Normo- or Hypo-Fractionated Photon or Proton Radiotherapy in the Management of Locally Advanced Unresectable Pancreatic Cancer: A Systematic Review.

LAPC is associated with a poor prognosis and requires a multimodal treatment approach. However, the role of radiation therapy in LAPC treatment remains controversial. This systematic review aimed to explore the role of proton and photon therapy, with varying radiation techniques and fractionation, in treatment outcomes and their respective toxicity profiles. METHODS: Clinical studies published from 2012 to 2022 were systematically reviewed using PubMed, MEDLINE (via PubMed) and Cochrane databases. Different radiotherapy-related data were extracted and analyzed. RESULTS: A total of 31 studies matched the inclusion criteria. Acute toxicity was less remarkable in stereotactic body radiotherapy (SBRT) compared to conventionally fractionated radiotherapy (CFRT), while in proton beam therapy (PBT) grade 3 or higher acute toxicity was observed more commonly with doses of 67.5 Gy (RBE) or higher. Late toxicity was not reported in most studies; therefore, comparison between groups was not possible. The range of median overall survival (OS) for the CFRT and SBRT groups was 9.3-22.9 months and 8.5-20 months, respectively. For the PBT group, the range of median OS was 18.4-22.3 months. CONCLUSION: CFRT and SBRT showed comparable survival outcomes with a more favorable acute toxicity profile for SBRT. PBT is a promising new treatment modality; however, additional clinical studies are needed to support its efficacy and safety.

Analysis of MRI and CT-based radiomics features for personalized treatment in locally advanced rectal cancer and external validation of published radiomics models.

Radiomics analyses commonly apply imaging features of different complexity for the prediction of the endpoint of interest. However, the prognostic value of each feature class is generally unclear. Furthermore, many radiomics models lack independent external validation that is decisive for their clinical application. Therefore, in this manuscript we present two complementary studies. In our modelling study, we developed and validated different radiomics signatures for outcome prediction after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) based on computed tomography (CT) and T2-weighted (T2w) magnetic resonance (MR) imaging datasets of 4 independent institutions (training: 122, validation 68 patients). We compared different feature classes extracted from the gross tumour volume for the prognosis of tumour response and freedom from distant metastases (FFDM): morphological and first order (MFO) features, second order texture (SOT) features, and Laplacian of Gaussian (LoG) transformed intensity features. Analyses were performed for CT and MRI separately and combined. Model performance was assessed by the area under the curve (AUC) and the concordance index (CI) for tumour response and FFDM, respectively. Overall, intensity features of LoG transformed CT and MR imaging combined with clinical T stage (cT) showed the best performance for tumour response prediction, while SOT features showed good performance for FFDM in independent validation (AUC = 0.70, CI = 0.69). In our external validation study, we aimed to validate previously published radiomics signatures on our multicentre cohort. We identified relevant publications on comparable patient datasets through a literature search and applied the reported radiomics models to our dataset. Only one of the identified studies could be validated, indicating an overall lack of reproducibility and the need of further standardization of radiomics before clinical application.

Re-irradiation of recurrent gliomas: pooled analysis and validation of an established prognostic score-report of the Radiation Oncology Group (ROG) of the German Cancer Consortium (DKTK).

The heterogeneity of high-grade glioma recurrences remains an ongoing challenge for the interdisciplinary neurooncology team. Response to re-irradiation (re-RT) is heterogeneous, and survival data depend on prognostic factors such as tumor volume, primary histology, age, the possibility of reresection, or time between primary diagnosis and initial RT and re-RT. In the present pooled analysis, we gathered data from radiooncology centers of the DKTK Consortium and used it to validate the established prognostic score by Combs et al. and its modification by Kessel et al. Data consisted of a large independent, multicenter cohort of 565 high-grade glioma patients treated with re-RT from 1997 to 2016 and a median dose of 36 Gy. Primary RT was between 1986 and 2015 with a median dose of 60 Gy. Median age was 54 years; median follow-up was 7.1 months. Median OS after re-RT was 7.5, 9.5, and 13.8 months for WHO IV, III, and I/II gliomas, respectively. All six prognostic factors were tested for their significance on OS. Aside from the time from primary RT to re-RT (P = 0.074) and the reresection status (P = 0.101), all factors (primary histology, age, KPS, and tumor volume) were significant. Both the original and new score showed a highly significant influence on survival with P < 0.001. Both prognostic scores successfully predict survival after re-RT and can easily be applied in the routine clinical workflow. Now, further prognostic features need to be found to even improve treatment decisions regarding neurooncological interventions for recurrent glioma patients.

Independent validation of a new reirradiation risk score (RRRS) for glioma patients predicting post-recurrence survival: A multicenter DKTK/ROG analysis.

BACKGROUND AND PURPOSE: Reirradiation (reRT) is a valid option with considerable efficacy in patients with recurrent high-grade glioma, but it is still not known which patients might be optimal candidates for a second course of irradiation. This study validated a newly developed prognostic score independently in an external patient cohort. MATERIAL AND METHODS: The reRT risk score (RRRS) is based on a linear combination of initial histology, clinical performance status, and age derived from a multivariable model of 353 patients. This score can predict post-recurrence survival (PRS) after reRT. The validation dataset consisted of 212 patients. RESULTS: The RRRS differentiates three prognostic groups. Discrimination and calibration were maintained in the validation group. Median PRS times in the development cohort for the good/intermediate/poor risk categories were 14.2, 9.1, and 5.3 months, respectively. The respective groups within the validation cohort displayed median PRS times of 13.8, 8.8, and 3.8 months, respectively. Uno's C for development data was 0.64 (CI: 0.60-0.69) and for validation data 0.63 (CI: 0.58-0.68). CONCLUSIONS: The RRRS has been successfully validated in an independent patient cohort. This linear combination of three easily determined clinicopathological factors allows for a reliable classification of patients and may be used as stratification factor for future trials.

Non-linear imaging and characterization of atherosclerotic arterial tissue using combined SHG and FLIM microscopy.

Atherosclerosis is one of the leading causes of death in the Western World and its characterization is extremely interesting from the diagnostic point of view. Here, we employed combined SHG-FLIM microscopy to characterize arterial tissue with atherosclerosis. The shorter mean fluorescence lifetime measured within plaque depositions (1260 ± 80 ps) with respect to normal arterial wall (1480 ± 100 ps) allowed discriminating collagen from lipids. SHG measurements and image analysis demonstrated that the normal arterial wall has a more anisotropic Aspect Ratio (0.37 ± 0.02) with respect to plaque depositions (0.61 ± 0.02) and that the correlation length can be used for discriminating collagen fibre bundles (2.0 ± 0.6 µm) from cholesterol depositions (4.1 ± 0.6 µm). The presented method has the potential to find place in a clinical setting as well as to be applied in vivo in the near future. Graphic composition of SHG and FLIM images representing normal arterial wall and plaque depositions.

Characterization of collagen and cholesterol deposition in atherosclerotic arterial tissue using non-linear microscopy.

Atherosclerosis is characterized by the accumulation of lipids within the arterial wall and is commonly diagnosed using standard histology. Non-linear microscopy represents a possible label-free alternative to standard diagnostic methods for imaging various tissue components. Here we employ SHG and CARS microscopy for imaging thin cross-sections of atherosclerotic arterial tissue, demonstrating that both cholesterol deposition in the lumen and collagen in the normal arterial wall can be imaged and discriminated using SHG and CARS microscopy. A simultaneous detection of both forward and backward scattered SHG signals allows distinguishing collagen fibres from cholesterol. Further analysis, based on image pattern evaluation algorithms, is used to characterize collagen organization in the healthy arterial wall against collagen found within plaques. Different values of fibre mean size, distribution and anisotropy are calculated for lumen and media prospectively allowing for automated classification of atherosclerotic lesions. The presented method represents a promising diagnostic tool for evaluating atherosclerotic tissue.

Characterization of atherosclerotic plaque depositions by Raman and FTIR imaging.

Spectroscopy-based imaging techniques can provide useful biochemical information about tissue samples. Here, we employ Raman and Fourier transform infrared (IR) imaging to characterize composition and constitution of atherosclerotic plaques of rabbits, fed with a high cholesterol diet. The results were compared with conventional light microscopy after staining with hematoxylin eosin, and elastica van Gieson. The spectral unmixing algorithm vertex component analysis was applied for data analysis and image reconstruction. IR microscopy allowed for differentiation between lipids and proteins in plaques of full aortic cross sections. Raman microscopy further discriminated cholesterol esters, cholesterol and triglycerides. FTIR and Raman images were recorded at a resolution near 20 micrometer per pixel for a large field of view. High resolution Raman images at 1 micrometer per pixel revealed structural details at selected regions of interest. The intima-media and the lipid-protein ratio were determined in five specimens for quantitation. These results correlate well with histopathology. The described method is a promising tool for easy and fast molecular imaging of atherosclerosis.

In vivo characterization of atherosclerotic plaque depositions by Raman-probe spectroscopy and in vitro coherent anti-stokes Raman scattering microscopic imaging on a rabbit model.

Visualization as well as characterization of inner arterial plaque depositions is of vital diagnostic interest, especially for the early recognition of vulnerable plaques. Established clinical techniques provide valuable visual information but cannot deliver information about the chemical composition of individual plaques. Here, we employ Raman-probe spectroscopy to characterize the plaque compositions of arterial walls on a rabbit model in vivo, using a miniaturized filtered probe with one excitation and 12 collection fibers integrated in a 1 mm sleeve. Rabbits were treated with a cholesterol-enriched diet. The methodology can improve the efficiency of animal experiments and shows great potential for applications in cardiovascular research. In order to further characterize the plaque depositions visually, coherent anti-Stokes Raman scattering (CARS) microscopy images have been acquired and are compared with the Raman-probe results.