Jacek Fijuth

Background/Purpose: Pelvic nodal irradiation (PNI) can cause radiation-induced lymphopenia (RIL) in prostate cancer patients, yet PNI decisions rely on disease features without bone marrow vulnerability assessment. We tested whether sacral bone geometry on planning CT predicts grade ≥2 RIL independently of PNI and age.Methods: Radiation planning CTs from 260 consecutive VMAT-treated prostate cancer patients at a single institution were analyzed. TotalSegmentator v2 was used to segment pelvic bones and PyRadiomics was used to extract 14 sacral shape features. Associations with RIL were tested with Bonferroni correction. Cross-validated (5-fold × 20 repeats) AUC analyses were used to compare nested logistic models.Results: The cohort included 260 patients (median age 70); 82 (32%) received PNI. Grade ≥2 lymphopenia occurred in 120 patients (46.2%), with grade ≥3 in 48 (18.5%). Sacral flatness was associated with lymphopenia (OR 1.82/SD, 95% CI 1.31–2.53, p<0.001), improving cross-validated AUC from 0.757 to 0.825 over age and PNI. Sacral flatness was uncorrelated with all sacral DVH metrics (|r|<0.03), platelet or hemoglobin levels, muscle volume, or ADT status. Among 10 pelvic bones, only sacral flatness was significantly associated with lymphopenia. Stratification by sacral flatness tertile and PNI yielded lymphopenia rates from 23% to 97%. Decision curve analysis showed net benefit for lymphopenia prediction across thresholds 6–95%. Grade ≥2 lymphopenia was associated with worse OS (adjusted HR 2.69, 95% CI 1.34–5.42; RMST difference 2.5 months at 3 years).Conclusions: Available from planning CT before plan generation, sacral bone flatness is a pre-treatment anatomical marker of bone marrow vulnerability that predicts RIL independently of radiation dose, ADT use, and body composition. This automated biomarker warrants investigation for immune-sparing planning when PNI is indicated.

Purpose: To evaluate the impact of PSMA PET versus conventional imaging for staging, and the effect of dose escalation (DE) to metastatic lymph nodes in cN1 prostate cancer patients treated with EBRT and ADT. Methods: A retrospective multicenter analysis included 197 propensity score-matched patients (77 staged with PSMA PET, 120 with conventional imaging) treated with EBRT and ADT, with or without DE to lymph node metastases. Matching criteria were T stage, nodal involvement, imaging modality, Gleason score, and ADT duration. Primary endpoint was metastasis-free survival (MFS); secondary endpoints included overall survival (OS), locoregional control (LRC), and toxicity. Results: Median follow-up was 42 months (IQR: 25–59). Median EQD2 (alpha/beta=1.5) to elective nodes was 46 Gy, and to metastatic nodes, 66 Gy (PSMA PET) and 63 Gy (conventional imaging). The 3-year MFS was 80.5% (95% CI: 71.3–90.8%) for PSMA PET and 77.2% (95% CI: 69.5–85.8%) for conventional imaging; 5-year MFS was 59.3% versus 65.8% ( P =0.57). OS at 5 years was 82.2% (PSMA PET) and 77.4% (conventional imaging) ( P =0.72). On multivariable analysis, ISUP grade group 3–5 predicted earlier metastasis (HR: 4.03, 95% CI: 1.61–10.06; P =0.003); higher prostate dose (EQD2 ≥113 Gy) improved MFS (HR: 0.53, 95% CI: 0.30–0.95; P =0.033); long-term ADT (≥24 mo) improved OS (HR: 0.38, 95% CI: 0.19–0.78; P =0.009). No significant difference in toxicity was observed between groups. Conclusions: PSMA PET staging and nodal dose escalation >60 Gy were safe but did not improve MFS, OS, or LRC. ISUP grade group 3–5 and higher prostate dose significantly influenced outcomes.

The 2021 WHO glioma classification integrates molecular profiling, but outcome data for these patients are limited. We retrospectively analyzed 179 patients (median age 53) with WHO 2021-classified gliomas (grade 2: n = 45, grade 3: n = 51, grade 4: n = 83) treated with surgery and radio(chemo)therapy across four centers in Poland and France. Chemotherapy was administered to 74.9% of patients, with a median radiotherapy dose of 60 Gy (range 32.5–80 Gy). IDH1/2 mutations were identified in 55.3% and 1p/19q codeletion in 22.4%. Patients with IDH1/2 mutations had significantly longer progression-free survival (PFS, 7.7 vs. 1.0 years) and overall survival (OS, 8.2 vs. 2.5 years), both p < 0.01. 1p/19q codeletion was associated with prolonged PFS (7.7 vs. 1.6 years, p < 0.01). In grade 3 gliomas, chemotherapy improved PFS (6.8 vs. 3.6 years) and OS (6.9 vs. 3.9 years), both p < 0.01. Leukopenia grade 0–2 correlated with better PFS (3.6 vs. 1.2 years, p = 0.02) and OS (7.2 vs. 3.2 years, p = 0.04). Absolute lymphocyte count ≤ 1×10³/mm³ predicted worse OS (5.3 vs. 8.7 years, p = 0.0043). CTV < 127 cm³ predicted longer OS in grade 4 gliomas (3.2 vs. 1.7 years, p = 0.012). Our findings provide new real-world evidence on survival and prognostic factors in this population, for which contemporary RWE and OS/PFS data remain scarce.

Background: Primary glioblastoma is characterized by an extremely poor prognosis. The promoter methylation of GATA4 leads to the loss of its expression in many cancer types. The formation of high-grade astrocytomas can be promoted by the concurrent loss of TP53 and GATA4 in normal human astrocytes. Nevertheless, the impact of GATA4 alterations with linkage to TP53 changes in gliomagenesis is poorly understood. This study aimed to evaluate GATA4 protein expression, GATA4 promoter methylation, p53 expression, TP53 promoter methylation, and mutation status in patients with primary glioblastoma and to assess the possible prognostic impact of these alterations on overall survival. Materials and Methods: Thirty-one patients with primary glioblastoma were included. GATA4 and p53 expressions were determined immunohistochemically, and GATA4 and TP53 promoter methylations were analyzed via methylation-specific PCR. TP53 mutations were investigated via Sanger sequencing. Results: The prognostic value of GATA4 depends on p53 expression. Patients without GATA4 protein expression were more frequently negative for TP53 mutations and had better prognoses than the GATA4 positive patients. In patients positive for GATA4 protein expression, p53 expression was associated with the worst outcome. However, in patients positive for p53 expression, the loss of GATA4 protein expression seemed to be associated with improved prognosis. GATA4 promoter methylation was not associated with a lack of GATA4 protein expression. Conclusions: Our data indicate that there is a possibility that GATA4 could function as a prognostic factor in glioblastoma patients, but in connection with p53 expression. A lack of GATA4 expression is not dependent on GATA4 promoter methylation. GATA4 alone has no influence on survival time in glioblastoma patients.

The optimal sequence of chemoradiotherapy with immunotherapy is still not established. The patient’s immune status may play a role in determining this order. We aim to determine the kinetics of a multi-potential haemopoietic factor FMS-related tyrosine kinase 3 ligand (Flt-3L) during chemoradiotherapy. Our pilot, a single arm prospective study, enrolled patients with rectal cancer who qualified for neoadjuvant chemoradiotherapy. Blood samples for Flt-3L were collected before and every second week of chemoradiotherapy for a complete blood count every week. The kinetics of Flt-3L were assessed using Friedman’s ANOVA. A multiple factor analysis (MFA) was performed to find relevant factors affecting levels of serum Flt-3L during chemoradiotherapy. FactoMineR and factoextra R packages were used for analysis. In the 33 patients enrolled, the level of Flt-3L increased from the second week and remained elevated until the end of treatment (p < 0.01). All patients experienced Grade ≥2 lymphopenia with a nadir detected mostly in the 5/6th week. MFA revealed the spatial partitioning of patients among the first and second dimensions (explained by 38.49% and 23.14% variance). The distribution along these dimensions represents the magnitude of early changes of Flt-3L. Patients with the lowest values of Flt-3L change showed the highest lymphocyte nadirs and lowest dose/volume parameters of active bone marrow. Our hypothesis-generating study supports the concept of early initiation of immuno-therapy when the concentration of Flt-3L is high and no lymphopenia has yet occurred.

State-of-art normal tissue complication probability (NTCP) models do not take into account more complex individual anatomical variations, which can be objectively quantitated and compared in radiomic analysis. The goal of this project was development of radiomic NTCP model for radiation-induced hypothyroidism (RIHT) using imaging biomarkers (radiomics). We gathered CT images and clinical data from 98 patients, who underwent intensity-modulated radiation therapy (IMRT) for head and neck cancers with a planned total dose of 70.0 Gy (33–35 fractions). During the 28-month (median) follow-up 27 patients (28%) developed RIHT. For each patient, we extracted 1316 radiomic features from original and transformed images using manually contoured thyroid masks. Creating models based on clinical, radiomic features or a combination thereof, we considered 3 variants of data preprocessing. Based on their performance metrics (sensitivity, specificity), we picked best models for each variant ((0.8, 0.96), (0.9, 0.93), (0.9, 0.89) variant-wise) and compared them with external NTCP models ((0.82, 0.88), (0.82, 0.88), (0.76, 0.91)). We showed that radiomic-based models did not outperform state-of-art NTCP models (p > 0.05). The potential benefit of radiomic-based approach is that it is dose-independent, and models can be used prior to treatment planning allowing faster selection of susceptible population.

State-of-art normal tissue complication probability (NTCP) models do not take into account more complex individual anatomical variations, which can be objectively quantitated and compared in radiomic analysis. The goal of this project was development of radiomic NTCP model for radiation-induced hypothyroidism (RIHT) using imaging biomarkers (radiomics). We gathered CT images and clinical data from 98 patients, who underwent intensity-modulated radiation therapy (IMRT) for head and neck cancers with a planned total dose of 70.0 Gy (33–35 fractions). During the 28-month (median) follow-up 27 patients (28%) developed RIHT. For each patient, we extracted 1316 radiomic features from original and transformed images using manually contoured thyroid masks. Creating models based on clinical, radiomic features or a combination thereof, we considered 3 variants of data preprocessing. Based on their performance metrics (sensitivity, specificity), we picked best models for each variant ((0.8, 0.96), (0.9, 0.93), (0.9, 0.89) variant-wise) and compared them with external NTCP models ((0.82, 0.88), (0.82, 0.88), (0.76, 0.91)). Our models reach accuracy comparable with or better than previously presented non-radiomic NTCP models. The benefit of our approach is obtaining the RIHT predictions before treatment planning to adjust IMRT plan to avoid the thyroid region in most susceptible patients.

Background: Due to the rarity of osteosarcoma and limited indications for radiotherapy (RT), data on RT for this tumor are scarce. This study aimed to investigate the utilization of RT for osteosarcomas in the recent 20 years and to identify factors related to patients’ response to radiation. Methods: We performed a retrospective analysis of patients irradiated for osteosarcoma treatment. We planned to assess differences in the utilization of RT between the periods of 2000–2010 and 2011–2020, identify the risk factors associated with local progression (LP), determine whether RT-related parameters are associated with LP, and calculate patients’ survival. Results: A total of 126 patients with osteosarcoma who received 181 RT treatments were identified. We found a difference in RT techniques between RT performed in the years 2000–2010 and that performed in the years 2011–2020. LP was observed after 37 (20.4%) RT treatments. Intent of RT, distant metastases, and concomitant systemic treatment affected the risk of LP. Five-year overall survival was 33% (95% confidence interval (26%–43%)). Conclusions: RT for osteosarcoma treatment has evolved from simple two-dimensional palliative irradiation into more conformal RT applied for new indications including oligometastatic and oligoprogressive disease. RT may be a valuable treatment modality for selected patients with osteosarcoma.

We aimed to externally validate five normal tissue complication probability (NTCP) models for radiation-induced hypothyroidism (RIHT) in a prospectively recruited cohort of 108 patients with oropharyngeal cancer (OPC). NTCP scores were calculated using original published formulas. Plasma thyrotropin (TSH) level was additionally assessed in the short-term after RT. After a median of 28 months of follow-up, thirty one (28.7%) patients developed RIHT. Thyroid mean dose and thyroid volume were significant predictors of RIHT: odds ratio equal to 1.11 (95% CI 1.03–1.19) for mean thyroid dose and 0.87 (95%CI 0.81–0.93) for thyroid volume in univariate analyses. Two of the evaluated NTCP models, published by Rønjom et al. and by Boomsma et al., had satisfactory performance with accuracies of 0.87 (95%CI 0.79–0.93) and 0.84 (95%CI: 0.76–0.91), respectively. Three remaining models, by Cella et al., Bakhshandeh et al. and Vogelius et al., performed significantly worse, overestimating the risk of RIHT in this patient cohort. A short-term TSH level change relative to baseline was not indicative of RIHT development in the follow-up (OR 0.96, 95%CI: 0.65–1.42, p = 0.825). In conclusion, the models by Rønjom et al. and by Boomsma et al. demonstrated external validity and feasibility for long-term prediction of RIHT in survivors of OPC treated with Intensity-Modulated Radiation Therapy (IMRT).