Compared with intensity-modulated radiotherapy, image-guided radiotherapy reduces severity of acute radiation-induced skin toxicity during radiotherapy in patients with breast cancer

A dosiomics model for prediction of radiation-induced acute skin toxicity in breast cancer patients: machine learning-based study for a closed bore linac

BACKGROUND

Radiation induced acute skin toxicity (AST) is considered as a common side effect of breast radiation therapy. The goal of this study was to design dosiomics-based machine learning (ML) models for prediction of AST, to enable creating optimized treatment plans for high-risk individuals.

METHODS

Dosiomics features extracted using Pyradiomics tool (v3.0.1), along with treatment plan-derived dose volume histograms (DVHs), and patient-specific treatment-related (PTR) data of breast cancer patients were used for modeling. Clinical scoring was done using the Common Terminology Criteria for Adverse Events (CTCAE) V4.0 criteria for skin-specific symptoms. The 52 breast cancer patients were grouped into AST 2 + (CTCAE ≥ 2) and AST 2 - (CTCAE < 2) toxicity grades to facilitate AST modeling. They were randomly divided into training (70%) and testing (30%) cohorts. Multiple prediction models were assessed through multivariate analysis, incorporating different combinations of feature groups (dosiomics, DVH, and PTR) individually and collectively. In total, seven unique combinations, along with seven classification algorithms, were considered after feature selection. The performance of each model was evaluated on the test group using the area under the receiver operating characteristic curve (AUC) and f1-score. Accuracy, precision, and recall of each model were also studied. Statistical analysis involved features differences between AST 2 - and AST 2 + groups and cutoff value calculations.

RESULTS

Results showed that 44% of the patients developed AST 2 + after Tomotherapy. The dosiomics (DOS) model, developed using dosiomics features, exhibited a noteworthy improvement in AUC (up to 0.78), when spatial information is preserved in the dose distribution, compared to DVH features (up to 0.71). Furthermore, a baseline ML model created using only PTR features for comparison with DOS models showed the significance of dosiomics in early AST prediction. By employing the Extra Tree (ET) classifiers, the DOS + DVH + PTR model achieved a statistically significant improved performance in terms of AUC (0.83; 95% CI 0.71-0.90), accuracy (0.70), precision (0.74) and sensitivity (0.72) compared to other models.

CONCLUSIONS

This study confirmed the benefit of dosiomics-based ML in the prediction of AST. However, the combination of dosiomics, DVH, and PTR yields significant improvement in AST prediction. The results of this study provide the opportunity for timely interventions to prevent the occurrence of radiation induced AST.

Predicting acute radiation dermatitis in breast cancer: a prospective cohort study

BACKGROUND

Acute radiation dermatitis (ARD) is one of the most common acute adverse reactions in breast cancer patients during and immediately after radiotherapy. As ARD affects patient quality of life, it is important to conduct individualized risk assessments of patients in order to identify those patients most at risk of developing severe ARD.

METHODS

The data of breast cancer patients who received radiotherapy were prospectively collected and analyzed. Serum ferritin, high-sensitivity C-reactive protein (hs-CRP) levels, and percentages of lymphocyte subsets were measured before radiotherapy. ARD was graded (0-6 grade), according to the Oncology Nursing Society Skin Toxicity Scale. Univariate and multivariate logistic regression analyses were used and the odds ratio (OR) and 95% confidence interval (CI) of each factor were calculated.

RESULTS

This study included 455 breast cancer patients. After radiotherapy, 59.6% and 17.8% of patients developed at least 3 (3+) grade and at least 4 (4+) grade ARD, respectively. Multivariate logistic regression analysis found that body mass index (OR: 1.11, 95% CI: 1.01-1.22), diabetes (OR: 2.70, 95% CI: 1.11-6.60), smoking (OR: 3.04, 95% CI: 1.15-8.02), higher ferritin (OR: 3.31, 95% CI: 1.78-6.17), higher hs-CRP (OR: 1.96, 95% CI: 1.02-3.77), and higher CD3 + T cells (OR: 2.99, 95% CI: 1.10-3.58) were independent risk factors for 4 + grade ARD. Based on these findings, a nomogram model of 4 + grade ARD was further established. The nomogram AUC was 0.80 (95% CI: 0.75-0.86), making it more discriminative than any single factor.

CONCLUSION

BMI, diabetes, smoking history, higher ferritin, higher hs-CRP, and higher CD3 + T cells prior to radiotherapy for breast cancer are all independent risk factors for 4 + grade ARD. The results can provide evidence for clinicians to screen out high-risk patients, take precautions and carefully follow up on these patients before and during radiotherapy.

To Optimize Radiotherapeutic Plans for Superior Tumor Coverage Predicts Malignant Glioma Prognosis and Normal Tissue Complication Probability

Background: Radiotherapy (RT) provides a modern treatment to enhance the malignant glioma control rate. The purpose of our study was to determine the effect of tumor coverage on disease prognosis and to predict optimal RT plans to achieve a lower normal tissue complication probability (NTCP). Methods: Ten malignant-glioma patients with tumors adjacent to organs at risk (OARs) were collected. The patients were divided into two groups according to adequate coverage or not, and prognosis was analyzed. Then, using intensity-modulated radiation therapy (IMRT), volume-modulated arc therapy (VMAT), and helical tomotherapy (TOMO) to simulate new treatment plans for 10 patients, the advantages of these planning systems were revealed for subsequent prediction of NTCP. Results: The results of clinical analysis indicated that overall survival (p = 0.078) between the adequate and inadequate groups showed no differences, while the adequate group had better recurrence-free survival (p = 0.018) and progression-free survival (p = 0.009). TOMO had better CI (p < 0.001) and also predicted a lower total-irradiated dose to the normal brain (p = 0.001) and a lower NTCP (p = 0.027). Conclusions: The TOMO system provided optimal therapeutic planning, reducing NTCP and achieving better coverage. Combined with the clinical results, our findings suggest that TOMO can make malignant glioma patients close to OARs achieve better disease control.

Risk Factors Related to Acute Radiation Dermatitis in Breast Cancer Patients After Radiotherapy: A Systematic Review and Meta-Analysis

Background

Acute radiation dermatitis (ARD) is the most common acute response after adjuvant radiotherapy in breast cancer patients and negatively affects patients’ quality of life. Some studies have reported several risk factors that can predict breast cancer patients who are at a high risk of ARD. This study aimed to identify patient- and treatment-related risk factors associated with ARD.

Methods

PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, and WanFang literature databases were searched for studies exploring the risk factors in breast cancer patients. The pooled effect sizes, relative risks (RRs), and 95% CIs were calculated using the random-effects model. Potential heterogeneity and sensitivity analyses by study design, ARD evaluation scale, and regions were also performed.

Results

A total of 38 studies composed of 15,623 breast cancer patients were included in the analysis. Of the seven available patient-related risk factors, four factors were significantly associated with ARD: body mass index (BMI) ≥25 kg/m² (RR = 1.11, 95% CI = 1.06–1.16, I² = 57.1%), large breast volume (RR = 1.02, 95% CI = 1.01–1.03, I² = 93.2%), smoking habits (RR = 1.70, 95% CI = 1.24–2.34, I² = 50.7%), and diabetes (RR = 2.24, 95% CI = 1.53–3.27, I² = 0%). Of the seven treatment-related risk factors, we found that hypofractionated radiotherapy reduced the risk of ARD in patients with breast cancer compared with that in conventional fractionated radiotherapy (RR = 0.28, 95% CI = 0.19–0.43, I² = 84.5%). Sequential boost and bolus use was significantly associated with ARD (boost, RR = 1.91, 95% CI = 1.34–2.72, I² = 92.5%; bolus, RR = 1.94, 95% CI = 1.82–4.76, I² = 23.8%). However, chemotherapy regimen (RR = 1.17, 95% CI = 0.95–1.45, I² = 57.2%), hormone therapy (RR = 1.35, 95% CI = 0.94–1.93, I² = 77.1%), trastuzumab therapy (RR = 1.56, 95% CI = 0.18–1.76, I² = 91.9%), and nodal irradiation (RR = 1.57, 95% CI = 0.98–2.53, I² = 72.5%) were not correlated with ARD. Sensitivity analysis results showed that BMI was consistently associated with ARD, while smoking, breast volume, and boost administration were associated with ARD depending on study design, country of study, and toxicity evaluation scale used. Hypofractionation was consistently shown as protective. The differences between study design, toxicity evaluation scale, and regions might explain a little of the sources of heterogeneity.

Conclusion

The results of this systematic review and meta-analysis indicated that BMI ≥ 25 kg/m² was a significant predictor of ARD and that hypofractionation was consistently protective. Depending on country of study, study design, and toxicity scale used, breast volume, smoking habit, diabetes, and sequential boost and bolus use were also predictive of ARD.

Impact of CBCT frequency on target coverage and dose to the organs at risk in adjuvant breast cancer radiotherapy

The current study aims to assess the effect of cone beam computed tomography (CBCT) frequency during adjuvant breast cancer radiotherapy with simultaneous integrated boost (SIB) on target volume coverage and dose to the organs at risk (OAR). 50 breast cancer patients receiving either non-hypofractionated or hypofractionated radiotherapy after lumpectomy including a SIB to the tumor bed were selected for this study. All patients were treated in volumetric modulated arc therapy (VMAT) technique and underwent daily CBCT imaging. In order to estimate the delivered dose during the treatment, the applied fraction doses were recalculated on daily CBCT scans and accumulated using deformable image registration. Based on a total of 2440 dose recalculations, dose coverage in the clinical target volumes (CTV) and OAR was compared depending on the CBCT frequency. The estimated delivered dose (V95%) for breast-CTV and SIB-CTV was significantly lower than the planned dose distribution, irrespective of the CBCT-frequency. Between daily CBCT and CBCT on alternate days, no significant dose differences were found regarding V95% for both, breast-CTV and SIB-CTV. Dose distribution in the OAR was similar for both imaging protocols. Weekly CBCT though led to a significant decrease in dose coverage compared to daily CBCT and a small but significant dose increase in most OAR. Daily CBCT imaging might not be necessary to ensure adequate dose coverage in the target volumes while efficiently sparing the OAR during adjuvant breast cancer radiotherapy with SIB.

Compared with intensity-modulated radiotherapy, image-guided radiotherapy reduces severity of acute radiation-induced skin toxicity during radiotherapy in patients with breast cancer

Radiotherapy (RT) is an effective treatment for breast cancer. The side effects of breast irradiation, including skin toxicity in the irradiation field, cause considerable discomfort. This study compared the severity of skin toxicity caused by image-guided RT (IGRT) and intensity-modulated RT (IMRT) combined with an electronic portal imaging device (EPID) in breast cancer. This study retrospectively analyzed 458 patients with breast cancer who had received RT. The patients were divided into two groups: 302 and 156 patients in the IMRT and IGRT groups. In the IGRT group, 8 and 148 patients had received helical tomotherapy irradiation and IMRT with cone-beam computed tomography. Simple and multiple logistic regression analyses were used to estimate the relationship between RT technique and the severity of radiation skin toxicity. In our study, 284, 97, and 6 patients exhibited grades I, II, and III radiation dermatitis (RD). Moreover, 75 patients in the IMRT group (24.80%) and 22 patients in the IGRT group (14.10%) exhibited grade II RD. All patients with grade III RD were in the IMRT group (2.00%). No patient exhibited grade IV RD. The patients in the IGRT group exhibited less severity of RD than in the IMRT group. The severity of acute RD due to IGRT is significantly lower than that due to IMRT with EPID.