Neuroimaging for Radiation Therapy of Brain Tumors

The Value of PET/CT in Particle Therapy Planning of Various Tumors with SSTR2 Receptor Expression: Comparative Interobserver Study

The overexpression of somatostatin receptor type 2 (SSTR2) is a property of various tumor types. Hybrid imaging utilizing [68Ga]1,4,7,10-tetraazacyclododecane-1,4,7,10-tetra-acetic acid (DOTA) may improve the differentiation between tumor and healthy tissue. We conducted an experimental study on 47 anonymized patient cases including 30 meningiomas, 12 PitNET and 5 SBPGL. Four independent observers were instructed to contour the macroscopic tumor volume on planning MRI and then reassess their volumes with the additional information from DOTA-PET/CT. The conformity between observers and reference volumes was assessed. In total, 46 cases (97.9%) were DOTA-avid and included in the final analysis. In eight cases, PET/CT additional tumor volume was identified that was not detected by MRI; these PET/CT findings were potentially critical for the treatment plan in four cases. For meningiomas, the interobserver and observer to reference volume conformity indices were higher with PET/CT. For PitNET, the volumes had higher conformity between observers with MRI. With regard to SBGDL, no significant trend towards conformity with the addition of PET/CT information was observed. DOTA PET/CT supports accurate tumor recognition in meningioma and PitNET and is recommended in SSTR2-expressing tumors planned for treatment with highly conformal radiation.

Advances in determining the gross tumor target volume for radiotherapy of brain metastases

Brain metastases (BMs) are the most prevalent intracranial malignant tumors in adults and are the leading cause of mortality attributed to malignant brain diseases. Radiotherapy (RT) plays a critical role in the treatment of BMs, with local RT techniques such as stereotactic radiosurgery (SRS)/stereotactic body radiotherapy (SBRT) showing remarkable therapeutic effectiveness. The precise determination of gross tumor target volume (GTV) is crucial for ensuring the effectiveness of SRS/SBRT. Multimodal imaging techniques such as CT, MRI, and PET are extensively used for the diagnosis of BMs and GTV determination. With the development of functional imaging and artificial intelligence (AI) technology, there are more innovative ways to determine GTV for BMs, which significantly improve the accuracy and efficiency of the determination. This article provides an overview of the progress in GTV determination for RT in BMs.

Alterations in hypothalamic-pituitary axis (HPA) hormones 6 months after cranial radiotherapy in adult patients with primary brain tumors outside the HPA region

BACKGROUND

Cranial radiotherapy is a common treatment for brain tumors, but it can affect the hypothalamic-pituitary (H-P) axis and lead to hormonal disorders. This study aimed to compare serum levels of HPA hormones before and after cranial radiation.

MATERIALS AND METHODS

This study involved 27 adult patients who underwent brain tumor resection before the initiation of radiotherapy, and none had metastatic brain tumors. All participants had the HPA within the radiation field, and their tumors were located in brain areas outside from the HPA. Serum levels of HPA hormones were recorded both before and 6 months after cranial radiotherapy.

RESULTS

A total of 27 adult patients, comprising 16 (59.3%) males and 11 (40.7%) females, with a mean age of 56.37 ± 11.38 years, were subjected to evaluation. Six months post-radiotherapy, serum levels of GH and TSH exhibited a significant decrease. Prior to radiotherapy, a substantial and direct correlation was observed between TSH and FSH (p = 0.005) as well as LH (p = 0.014). Additionally, a significant and direct relationship was noted between serum FSH and LH (p < 0.001) before radiotherapy. After radiotherapy, a significant and direct correlation persisted between TSH and FSH (p = 0.003) as well as LH (p = 0.005), along with a significant and direct relationship between serum FSH and LH (p < 0.001). Furthermore, a significant and direct association was identified between changes in serum GH levels and FSH (p = 0.04), as well as between serum LH and FSH (p < 0.001).

CONCLUSION

Reduced serum levels of HPA hormones are a significant complication of cranial radiotherapy and should be evaluated in follow-up assessments.

Identifying core MRI sequences for reliable automatic brain metastasis segmentation

BACKGROUND

Many automatic approaches to brain tumor segmentation employ multiple magnetic resonance imaging (MRI) sequences. The goal of this project was to compare different combinations of input sequences to determine which MRI sequences are needed for effective automated brain metastasis (BM) segmentation.

METHODS

We analyzed preoperative imaging (T1-weighted sequence ± contrast-enhancement (T1/T1-CE), T2-weighted sequence (T2), and T2 fluid-attenuated inversion recovery (T2-FLAIR) sequence) from 339 patients with BMs from seven centers. A baseline 3D U-Net with all four sequences and six U-Nets with plausible sequence combinations (T1-CE, T1, T2-FLAIR, T1-CE + T2-FLAIR, T1-CE + T1 + T2-FLAIR, T1-CE + T1) were trained on 239 patients from two centers and subsequently tested on an external cohort of 100 patients from five centers.

RESULTS

The model based on T1-CE alone achieved the best segmentation performance for BM segmentation with a median Dice similarity coefficient (DSC) of 0.96. Models trained without T1-CE performed worse (T1-only: DSC = 0.70 and T2-FLAIR-only: DSC = 0.73). For edema segmentation, models that included both T1-CE and T2-FLAIR performed best (DSC = 0.93), while the remaining four models without simultaneous inclusion of these both sequences reached a median DSC of 0.81-0.89.

CONCLUSIONS

A T1-CE-only protocol suffices for the segmentation of BMs. The combination of T1-CE and T2-FLAIR is important for edema segmentation. Missing either T1-CE or T2-FLAIR decreases performance. These findings may improve imaging routines by omitting unnecessary sequences, thus allowing for faster procedures in daily clinical practice while enabling optimal neural network-based target definitions.

Cell-Free miRNAs as Non-Invasive Biomarkers in Brain Tumors

Diagnosing brain tumors, especially malignant variants, such as glioblastoma, medulloblastoma, or brain metastasis, presents a considerable obstacle, while current treatment methods often yield unsatisfactory results. The monitoring of individuals with brain neoplasms becomes burdensome due to the intricate tumor nature and associated risks of tissue biopsies, compounded by the restricted accuracy and sensitivity of presently available non-invasive diagnostic techniques. The uncertainties surrounding diagnosis and the tumor's reaction to treatment can lead to delays in critical determinations that profoundly influence the prognosis of the disease. Consequently, there exists a pressing necessity to formulate and validate dependable, minimally invasive biomarkers that can effectively diagnose and predict brain tumors. Cell-free microRNAs (miRNAs), which remain stable and detectable in human bodily fluids, such as blood and cerebrospinal fluid (CSF), have emerged as potential indicators for a range of ailments, brain tumors included. Numerous investigations have showcased the viability of profiling cell-free miRNA expression in both CSF and blood samples obtained from patients with brain tumors. Distinct miRNAs demonstrate varying expression patterns within CSF and blood. While cell-free microRNAs in the blood exhibit potential in diagnosing, prognosticating, and monitoring treatment across diverse tumor types, they fall short in effectively diagnosing brain tumors. Conversely, the cell-free miRNA profile within CSF demonstrates high potential in delivering precise and specific evaluations of brain tumors.

Concerns in the Blurred Divisions between Medical and Consumer Neurotechnology

Neurotechnology has traditionally been central to the diagnosis and treatment of neurological disorders. While these devices have initially been utilized in clinical and research settings, recent advancements in neurotechnology have yielded devices that are more portable, user-friendly, and less expensive. These improvements allow laypeople to monitor their brain waves and interface their brains with external devices. Such improvements have led to the rise of wearable neurotechnology that is marketed to the consumer. While many of the consumer devices are marketed for innocuous applications, such as use in video games, there is potential for them to be repurposed for medical use. How do we manage neurotechnologies that skirt the line between medical and consumer applications and what can be done to ensure consumer safety? Here, we characterize neurotechnology based on medical and consumer applications and summarize currently marketed uses of consumer-grade wearable headsets. We lay out concerns that may arise due to the similar claims associated with both medical and consumer devices, the possibility of consumer devices being repurposed for medical uses, and the potential for medical uses of neurotechnology to influence commercial markets related to employment and self-enhancement.

Advanced Imaging Techniques for Radiotherapy Planning of Gliomas

The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.

Radiomics in radiation oncology-basics, methods, and limitations

Over the past years, the quantity and complexity of imaging data available for the clinical management of patients with solid tumors has increased substantially. Without the support of methods from the field of artificial intelligence (AI) and machine learning, a complete evaluation of the available image information is hardly feasible in clinical routine. Especially in radiotherapy planning, manual detection and segmentation of lesions is laborious, time consuming, and shows significant variability among observers. Here, AI already offers techniques to support radiation oncologists, whereby ultimately, the productivity and the quality are increased, potentially leading to an improved patient outcome. Besides detection and segmentation of lesions, AI allows the extraction of a vast number of quantitative imaging features from structural or functional imaging data that are typically not accessible by means of human perception. These features can be used alone or in combination with other clinical parameters to generate mathematical models that allow, for example, prediction of the response to radiotherapy. Within the large field of AI, radiomics is the subdiscipline that deals with the extraction of quantitative image features as well as the generation of predictive or prognostic mathematical models. This review gives an overview of the basics, methods, and limitations of radiomics, with a focus on patients with brain tumors treated by radiation therapy.