The global incidence of brain tumours accounts to be 4.8 and 3.6 per lakh males and females respectively while the excessive Age Standardised Rates (ASR) of incidence (7.9 and 5.9 per Lakh males and females respectively) of brain carcinomas among both the genders was observed among the European population.[1]Metastatic tumours are estimated to occur as much as 10 times more frequently than primary malignant brain tumours. Estimates for the frequency of these tumours vary significantly, but previous studies have reported that they occur in 9–10% of all cancer diagnosis.[2] Multiple factors are found to be responsible for the increased occurrence of the brain metastases. Patients with systemic metastatic diseases are experiencing extended survival rates thanks to the recent adoption of advanced systemic therapies including immunotherapy. Accurate identification of cerebral metastases is crucial for staging, prognosis and determination of appropriate therapy. According to the surgical, radiologic or autopsy information evaluated, the occurrence of metastasis of systemic cancer to the brain vary from 20% to 40%.[3] More commonly, the primary carcinomas which causes brain metastases include, lung, breast, malignant melanoma, renal cell, gastrointestinal tract, uterine and carcinomas of unknown primary.[4]A good resolution data on anatomical location of the tumours can be effortlessly provided by the conventional imaging like CT and MRI unfortunately lacking functional information.[5] With latest advancesin the stream of radiology such as nuclear scintigraphy, PET and other nuclear imaging studies are inclined tofurnish dataon metabolic activity of the tumour under evaluation though carrying drawbacks such as poor anatomical localisation and low spatial resolution. The invention of PET-CT fusion imaging, reforming the drawbacks provides data consolidating anatomical and functional details with outstanding spatial resolution and clear cut anatomical localisation.[5] PET-CT involves inoculation of a radioactive isotope to the patient and studying. The tumour cells are identified as areas with larger uptake of the radioisotope (hot – spots) as the radioisotope heaps-up inside the tissues with greater metabolic activity. The PET metabolic data integrated with CT anatomical/morphologic data assistsin better localisation of the tumour. PET-CT also plays a significant role in detecting and localising metastases.[6] The most commonly used radioisotope in present day practice in PET-CT is 18F-FDG [18F-labeled fluoro-2-deoxyglucose]. 18F-FDG PET helps in identifying the malignant tumour and its metastatic deposits by their raised glucose consumption feature. Different parameters are utilized in measuring the metabolic activity of the tumour by PET-CT while the commonest parameter is a semi-quantitative measurement the SUV max[maximum standardised uptake value] with high reproducibility and has been recommended for primary evaluation of malignancy and treatment follow-up.[7,8]With this background, this study focused to establish the correlation between metabolic activity (SUV max) of the metastatic brain lesion and various prognostic factors like histological subtype of the primary tumour and imaging characteristics which can enable us to predict the prognosis of the patient and assist in the management.

Study setting: The study was conducted in the department of Radiodiagnosis in a tertiary care hospital in Chennai, Tamil Nadu. Study period: The study was conducted from October 2018 to September 2020 for a period of 2 years. Study design: Hospital-based observational retrospective design was used for this present study. Study participants: All eligible patients who were referred for whole body PET-CT scan for diagnosis and also for staging of primary carcinoma with brain metastasis. Sample size: During the study period,about 78 patients came to the department of Radiodiagnosis for whole body PET-CT scan for diagnosis and for staging of primary carcinoma with brain metastasis and sample size was taken as 78 in the study. Sampling: Consecutive sampling method was used for recruiting the study participants in the study. Inclusion criteria: • Patients with metastatic brain tumors who came to the department of Radiodiagnosis for whole body PET-CT scan. Exclusion criteria: • Plasma glucose level above the threshold [200mg/dl (~ 11.1 mmol /L)]. • Pregnant/ Breastfeeding patients. • Claustrophobic patients. Equipment used: Siemens Biograph Horizon TRUE V PET/CT (120). Softwareused: syngo.via version VB30A (120). Radiotracer Used: 18F-Flurodeoxyglucose [Dose: 5-10 mCi]. Contrast Media Used: Iohexol [Trade name -Omnipaque 350 mg/dL] [dose -1.5 mg/kg] Procedure: In this study, patient's clinical history was obtained and routine screening done. Informed written consent was obtained from every participant. After overnight fasting [at least 4 to 6 hours], patients changed into appropriate robes and adequate oral hydration was advised. Blood glucose level were measured and recorded before injection of the radiotracer. Appropriate radiotracer dose was taken, recorded and injected intravenously and the time of injection was also recorded. Then, the patient was allowed to rest quietly for 45-60 minutes in a shielded room for allowing FDG uptake into the tissues. Patients were later made to rest in supine or recumbent position to reduce the FDG uptake in muscles. Acquisition parameters: PET and CT Patient positioning: Patients are made to lie down flat in supine position with patient orientation of Head first with their arms above their head. Low dose scanogram / scout image obtained for planning of FOV. The routine field of coverage for PET and CT was from Vertex to Mid-thigh. Low dose whole body CT scan done with in-built 16-slice CT scanner, with acquisition of 5 mm slices after intravenous contrast administration with shallow or tidal breathing. CT scan acquisition was done routinely in venous phase. Study can be individually tailored to include plain [non-contrast], arterial, venous and/or delayed phases as required. Acquired CT data can be reconstructed to 1.5 mm slice images. A suspended-inspiration thoracic CT was acquired with high-resolution lung algorithm. Whole body CT data was acquired in soft tissue window, which can be reformatted for viewing in multiple windowing presents like bone and brain windows. Routine time taken for CT acquisition was approximately 1 to 2 minutes. PET counts acquisition is done in 6 to 7 beds of ~20cm length each, exposure time for each bed lasting for ~1 minute. Detector sensitivity was 7.6 cps/kBq @435 keV and the PET resolution was 4.2 mm. Routine time taken for PET counts acquisition was 7-8 minutes and the total time taken for total study was approximately 20 minutes. The PET –CT image fusion is done by the software package [syngo.via] in Siemens PET-CT workstation. CT component is used for precise anatomic localization and attenuation correction. PET-CT fusion images are rendered by the syngo.via software. CT images, PET grayscale counts and PET-CT fusion images are available for viewing after multiplanar reconstruction [MPR] in 3 planes –Axial, coronal and sagittal planes. For measuring the FDG uptake of the lesion, Region of Interest (ROI) iso-contour was drawn to include the entire lesion. ROI varies for each lesion, such that the system automatically delineates the entire lesion in 3-dimensional plane. Then the system calculates and displays the maximum SUV value of the lesion under consideration. SUVmaxvalue of the metastatic deposits was also calculated using the same procedure. In case of multiple metastatic deposits, the lesion with the highest SUVmax was taken as representative lesion. In cases of equivocal lesions under doubt, if the SUVmax of lesion is greater than the SUVmax of the mediastinal blood pool, that lesion is considered as metastatic lesion, provided that there is no alternative explanation for the lesion. Metastatic Lesions with SUVmax> 4.5 were considered hypermetabolic in reference to the surrounding white matter of the brain.

Majority of the study participants were elderly comprising of 43.6%. Around 6.4% of the tumour patients were below 30 years of age. Gender distribution was almost equal in the present study with females (54%) slightly higher than males (46%). Most participants had the primary tumour at lungs (53.8%) followed by breast (26.9%). Around 5.1% of the primary tumours were of unknown in origin. With regards to the histological types of the primary tumour, adenocarcinoma (25.6%) and invasive mammary carcinoma (25.6%) were the most common type present in the primary tumour. (Table:1) The maximum number of cases had the metastatic brain lesions in the frontoparietal lobes (61.5%) as shown in Table:2 and 44.5% of the brain metastasis were present in the parietal lobes followed by cerebellum (29.5%). Around 41% of the patients had one metastasis whereas, 9% of the participants were more than five metastases. There were other metastatic sites (extra-cranial) present simultaneously of which, half of them were present in adrenal, liver and bone. About 43.6% of the tumor patients had peripheral enhancing as the CT morphology of brain metastasis, followed by solid enhancing (38.5%) and cystic lesion (17.9%). The maximum standardized uptake value (SUV max) of brain metastasis has been divided into FDG Avid (SUV max value of  4.5) and non FDG Avid (SUV max  4.5). Most FDG avid were seen in solid enhancing type of lesion and majority of the non FDG avid were seen in the peripheral enhancing type of lesion. There was an association between the SUV max of brain metastasis and the CT morphology the brain metastasis with p < 0.05, (Table:3). Table: 4 show a significant association between the SUV max of the brain metastasis and the primary site of carcinoma. More FDG uptake was seen in the brainmetastasis which had lungs as the primary site. Non FDG avid was also common in lung primary followed by breast. There was no significant association between SUV max metastasis score and Histopathological Examination of Carcinoma as evident by the p value (table:5). Table: 1 Baseline characteristics of the study participants (n=78): Characteristics Category Number (n) Percentage (%) 1. Age Below 30 30-40 41-50 51-60 Above 60 5 10 15 14 34 6.4 12.8 19.2 17.9 43.6 2. Gender Male Female 36 42 46 54 3. Site of primary tumour Breast GIT Lung MSK Renal Unknown 21 5 42 5 1 4 26.9 6.4 53.8 6.4 1.3 5.1 4. Histological types of primary a. Lungs Adenocarcinoma Squamous cell carcinoma. High Grade spindle cell sarcoma Unknown HPE 20 1 1 20 25.64 1.28 1.28 25.64 b. Breast Invasive mammary carcinoma Unknown HPE 20 1 25.64 1.28 c. GIT Colon - Adenocarcinoma Rectum – Adenocarcinoma Oesophagus - Adenocarcinoma Small Bowel – Carcinoid 1 1 1 2 1.28 1.28 1.28 2.56 d. MSK PNET Synovial sarcoma Chondrosarcoma Pleomorphic sarcoma Malignant Melanoma 1 1 1 1 1 1.28 1.28 1.28 1.28 1.28 e. Renal 1 1.28 f. Unknown primary 4 5.13 Table: 2 Distribution of the tumour in brain metastasis (n=78) S.No Characteristics Number (n) Percentage (%) 1. CT morphology of the tumour: Cystic Peripheral enhancing Solid enhancing 14 34 30 17.9 43.6 38.5 2. Location of brain metastasis: Frontal Parietal Temporal Occipital Cerebellum Ganglio capsular Brain stem Multiple (3 or more) 48 35 6 11 23 3 3 28 61.5 44.9 7.7 14.1 29.5 3.8 3.8 35.9 3. Number of metastatic lesion 1 2 3 4 >5 32 19 11 9 7 41.0 24.4 14.1 11.5 9.0 4. Sites of extracranial metastasis Liver Lung Bone Adrenal Kidney GIT Breast Muscle 38 17 38 43 6 3 2 9 48.7 21.8 48.7 55.1 7.7 3.8 2.56 11.5 Table 3: Association between SUV max metastasis and CT Morphology of carcinoma. Characteristics n (%) with Carcinoma (78) x2 p value Cystic (14) Peripheral Enhancing (34) Solid Enhancing (30) SUV max metastasis ≥ 4.5 (FDG Avid) < 4.5 (Non FDG Avid) 1 (7.1%) 13 (92.9%) 18 (52.9%) 16 (47.1%) 22 (73.3%) 8 (26.7%) 16.78 0.000* *p<0.05 statistically significant, Chi-square test. Table 4: Association between SUV max metastasis and primary site of carcinoma Characteristics n (%) with Carcinoma (78) x2 p value Breast (21) GIT (5) Lung (42) MSK (5) Renal (1) Unknown (4) SUV max metastasis ≥ 4.5 (FDG Avid) < 4.5 (Non FDG Avid) 6 (28.6%) 15 (71.4%) 3 (60%) 2 (40%) 25 (59.5%) 17 (40.5%) 3 (60%) 2 (40%) 0 (0%) 1 (100%) 4 (100%) 0 (0%) 10.29 0.037* *p<0.05 statistically significant. There was a significant association between SUV max metastasis score and primary site of carcinoma as evident by the p value which was less than 0.05. Table 5: Association betweenHPE of Carcinoma and SUV max metastasis. Characteristics SUV max metastasis (N= 78) x2 p value ≥ 4.5 (FDG Avid) (41) < 4.5 (Non FDG Avid) (37) HPE of Carcinoma Adenocarcinoma Carcinoid Chondrosarcoma High grade spindle cell sarcoma Infiltrating mammary carcinoma Invasive mammary carcinoma Malignant melanoma Pleomorphic sarcoma PNET Squamous cell carcinoma Synovial sarcoma Unknown HPE 12 (29.3%) 2 (4.9%) 1 (2.4%) 1 (2.4%) 0 (0%) 6 (14.6%) 1 (2.4%) 0 (0%) 1 (2.4%) 1 (2.4%) 0 (0%) 16 (39%) 11 (29.7%) 0 (0%) 0 (0%) 0 (0%) 1 (2.7%) 13 (35.1%) 0 (0%) 1 (2.7%) 0 (0%) 0 (0%) 1 (2.7%) 10 (27%) 12.88 0.123 There was no significant association between HPE of Carcinoma and SUV max metastasis score as evident by the p value which was less than 0.05.

Brain metastasis is one of the common malignant brain tumours. Accurate pre-therapeutic diagnosis and prognostication of the disease is needed for appropriate selection of treatment regimen. Although CT and MRI examinations have facilitated the diagnosis of brain tumours, there is often uncertainty with metastatic or primary brain tumours. In addition, when CT or MR images suggest the presence of a metastatic brain tumour, several kinds of diagnostic work-up is performed for systemic evaluation. These include chest radiography; mammography; abdominal sonography; bone scanning; chest, abdominal, and pelvic CT; and bone marrow examination. However, these procedures are time-consuming and costly, and many usually prove unnecessary. A more simple and efficient diagnostic tool that can investigate systemic status safely and reliably is needed. PET-CT is a non-invasive imaging modality that can assess the morphologic and metabolic characteristics of tumours. Several studies across the world have established the usefulness of PET-CT in identification and characterization of brain metastasis. The FDG uptake in PET-CT can be calculated by using various semi-quantitative parameters like SUVmax, SUVmean and SUVpeak. Out of these parameters, SUVmax is the most commonly used in clinical practice due to its reproducibility and standard performance in various studies for evaluation of cancer patients. In our study, SUVmax was calculated and taken as a measure of metabolic activity of the metastatic brain lesion and primary tumours. This measured metabolic activity of the metastatic brain lesion was correlated with the metabolic activity of the primary tumour and its histological type. The results obtained in our study were comparable to the results of many previously published studies. In our retrospective analysis including 78 patients who presented with brain metastasis, the lung was the most common primary site. However, there were other primary sites in several patients in this group, like the breast cancer, skin cancer and renal cell cancer. Similar observations were made in previous studies such as bronchogenic carcinoma being the most common primary tumour leading to brain metastasis followed by breast carcinoma and renal cell carcinoma.[9 – 12] Out of the 43 cases of primary lung carcinomas with brain metastasis, 21 cases were of adenocarcinoma, 1 case was of squamous cell carcinoma and 1 case of spindle cell carcinoma histology. This was found to be in accordance with previous studies which showed adenocarcinoma is the most common histologic subtype led to brain metastasis.[9, 13] The locations of the metastatic brain lesions were more commonly found at fronto-parietal lobes (61.5%) followed by the parietal lobes (44.5%) and the cerebellum (29.5%) in the present study. While in comparison with the findings of a recent systematic review (2022) distribution of brain metastases were found to be inconsistently at infratentorial areas, particularly the cerebellum, parietal, frontal lobes, the occipital and temporallobes may be because of different subtypes of lung cancers studied.[14] The enhancement pattern of the metastatic lesion noticed in our study was peripheral enhancing (43.6%) followed by solid enhancing (38.5%) and cystic lesion (17.9%). Whereas, previous studies have reported marginal, ring, intralesional enhancement, patchy areas of no enhancement and no radiotracer uptake due to necrosis, calcifications or haemorrhages and on examining the ring enhancements, they were more commonly frequented with gliomas (40%) followed by the brain metastases (30%).[9,15] Out of the total 78 cases, 37 cases were non FDG avid (SUVmax ≤ 4.5) and 41 cases were FDG avid (SUVmax>4.5). In our study, there is a significant correlation between the CT imaging characteristics of metastatic brain lesions and its metabolic activity on PET- CT with p value of 0.000 whereas, in a meta-analysis done by Li Y et al has observed that contrast enhanced MRI has higher sensitivity than FDG PET (77% vs 21%) for the diagnosis of brain metastasis secondary to lung cancer.[16]

PET–CT is a helpful non-invasive imaging modality in detecting primary in patients with metastatic brain lesion. The 18F-FDG PET/CT study may help detect malignant brain lesions and, therefore, including brain region imaging into the study protocol should be considered.

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