Radiation induced lung damage - Chapter 2 Irradiation of the lung: dose-volume effects

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Radiation induced lung damage

Seppenwoolde, Y.

Publication date

2002

Link to publication

Citation for published version (APA):

Seppenwoolde, Y. (2002). Radiation induced lung damage.

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Chapterr 2

Irradiationn of the lung:

dose-volumee effects

Yvettee Seppenvwootde, Joos V. Lebesque

Irradiationn of the lung: dose-volume effects

Manyy factors like fractionation, overall treatment time and patient specific aspects are importantt when studying and quantifying the effects of partial king irradiation. The tocat reactionss of lung tissue to irradiation are ascribed with reg^ to the dcee-volume effect Differentt models that are used to predict the incidence of radiation pneumonitis and the influencee of irradiation on the overal king function are discussed. The easy-to-cafcuiate meann king dose (MLD) and the volume irradiated with more than 20 Gy (V20) can both hee used to predict the incidence of radiation pneumonitis. These parameters represent twoo extremes m underfying local dose-effect r e t a t i ^

dinteaflyy applied treatment plane show a high «jrrelatton between the V20 and trie MLD, soo that the decision for the 'bes? underlying ioeaf dose-effect relation should be based on tiletile analysis of additional patient data. Dose-escalation studies and multi-center co-operationn wffl create more possibflities to investigate all confounding factors concerning lungg irradiation.

Introduction n

Locall failure is a major cause for thé disappointing cure rate of patiënte with inoperable noh-smal!! cell lung cancer (NSCLC) treated with radiotherapy. In a study of Martel et al. (1999), basedd on Tumor control probability (TCP) model calculations, ft was found that the dose to achievee a significant probability of tumor control rnay be targ^ (in the ordered 84 Gy) for longer (>> 30 months) local progression-free survival. However, the maximum safe radiation dose that cann be delivered to most thoracic tumors is limited by the tolerance of lung tissue.

Generally,, the radiation response in lung is divided into two distinct phases; early radiation effectss (radiation pneumonitis) become manifest between 1 and 8 months after radiotherapy. Thee clinical symptoms of radiation pneumonitis range from mild symptoms such as fever, dyspneaa and cough to death from respiratory failure. Late effects develop in some patients fromm 6 months after treatment onwards (Marks 1994). Consequently, both a recovery from the earlyy inflammatory response and a development of fibrosis may be observed between 3 and 188 months. In the early phase, inflammatory cells and interstitial and alveolar exudates are absorbedd and the epithelium and the microvasculature reverts to normal (Roswit 1977). The processs of fibrosis is characterized by a progressive thickening of the alveolar septa and vessell walls with bundles of elastic fibers and collagen, and consequently decreases local and overalll lung function. The fibrosis phase remains constant from a little over a year to 10 years followw up in a study of Skoczytas et al. (2000). Clinically, radiation pneumonitis mostly precedess fibrosis, but both processes can develop independently and may show variation in degreee and extent of the radiation response.

Besidess radiation pneumonitis and radiation fibrosis, reduction in pulmonary function is reportedd following radiotherapy for breast cancer, malignant lymphoma and lung cancer as earlyy as 4-8 weeks after radiotherapy. Generally, a decrease of lung volumes in ail compartmentss is measured, which is maximal 6-9 months after irradiation. At about the same time,, gas exchange abnormalities occur which are more or (ess proportional to the decrease inn lung volumes. Thereafter, some recovery in pulmonary function is reported, although this is onlyy minimal for the diffusion capacity, indicating true diffusion problems.

Duee to these pulmonary side effects, the total dose that can safely be delivered to the thorax iss limited and therefore tumor control is hampered. The majority of patiënte with NSCLC have marginall lung function already before radiotherapy due to pre-existent pulmonary disease. Patientss with chronic obstructive pulmonary disease (COPD) are more likely to have emphysemaa with a lower CT-density throughout the lungs, and their lung perfusion is inhorhogeneous.. Some patients suffer from bullous disease and have lung regions where locallyy the density is very low. These bullous regions are neither well ventilated nor perfused. Furthermore,, the ventilation and perfusion can be obstructed by atelectasis, infiltrates or tumor.. For these patients it is important to take into account every single factor that could limit radiationn damage to the remaining (healthy) lung tissue, while in the mean time the tumor is adequatelyy irradiated. During the last years, the use of 3D conformal radiotherapy has increased,, resulting in smaller field sizes and better tumor coverage. However, to optimize the treatmentt plans and escalate the dose, It is essential to know the relation between the 3D treatmentt plan and complications.

Pulmonaryy damage, general aspects

Thee probability and the severity of radiation-induced lung damage mainly depend on the radiationn dose, the amount of the irradiated volume and the fractionation schedule. Van Dyk ett al. (1981) made the first attempt to relate the incidence of radiation pneumonitis (as defined byy clinical symptoms and characteristic radiographic changes) to the absolute dose in the lung afterr total lung irradiation. They observed a steep dose-response relation that rose from 5% to 50%% complication probability with an increase of the (single) dose from 8.2 to 9.3 Gy.

Fractionationn and overall treatment time

Whenn multiple fractions are given, an impressive sparing effect of fractionation is seen; no casess of pneumonitis were reported among 110 patients who received 15 to 25 Gy in fractions off 1.5 and 1.75 Gy to both lungs (Newton 1969, Rab 1976, Breur 1978, Van Dyk 1981). To enablee comparison of clinical studies with different fractionation schedules, several methods cann be used that convert the different radiotherapy schedules to a single equivalent dose or specifiedd level of effect Currently the Linear-Quadratic (LQ) cell survival model is used. Fractionationn sensitivity is quantified by the ot/B ratio of the parameters of the LQ model. Bentzenn et al. (2000) concluded from a literature review that the cc/B ratio for normal lung tissue iss low, possibly 2-3 Gy. The physical dose-distribution of a radiation treatment plan is such that locallyy different doses per fraction occur. To take this dose per fraction into account, the physicall dose distribution can be converted into the biologically equivalent dose distribution givenn in fractions of 2 Gy, resulting in the Normalized Total Dose (NTD) distribution, by using thee LQ model (Mactejewskt 1986). A linear time component can be incorporated when the overalll treatment time of the fractionation schedules differs from conventional treatment scheduless (Van Dyk 1990). Two studies (Van Dyk 1989, Dubray 1995) tested for an effect of overalll treatment time and found that tilts was not statistically significant. Therefore, the use of thee LQ model with no time factor at all is probably the best strategy in clinical practice (Bentzen 2000). .

Chemo-- and hormonal therapy

Whenn cytotoxic drugs are combined with other potentially lung-toxic agents, such as radiation, ann enhancement of pulmonary side effects may be observed. In animal studies, cyclophosphamide,, bleomycin and adriamycin were found to enhance radiation-induced lung

IrradiationIrradiation of the kmg: dose-vobme effects

damagee (Collis 1983). In general, the radiation-modifying effect is more pronounced when chemotherapyy is administered concurrently with radiation than if time is allowed to elapse betweenn exposure to each modality (von der Maase 1986). No interaction was observed when thee time-interval between chemotherapy and radiotherapy was longer than 28 days.

AA number of clinical reports (Hrafhkelsson 1987) have indicated an increase in radiation pneumonitiss and fibrosis when chemotherapy and radiotherapy were given concomitantly to patientss with Hodgkin's disease, kmg cancer and breast cancer (Lagrange 1988). No consistentt differences were observed between irradiated patients receiving and not receiving additionall chemotherapy (MOPP and MOPP/ABVD) (Allavena 1992). Morgan et al. (1985) reportedd a lower diffusion capacity for patients treated with MOPP chemotherapy and irradiationn compared to those with radiotherapy atone. Excessive pulmonary toxicity was describedd in series with ABVD chemotherapy and radiotherapy (Brice 1991).

Thee most adverse chemotherapy-radiation interactions appear to arise from the ongoing clinicall breast cancer trials using high dose chemotherapy with autologous bone marrow rescue,, followed by radiotherapy (Marks 1992). For breast cancer patients treated with radiotherapyy combined with less aggressive chemotherapy such as CMF, severe pulmonary toxicityy is rarety noticed (Hardman 1994). For hormonal regiments the results are contradicting.. Theuws et al. (1998b) did not find an influence of tamoxifen on lung function. Bentzen,, however, found an increase of the incidence of (ate radiological lung changes in the irradiatedd apex of the lungs (Bentzen 1996).

Smoking g

Cigarettee smoke containing nicotine and carbon monoxide, has been reported to decrease the diffusionn capacity in smokers due to pulmonary vasoconstriction (Knudson 1989, Sansores 1992).. There are also some indications that smoking may "protect" both tumor (Siemann 1978, Bjermerr 1990) and normal lung tissue (Franzen 1989, Bjermer 1992, 1993, Theuws 1998b) fromm acute radiation effects. The exact mechanism of this effect is not known, but it is suggestedd mat smoking may suppress the local inflammatory reaction in the lung. In a Danish studiee (Jensen 1990), reduced lung function was reported in smokers with respect to non-smokers,, 8 years after radiotherapy.

Age e

Variouss results have been published concerning the impact of age on radiation-induced pulmonaryy changes. Jensen et al. (1990) reported that young patients treated for Hodgkin's diseasee had a more pronounced restrictive lung function 8 years after treatment than older patients.. Hardman et al. (1994), found no association between age and pulmonary damage. Forr radiation pneumonitis however, the risk increases considerably with age (Gagliardt 2000).

Cytokines s

Apartt from the factors mentioned above, individual variability in sensitivity to cytotoxic therapy suchh as radiotherapy and chemotherapy may play a rote as welt. It has been suggested that transformingg growth factor beta (TGF-&), known to pfay an important role in the development off excessive fibrosis, may be useful in predicting an individual patient's risk for developing normall tissue injury (Anscher 1998). This was first reported in breast cancer patients treated withh high-dose chemotherapy and autologous bone marrow transplantation. Anscher et al. (1998)) reported an association between the changes in TGF-R levels and radiation pneumonitis.. Normalisation of the plasma TGF-G level during thoracic radiotherapy for lung cancerr appeared to be useful for identifying patients not at risk for thee development of radiation pneumonitis.. Results from a pilot study with a limited number of patients from Vujaskovic and

Groenn (2000) suggest that elevated TGF-ft levels during radiotherapy may not only identify patientss with a higher risk of developing pulmonary toxicity but also patients with a higher risk off treatment failure.

Locall effects of lung irradiation

Too determine the effect of lung irradiation, the local damage to lung tissue can be measured withh 3D imaging techniques. Changes in lung density can be measured by comparison of follow-upp CT scans with the CT scan made before treatment. Density changes visible on CT aree caused by an inflammatory reaction of the lung tissue (early response) and fibrosis that generallyy develops later.

Mahh et al. (1987, 1994) conducted a study to obtain a dose-response curve for CT density changes.. An increase of more than 5% in lung density in the high dose region was scored as damage.. They found a probit-like dose-incidence curve with a D ^ of 35.7 Gy (NTD). When the fulll 3D dose-distribution of the applied treatment plan is known, the average local damage in eachh dose-interval can be calculated, leading to a local dose-effect relation for lung density changes.. These effect relations cannot in a simple way be compared with dose-incidencee curves. Dose-incidence curves represent the probability to develop a certain amount off damage and the steepness of the dose-incidence curve represents the inter-patient variance.. Dose-effect relations quantify the average amount of damage in each dose-interval. Forr malignant lymphoma, breast- and lung cancer patients, the dose-effect relation for lung densityy changes is shown in Figure 1 (dotted line).

400 60 Dosee (Gy)

FigureFigure 1. The dose-effect data for perfusion changes for 81 breast cancer and lymphoma patients (triangles) and the

wellwell perfused regions of 25 lung cancer patients (squares) in the Netherlands Cancer Institute (NKI, Chapter 3) and the datadata of Duke University (Garipagaoglu 1999) (solid circles), consisting of fifty patients (32 lung cancer, 7 lymphoma, 9 breastbreast cancer and 2 other thoracic tumors). The data could well be described with a logistic function with a Dso of 63 GyGy and a steepness parameter kof 1.7 (soTid line). The dashed line represents the dose^ffect relatbn for CT density changeschanges in the patients of the Netherlands Cancer Institute.

IrradiationIrradiation of the lung: dose-volume effects

AA similar analysis was performed for changes in lung perfusion and ventilation due to radiotherapy.. Three-dimensional perfusion and ventilation scans are obtained by single photon emissionn computed tomography (SPECT) lung perfusion/ventilation imaging. The images can bee matched to the pre-treatment CT scan by means of chamfer matching (Kwa 1998b) or by hand.. To correct for attenuation, a post-reconstruction correction method incorporating a variable-effectivee linear-attenuation coefficient calculated from the spatially correlated CT data wass developed (Damen 1994a). The resolution of the gamma camera used for SPECT is not ideal,, causing blurring of the perfusion/ventilation patterns. This means that perfusion defects thatt are small and sharply outlined cannot be quantified correctly, leading to an underestimationn of the dose-effect in the higher dose-bins (Garipagaoglu 1999). The same appliess for scatter in the patient. However, as long as dose-gradients are shallow and irradiatedd fields are rather large, scatter and blurring will not influence dose-effect relations in thee lower dose bins and only minimally affect the higher dose-bins.

Forr each volume element in the lung the effect of the treatment can be calculated by comparingg the pre-and post-treatment normalized SPECT-values. The dose-effect relations thuss obtained were found to be similar for patients with healthy lungs before treatment (malignantt lymphoma and breast cancer patients) and for the well-perfused lung regions of patientss with NSCLC (Boersma 1994, Marks 1997b). The dose-effect curve for perfusion is almostt linear but can also be described by a logistic function with a Dso of 63 Gy and a steepnesss parameter k of 1.7. The data of the Netherlands Cancer Institute are in accordance withh the data of Duke University (Figure 1). The dose-effect relations for perfusion and ventilationn (the latter not shown) demonstrate a similar, almost linear dose-dependent increase off early pulmonary damage, whereas the dose-effect relation for lung density changes is different,, suggesting the existence of two different biological endpoints, i.e. functional and structurall damage.

Forr lung cancer patients the presence of tumor can result in locally reduced perfusion before treatment.. Tumor regression during treatment can cause reperfusion in some cases. Reperfusionn will have an effect on the measured dose-effect relation. As an example, local reperfusionn can be visualized by correcting the post-treatment perfusion pattern for the dose-effectt (Figure 2).

A.. Pre-RT B. Post-RT C. Post-RT perfusion D.

Dose-perfusionn perfusion corrected for irradiation distribution

FigureFigure 2. Perfusion patterns of a patient with lung cancer. In black the GTVand the king contours are indicated. A. Pre-treatment pattern.pattern. B. Post- treatment pattern. C. Post-treatment pattern corrected for the dose-effect relation as shown in Figure 1. D. Dose-distribution.Dose-distribution. The region posterior of the tumor is better perfused after treatment than before, despite the fact that a high dosedose is applied in this region.

Overalll effects of lung irradiation

Radiationn pneumonitis, data and models

Thee amount of irradiated volume and radiation dose have an effect on radiation-induced lung injury.. It is important to be able to estimate the severity and probability of developing radiation pneumonitiss for an individual patient. Severe radiation pneumonitis during the first 6 months afterr irradiation may be life threatening. In patients who survive this pneumonitis phase, the typee and severity of the early response may have bearing on the type and severity of the ensuingg late response. The severity of radiation pneumonitis can be scored according to prescribedd criteria, for example according to the SWOG criteria where a grade 1 radiation pneumonitiss is scored when radiological changes are observed but the symptoms do not requiree steroids. Grade 2 is scored when steroids are required. For grade 3 oxygen is needed andd for grade 4 assisted ventilation is required.

Severall theoretical models have been developed to estimate the risk of radiation pneumonitis basedd on the 3D dose distribution. These models should describe the clinical data with sufficientt accuracy. Clinical data on the relation between the 3D dose distribution and the probabilityy of developing radiation pneumonitis were sparse when these models and parameterr values were published. In the following section the clinical data collected since then willl be discussed with respect to the different models.

Thee Lyman mode)

Inn 1991, Emami et al. (1991) estimated that a homogeneous dose of 17.5 Gy given to the wholee lung, or 30 Gy given to 2/3 Of the lung, or 40 Gy given to 1/3 of the lung would result in 5%% probability on a complication within 5 years. For a 50% complication probability these figuress were 24.5 Gy, 40 Gy, and 65 Gy respectively. These doses were not corrected for tissuee inhomogeneities. Subsequently, Burman et al. (1991) applied the model of Lyman (1985)) to these estimations, resulting in parameter values for TD» of 24.5 Gy, a steepness parameterr m of 0.18, and a volume exponent n of 0.87. For an inhomogeneous dose distribution,, the Dose Volume Histogram (DVH) has to be reduced into a single step DVH. This iss usually done according to Kutcher and Burman (1989) using a power-law relationship betweenn tolerance dose and irradiated volume and the same volume exponent n. The group off Michigan (Mattel 1994) discussed that the TO» value should be corrected to 28 Gy. to accountt for tissue heterogeneity. Using this value, they observed a good correlation between thee calculated Normal Tissue Complication Probability (NTCP) and the observed incidence of radiationn pneumonitis in lymphoma patients treated with mantie field irradiation. However, for lungg cancer patients, thé correlation was weak (Martel 1994). Marks et al. (1997a) reported similarr findings: a reasonable correlation was observed between the observed incidence of pneumonitiss and the NTCP (calculated with a TD» of 29.5 Gy) in a study of 100 patients. However,, in the subgroup of the 67 lung cancer patients the correlation was weak, but when patientss with a poor pulmonary function prior to radiotherapy were excluded, the correlation improvedd considerably. In the 60 lung cancer patients studied by Graham et al. (Graham 1994) alsoo a weak correlation between the calculated NTCP (using a TDM of 26 Gy) and the observedd incidence of radiation pneumonitis was observed. Oetzel et al. (1995), found a good correlationn in a patient group irradiated for lung and esophageal cancer, using the original valuee for TD» of 24.5 Gy. However, apart from differences in the value of TDso there are other differencess between these studies. In the study of Martel et al. (1994) the best correlation was observedd when the lungs were considered to be a paired organ, whereas Oetzel et al. (1995)

IrradiationIrradiation of the lung: dose-volume effects

foundfound the best results when the lungs were considered as independent separate organs. Furthermoree Martel ét al. and Oetzel et al. scored any grade of radiation pneumonitis as a complication,, whereas Graham et at. only considered severe complications (2: grade 3) as a complication.. Finally, Oetzel et at. converted the dose in each voxel to the Normalized Total Dose,, whereas the other groups only used the physical dose.

Thee relative serially model

Gagliardii et at. (2000) characterized the dose-response curve for radiation pneumonitis (grade 11 and higher) following radiotherapy for 68 breast cancer patients. The NTCP model in this studyy was the relative seriality model (Kallman 1992) with parameter values Dso, a steepness parameterr y and a seriality parameter s, which represents the functional seriality of the organ: forr a parallel organs like kidney or lungs s will be dose to zero, for a serial organ like the spinal cordd s is equal to one. The seriality model assumes Poisson statistics to describe cell survival andd the organization of normal tissue in substructures responsible for the organ function. They foundd a D& of 30.1 Gy, a 7 of 0.97 and a relative seriality factor of 0.01, which indicates a strongg parallel behavior of lung tissue. In this study the lungs were considered as separate organs. .

Thee critical volume model

Ass in the relative seriality model, this model is based on the concept of functional subunits (FSUs)) defined either structurally or functionally, and an assumption that normal tissue complicationn probability is fully determined by the number or fraction of surviving FSUs in that organn or tissue (Jackson 1993, Yorke 1993, Niemierko 1993). One can use a sigmoidal function,, characterized by a D50 and a steepness parameter k as the underlying local dose-effectt relation. This sigmoid function represents the FSU-kHI due to locally applied dose. If the dose-effectt relation for perfusion represents the dose-effect relation for FSU-kMI, the average reductionn of local perfusion over the whole lung can be calculated (analogue to the fraction of FSUss killed). A strong correlation was observed between the average reduction in perfusion andd the incidence of radiation pneumonitis (Kwa 1998c). However, the limited number of patientss and the low incidence of pneumonitis in this study did hot allow a reliable comparison withh the other NTCP models.

WinCimm |MiBiinun«

Apartt from fitting the data to the theoretical models, Graham et al. (Graham 1999) investigated whetherr a straightforward parameter as the percentage of the total lung volume that received moree titan 20 Gy was related to the incidence of radiation pneumonitis, for 99 patients irradiatedd for lung cancer (Figure 3A). Univariate analysis revealed the percent of the total lungg volume exceeding 20 Gy (V20), the effective volume (V^, which is the volume that, irradiatedd homogeneously with the prescribed dose, gives the same NTCP as the inhomogeneouss dose-distribution (Ten Haken 1993)) and the mean King dose, and location of thee primary tumor (upper versus tower lobes) to be correlated with the development of a Grade 22 pneumonitis. Multivariate analysis revealed the V20 to be the most significant predictor of radiationn pneumonitis. Simitar findings were reported by Marks et al. (1997a) for the lung volumee receiving more than 30 Gy. Armstrong et al. (1997) found a higher incidence of grade 33 radiation pneumonitis for patients with more than 30% of their lungs irradiated with more than 255 Gy compared to patients with a smaller V25.

Anotherr rather straightforward parameter as the mean dose seems to be correlated with the incidencee of pneumonitis as well. In the study of Martel et al. (1994), the mean lung dose in thee 5 lymphoma patients with complications was 26.1 Gy, whereas the mean dose in the 16

lymphomaa patients without complications was 21 Gy. For the 9 lung cancer patients with complicationss and the 33 patients without complications these figures were 24 Gy and 18 Gy, respectively.. These differences were even larger when the lungs were considered to be independentt separate organs (30 Gy vs 21.3 Gy, and 34.2 Gy vs 18.2 Gy, respectively). In the studyy of Oetzel et al. (1995) these differences were somewhat smaller: the mean physical lung dosee in the 37 lung cancer patients without complications was 20.1 Gy, whereas this figure wass 23.8 Gy for the 9 patients with pneumonitis.

100 20 30 A.. V20 (%)

100 20 B.. Mean lung dose (Gy)

FigureFigure 3. A. The incidence of radiation pneumonitis (grade >2) as a function of the volume receiving more than

2020 Gy for 99 lung cancer patients (Graham 1999). B. The incidence of radiation pneumonitis (grade >2)asa function ofof mean (bbtogical) lung dose. The data of 540 patients from 5 institutions were pooled (Kwa 1998a). The error bars representrepresent the 68% confidence intervals. The fit parameters were TDsr30.5 Gy, and m=0.30.

Inn a large multi-center study (Kwa 1998a), 540 patients were pooled to study the dose-incidencee curve for radiation pneumonitis. Three-dimensional dose calculations were performedd with the same type of inhomogeneity correction (equivalent-path-length method in 44 of the 5 centers). Dose-volume histograms were calculated for the lungs as one organ, from whichh the mean (biological) lung dose, MLD, was obtained. Radiation pneumonitis was scored whenn a complication grade 2 (SWOG) or higher occurred. The mean lung dose, MLD, ranged fromm 0 Gy to 34 Gy and 73 of the 540 patients experienced pneumonitis. In all centers, an increasingg pneumonitis rate was observed with increasing MLD. Between the lung groups of differentt institutes, significant differences were present. Accounting for these differences by addingg center dependent offset values for lung cancer patients, the data was fitted with an TD50=30.5+1.44 Gy and 2 1 SE) for all patients, and an offset of 0-11% for the

lungg group, depending on the center. In Figure 3B the dose-incidence curve for radiation pneumonitiss is shown, corrected for the center-dependent offset. The MLD, which is relatively easyy to calculate, can be used to predict the risk of radiation pneumonitis, grade > 2. About halff of the complications grade > 2 were complications grade > 3 in all dose-bins.

ComparisonComparison ofDVH reduction techniques and simple parameters using the critical volume model

Theree are differences and similarities of the different parameters that are predictive for radiationn pneumonitis. In Figure 4A these parameters are shown, based on a DVH of a lung cancerr patient: the cumulative DVH is plotted with the V20 and the V30, (which are easily derivedd from the DVH), the mean lung dose and the equivalent uniform doses. The equivalent

IrradiationIrradiation of the lung: dose-volume effects

uniformm dose (EUD) has a more general definition than the definition used by Niemierko (1997). .

Wee defined the EUD as the equivalent dose which, according to the underlying theoretical model,, when given as a uniform dose to the entire organ would produce the same NTCP as thee original inhomogeneous dose distribution. Therefore, this EUD is not yet uniquely defined ass it still depends on the underlying theoretical model. All the parameters in Figure 4A can be obtainedd by reducing the DVH to a single step-DVH using an underlying local dose-effect relationn representing dose-dependent local damage or FSU kill. When the MLD is used as a

100% % 80% % ffi ffi ii 60%

I I

40% % 20% % 0% % -- Cumulalive DVH MLDD = 236y V200 = 44% __ _ V30 = 30% EUDD <n=0.25) = 44 Gy EUD(D500 = 45Gy.k=2.5) = 27Gy

V V

: : ii ^ i i i i A A 100% % '' Linear (Power-taw n=1) Stepp (V20) -- — Step(V30) Power-toww (n=0.25) Sigmoidd (D50=45 Gy, k=2.5> 200 40 60 Dosee (Gy) 80 0 40 0 Dosee (Gy)

FigureFigure 4. A. The cumulative DVH of a king cancer patient with the V20 and the V30, (which are easily derived from the

DVH),DVH), the mean king dose, the equivalent uniform dose based on the KutcherDVH reduction scheme (EUD^,^ and basedbased on a local sigmoid dose-effect relation (EUD3^. B. Different dose^ffect relations that are used to derive the singlesingle parameters in Figure 4A, which are predictive for radiation pneumonitis.

predictorr for radiation pneumonitis, a linear dose-response for the underlying local damage is assumed,, while for the V20 and V30 a step-function is taken as the local dose-response curve. Inn the Kutcher DVH reduction scheme, a power-law relation, (characterized by n) between the locall dose and the effect is assumed (Kwa 1998c), resulting in an EUDpo^ertaw or EUDLKB (Appendixx I, equation 7), which is the same as the D ^ defined by Mohan (1992), D ^ accordingg to Damen (1994b) and the EUD defined by Niemierko (1999). The underlying dose-effectt relations are shown in Figure 4B. When n=1 in the Kutcher model, the E U D , » ^ ^ will bee equal to the MLD (Kwa 1998c). If a sigmoid logistic expression (characterized with a D^ andd a k) for the local dose-effect relation is used, an EUDsigri,0|d can be calculated as well

(Appendixx I, equation 12). When the dose-effect relation for FSU-kill is linear (which is almost thee case when perfusion data is used, Figure 1), the EUD-ag^c will be equal to the mean lung dose. .

Alll the models can thus be compared using the EUDmodel. From the step-dose-effect relations

Reductionn in overall lung function; dose-volume parameters

Sincee the mean lung dose can be used to predict the average reduction in perfusion over the completee lung, Theuws et al. (1998b) investigated whether this parameter could be used to predictt the reduction in overall lung function. For 81 patients (41 lymphoma patients and 40 breastt cancer patients) the correlation coefficients were calculated between the mean lung dosee and the change in overall lung function parameters, measured prior to radiotherapy and 3-44 months after therapy (Figure 5). The correlation coefficients between the mean lung dose andd the reduction of the Alveolar Volume (VA), Vital Capacity (VC), Forced Expiratory Volume

inn 1 second (FEV,) and Transfer Factor for Carbon Monoxide (TLiCOc), were 0.73, 0.70, 0.69

andd 0.58 respectively. 50 0 40 0

>'1 1

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30 0 20 0

22 1

TOTO u _

22 2

S S II 10 -10 0 -20 0 3 months 18 months Is? ? I I ^ è è

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10 0 15 5 20 0 25 5 30 0

Meann lung dose (Gy)

FigureFigure 5. Comparison of the mean relative changes in VA SEM, 3 and 18 months after radbtherapy for 110 breast

cancercancer and and malignant lymphoma patients as a function of the mean lung dose. The plotted lines represent the dose-dependentdependent reduction in VA at 3 months (0.9% per Gy) and 18 months (0.4% per Gy).

Thee relation between the mean lung dose and the reduction in overall lung function parameterss could be described with one regression line through the origin and a slope of % reductionn in overall lung function for each increase of 1 Gy in mean lung dose. For patients treatedd with MOPP/ABV chemotherapy prior to radiotherapy, the overall lung function was

7-12%% lower prior to the start of radiotherapy than for patients without treatment before radiotherapy.. CMF chemotherapy given after radiotherapy caused an additional decrease in TL.COCC of 6% which should be added to the estimated radiation-induced reduction of TLCOc- The

groupp from the Duke University (Marks 1997a), investigated whether the reduction in FEV-, andd TL C O c was correlated with the lung volume irradiated to > 30 Gy or with the estimated

NTCPP values for lung cancer patients. In a study of 100 patients only a poor correlation was foundd between these parameters. However, when patients with a poor pulmonary function priorr to therapy were excluded, the correlation improved.

Irradiator}Irradiator} of the lung: dose-volume effects

Recoveryy of radiation induced pulmonary damage

Severall studies have been performed to evaluate the effects of radiotherapy on lung tissue overr time. Pulmonary function tests (VA, VC, FEV^ and TL,Coc). SPECT perfusion and

ventilationn scans and CT scans were made before, 3,18, and 48 months after radiotherapy for 1100 patients treated for breast cancer or malignant lymphoma (Boersma 1996). Dose-effect relationss for changes in local perfusion, ventilation, and lung tissue density were determined forr each individual patient for each follow-up period. Average dose-effect relations for both subgroupss were determined, as well as dose-effect relations for different regions. In general, partiall improvement of local pulmonary injury was observed between 3 and 18 months for eachh of the three endpoints. After 18 months, no further improvement was seen.

Patientss with breast cancer and malignant lymphoma showed a similar improvement, which wass attributed to a recovery from the early radiation response and could not be explained by contractionn effects of fibrosis of lung parenchyma. Also in the pulmonary function tests, a partiall recovery from the radiation induced lung damage was observed between 3 and 18 monthss after treatment. Early and late reduction in VA, VC, FEV^ could be estimated before

radiotherapyy for breast cancer and lymphoma patients based on the mean radiation dose (Figuree 5), whereas for the reduction in TL C O c also the chemotherapy regimen should be taken

intoo account (Theuws 1999). After 18 months no further recovery could be observed.

Discussion n

Forr dose-escalation studies it is important to be able to estimate the radiation pneumonitis risk forr each patient individually, based on the 3D treatment plan. Lung tissue shows a strong parallell behavior and a strong volume effect when irradiated. This is reflected in the value of thee parameters in the models predicting the risk of radiation pneumonitis. The volume

1 1 0.8 8 0.6 6 Q--z Q--z 0.4 4 0.2 2 0 0 ( ( Dosee (Gy)

FigureFigure 6. Probability of radiation pneumonitis (grade > 2) versus dose for irradiation of the whole lung, 213 and 1/3 of

thethe lung according to the Lyman model (solid line) with the parameter values D50 = 30.5 Gy, m = 0.3 andn=1 (Kwa

1998c).1998c). For the seriality model (dashed line) the seriality parameter sis 0.01 (Gagliardi 2000) whereas the Dso and the steepnesssteepness parameter were taken as in the Lyman model to facilitate comparison between the models.

parameterr in the Lyman model n was equal to one, whereas in the seriality model the seriality parameterr was very small (s = 0.01). The dose-effect relations resulting from those two models forr the whole lung, 2/3 and 1/3 of the lung are shown in Figure 6. Both models show a comparablee volume effect. Parallel behavior with a volume parameter n equal to one has also beenn demonstrated for other parallel organized tissues like the parotid gland (Eisbruch 1999, Moerlandd 2000) and recently also for liver (Ten Haken 2000).

70% %

100 15 20

Meann Lung Dose (Gy)

25 5 30 0

FigureFigure 7. Scatter-plot of the mean lung dose (MLD) and the volume irradiated with more than 20 Gy (V20) of clinical

treatmenttreatment plans of 3 different patient groups of the NKI: breast cancer patients (circles), malignant lymphoma patients (squares),(squares), NSCLC patients (triangles). The correlation between the two parameters is high, r2

= 0.75 and is even higher

whenwhen the lymphoma patients are excluded (r1

= 0.9).

Becausee the models to predict the incidence of radiation pneumonitis give similar results, it is difficultt to make a decision about which model is best suited for clinical use. Of the simple parameters,, the V20 (or V30) and the mean lung dose represent the two extremes in the underlyingg dose-effect relations while the more complicated models use underlying dose-effect relationss that are more or less in between these extremes (Figure 4). The ultimate decision of thee 'best' underlying local dose-effect relation should be based on the analysis of patient data. However,, clinically applied treatment plans in the Netherlands Cancer Institute show a high correlationn (r = 0.94) between the V20 and the MLD (Figure 7). Because the two parameters aree not independent in our data set, it is not possible to test the models independently. For example,, because of the correlation between the V20 and the MLD, a certain treatment plan willl result in the same incidence of radiation pneumonitis, regardless of the use of V20 (Figure 4A)) or the MLD (Figure 4B). The shape of the mantle field irradiation of the lymphoma patients withh a low dose, but a large field-size, yields some variation in the distribution of MLD and V20, butt still more data is needed both in the region where a large part of the lung is irradiated with moree than 20 Gy and a low MLD, and in the region where a high mean lung dose coincides withh a small V20 to be able to distinguish between the models. It is quite possible that when moree clinical data becomes available, the true dose-effect relation will appear to be somewheree in between the MLD and V20, like a sigmoid local dose-effect relation. Hopefully

IrradiationIrradiation af the king: doss-volume effects

withh the ongoing dose-escalation studies additional data will be collected in the 'empty* regions off the MLD/V20 scatter-ptot

Pre-treatmentlungPre-treatmentlung function

Markss et al. (1097a) proposed to take into account both the pre-treatment lung function and thee 3D dose distribution in the design of the optimal treatment plan, by calculating Functional Dosee Volume Histograms (fDVH). These fDVHs were based on pre-treatment SPECT perfusionn data. This could result in beam setups that minimize the incidental irradiation of functioningg tissue. Although this approach certainly may have theoretical advantages, ft is basedd on the assumption that nonfunctioning areas do not and will not contribute to tine overalll lung function. However, in many patients reperfuston is observed adjacent to the tumor (Markss 1995) due to tumor regression. This probably explainss why in another paper of Marks ett al. (1997a) the prediction of radiation pneumonitis was not improved using the fDVHs comparedd to the conventional DVHs.

Conclusions s

Inn the analysis of the effect of irradiation on the lungs, many known and yet unknown factors playy a role. Because óf the complexity of the problem, the data are still inconclusive with regardd to an appropriate description of the dose-volume effect Therefore additional patient dataa is needed to adequately perform multi-variate analyses. Dose-escalation studies and multi-centerr cooperation will create more possibilities to investigate all confounding factors concerningg lung irradiation.