelial ovarian cancer considered in remission will develop recurrent disease within five years. Special attention to undetected peritoneal metastasis and residual tumorous cells during surgery is necessary as they are the main predictors of recurrences. Targeted therapies aim to bring chemotherapy, radiotherapy and selective tumor photosensitizer (PS) agents to the targeted cell and its tumoral microenvironment. Folate receptor α (FRα) shows promising prospects in targeting ovarian cancerous cells. Indeed, with good specificity and frequent overexpression in ovarian cancer, FRα is a recurrent topic in recent publications. The aim of this review is to present FRα and the reasons that make it an ideal targeting ligand for ovarian carcinoma therapy. Prophylactic photodynamic therapy (PPDT) using new generation FRα-coupled agents combined with complete cytoreductive surgery could allow for a significant decrease in recurrence rates. Preclinical trials are being run in order to allow for human clinical applications.

Multiparametric MRI-targeted TRUS prostate biopsies using visual registration.

Prebiopsy multiparametric prostate MRI (mp-MRI), followed by transrectal ultrasound-guided (TRUS-G) target biopsies (TB) of the prostate is a key combination for the diagnosis of clinically significant prostate cancers (CSPCa), to avoid prostate cancer (PCa) overtreatment. Several techniques are available for guiding TB to the suspicious mp-MRI targets, but the simplest, cheapest, and easiest to learn is "cognitive," with visual registration of MRI and TRUS data. This review details the successive steps of the method (target detection, mp-MRI reporting, intermodality fusion, TRUS guidance to target, sampling simulation, sampling, TRUS session reporting, and quality insurance), how to optimize each, and the global indications of mp-MRI-targeted biopsies. We discuss the diagnostic yield of visually-registered TB in comparison with conventional biopsy, and TB performed using other registration methods.

Spectral clustering applied for dynamic contrast-enhanced MR analysis of time-intensity curves.

Dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) represents an emerging method for the prediction of biomarker responses in cancer. However, DCE images remain difficult to analyze and interpret. Although pharmacokinetic approaches, which involve multi-step processes, can provide a general framework for the interpretation of these data, they are still too complex for robust and accurate implementation. Therefore, statistical data analysis techniques were recently suggested as another valid interpretation strategy for DCE-MRI. In this context, we propose a spectral clustering approach for the analysis of DCE-MRI time-intensity signals. This graph theory-based method allows for the grouping of signals after spatial transformation. Subsequently, these data clusters can be labeled following comparison to arterial signals. Here, we have performed experiments with simulated (i.e., generated via pharmacokinetic modeling) and clinical (i.e., obtained from patients scanned during prostate cancer diagnosis) data sets in order to demonstrate the feasibility and applicability of this kind of unsupervised and non-parametric approach.